MATERIAL CHARACTERIZATION BY ENERGY

FILTERED SECONDARY ELECTRON SIGNALS

INSIDE THE SCANNING ELECTRON MICROSCOPE

Avinash Srinivasan

(B.Tech, VIT University, India)

A THESIS SUBMITTED

FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING

NATIONAL UNIVERSITY OF SINGAPORE

2014

DECLARATION

I hereby declare that this thesis is my original work and it has been

written by me in its entirety. I have duly acknowledged all the sources

of information which have been used in the thesis.

This thesis has also not been submitted for any degree in any

university previously.

_________________________

Avinash Srinivasan

20 August 2014

i

Acknowledgements

Upon completion of this thesis, I would like to express my deepest gratitude to

those people who have helped make this work possible.

First and foremost I would like to thank my PhD Supervisor, Associate Professor

Anjam Khursheed who has been a constant source of guidance and support. A

world expert in his field, Prof. Khursheed is a fine example of how great knowledge

leads to great humility, listening to ideas of his students and helping them to

develop those ideas with his deep understanding of the subject. I also thank him for

reading through this thesis carefully and providing his valuable comments.

Next I would like to thank the office staff at CICFAR lab, Mrs Ho Chiow Mooi,

Mr Koo Chee Keong and Ms Linn Linn, who are the backbone of the lab’s

operation, for all their administrative help and infrastructure support.

I would also like to mention Dr Hung Quang Hoang and Mr Nelliyan Karuppiah

for their help in the initial stages of my work. I also thank Mr Han Weiding for his

useful assistance in some of the experiments and Mr Suvra Sarkar for useful

discussions and inputs.

On the personal front, this acknowledgement would be incomplete without

mentioning the unwavering support and constant encouragement of my parents,

Mrs Uma Srinivasan and Mr R Srinivasan, who have backed me in all stages of my

life. I also thank my wife Indrani for all her encouragement and understanding

during my work.

ii

Table of contents

Acknowledgements .................................................................................................. i

Summary ................................................................................................................. v

List of Tables ......................................................................................................... vi

List of Figures ....................................................................................................... vii

Chapter 1 – Introduction to the thesis ..................................................................... 1

References ....................................................................................................... 7

Chapter 2 – Introduction to the SEM .................................................................... 11

2.1 Output signals inside the SEM ........................................................... 15

2.2 Objective lens improvements ............................................................. 21

2.3 Secondary electron energy analyzers SEM attachments .................... 24

2.4 Retarding Field Analyzers .................................................................. 25

2.5 Signal–to–Noise considerations ......................................................... 27

2.6 Deflection/multi–channel analyzers ................................................... 33

2.7 Full range deflection/multi–channel analyzer designs ....................... 35

2.8 Objectives of the thesis ....................................................................... 39

References ..................................................................................................... 41

Chapter 3 – Voltage and dopant concentration measurements of semiconductors

using a band–pass toroidal energy analyzer inside a SEM ................................... 47

3.1 Introduction ........................................................................................ 47

3.2 The problem of specimen fringe fields and local surface microfields 51

3.3 Experimental Results .......................................................................... 55

3.3.1 The experimental setup ............................................................... 55

iii

3.3.2 Experimental analyzer SE signals on a doped silicon specimen in

presence of specimen fringe fields ............................................................ 57

3.3.3 Experimental analyzer SE signals in presence of surface

microfields ................................................................................................ 61

3.3.4 Experimental analyzer SE signals along a semiconductor sample

with a potential gradient............................................................................ 64

3.3.5 Experimental SE analyzer dopant contrast signals from abrupt

semiconductor heterojunctions ................................................................. 67

3.4 Conclusions ........................................................................................ 72

References ..................................................................................................... 74

Chapter 4 – New contrast mechanisms and material characterization by energy

filtered secondary electron signals inside the SEM .............................................. 77

4.1 Introduction ........................................................................................ 77

4.2 Probing and analyzing buried interfaces of multifunctional oxides using

a secondary electron energy analyzer. ........................................................... 78

4.2.1 Introduction ................................................................................. 78

4.2.2 Materials and methods ................................................................ 79

4.2.3 Results and Discussion ................................................................ 82

4.3 SE signal contrast in presence of magnetic fields above the specimen

90

4.4 SE analyzer signal contrast due to surface oxidation of a thin film metal

layer specimen ............................................................................................... 94

4.5 Conclusions ........................................................................................ 98

iv

References ..................................................................................................... 99

Chapter 5 – New secondary electron energy analyzer designs for the SEM ...... 102

5.1 Introduction ...................................................................................... 102

5.2 A wide–range parallel energy analyzer design ................................. 104

5.2.1 Need for a high transmittance wide–range parallel energy analyzer

104

5.2.2 A first–order focusing wide–range PRMA design .................... 109

5.3 Experimental prototype of a RMA attachment inside a SEM specimen

chamber ....................................................................................................... 117

5.4 Conclusion ........................................................................................ 124

References ................................................................................................... 125

Chapter 6 – Conclusions and Suggestions for future work................................. 127

6.1 Conclusions ...................................................................................... 127

6.2 Suggestions for future work ............................................................. 128

Appendix A: Publications resulting from this project ........................................ 131

v

Summary

The scanning electron microscope (SEM) today is capable of providing high

resolution nanometer-level topographical images of a specimen. However, there is

potential to transform it into a nano-scale material science analytical tool. The aim

of this dissertation is to devise and develop methods to improve the analytical

capabilities of the SEM by the use of secondary electron (SE) energy analyzer

attachments. This work presents high signal to noise voltage measurements in the

presence of surface fields and dopant concentration measurements on

semiconductors using the second–order focusing toroidal analyzer. An analytical

applications such as a new application of detecting trapped charges at buried

interfaces of multifunctional oxides is demonstrated, and the results point towards

the development a new SEM analytical technique. Also a prototype of the Radial

Mirror Analyzer is developed and tested inside the SEM. A new design of a multi-

channel SE analyzer, one that can capture the SE energy spectrum, in parallel is

also presented.

vi

List of Tables

Table 3.1 – Dopant concentration measurement results for the Si/ZnO p–n

heterojunction for different p–doped samples. ..................................................... 71

Table 5.1 – Simulated energy resolution for first–order focusing PRMA designs.

............................................................................................................................. 115

vii

List of Figures

Fig. 2.1 – Schematic drawing of a conventional SEM ......................................... 12

Fig. 2.2 – Beam/Specimen interaction: (a) Interaction volume and emitted signals

(b) Energy spectrum of electrons that leave the specimen. .................................. 14

Fig. 2.3 – Monte Carlo simulation of primary electrons striking a silicon sample at

energies 1, 5, 10 and 15 keV. ................................................................................ 15

Fig. 2.4 – Conventional detector layout inside the SEM. ..................................... 16

Fig. 2.5 – Secondary electron signal generation. .................................................. 17

Fig. 2.6 – The SE Chung–Everhart energy distribution........................................ 18

Fig. 2.7 – SE energy distribution with work function variations. ......................... 19

Fig. 2.8 – Variation of SE energy distribution with changes in (a) Specimen

potential and (b) Dopant type and concentration across a p–n junction. .............. 20

Fig. 2.9 – Different types of SEM objective lenses: (a) Conventional lens (b)

Magnetic In–lens (c) Single pole lens below the specimen (d) Single pole lens

above the specimen (e) Retarding field lens and (f) Mixed–field immersion lens

[2.10, 2.11]. ........................................................................................................... 22

Fig. 2.10 – Arrangement of an energy spectrometer for conventional objective lens

type SEMs. ............................................................................................................ 23

Fig. 2.11 – General layout of a closed loop retarding field spectrometer with

hemispherical grid. ................................................................................................ 26

Fig. 2.12 – Output S–curve signals of the retarding field analyzer. ..................... 26

Fig. 2.13 – Comparison of the signal–to–noise characteristics of retarding field

analyzers with multi–channel energy analyzers as a function of cut–off energy in

the SE Chung–Everhart spectrum [2.27]. ............................................................. 31

Fig. 2.14 – Schematic of magnetic immersion lens SE analyzer layout of Kazemian

et al. [2.28, 2.29] used for quantitative dopant mapping [2.1]. ........................... 32

Fig. 2.15 – The 63° CDA Hannah voltage contrast spectrometer [2.8] (a)

Spectrometer layout (b) Experimentally acquired SE spectra for different specimen

voltages. ................................................................................................................ 34

Fig. 2.16 – Schematic layout of the electrostatic toroidal deflection analyzer

reported by Rau and Robinson [2.35]. .................................................................. 36

viii

Fig. 2.17 – Layout of a second–order focusing toroidal analyzer prototype

attachment [2.11]. ................................................................................................. 38

Fig. 3.1 – Original layout of the second–order focusing toroidal analyzer prototype

attachment: (a) Experimental layout (b) Original specimen holder layout [3.3]. . 47

Fig. 3.2 – Experimental SE spectrum reported by Hung et al. [3.3] (a) full range

and (b) selected range in which curve 2 (dotted line) is obtained by shifting curve

1 by 12 mV in order to demonstrate the noise limit. ............................................ 48

Fig. 3.3 – Experimental secondary electron output signals at different specimen

biasing voltages reported by Hoang et al. [3.3]. ................................................... 49

Fig. 3.4 – Experimental secondary electron signals showing improved signal–to–

noise when specimen/inner cap is biased at −10 and −10.1 V shown around the

peak value: (a) Deflection voltage range from 7 to 8 V and (b) deflection voltage

range from 7.1 to 7.16 V [3.3]. ............................................................................. 50

Fig. 3.5 – Direct ray tracing of a 0.5 eV electron (polar launch angle 45 degrees)

with fringe fields above the specimen; the specimen is biased more negative with

reference to the inner cap. The dotted path shows the electron trajectory without

fringe fields (Specimen = – 10 V). ....................................................................... 52

Fig. 3.6 – Simulated potential distribution and electron trajectories of 0.5 eV and

0.4 eV electrons (polar launch angle 45) in the presence of Type I surface

microfields. The dotted line shows the simulated trajectory of the electron without

surface fields. ........................................................................................................ 54

Fig. 3.7 – Simulated potential distribution and electron trajectory of a 0.5 eV

electron (polar launch angle 45) in the presence of Type II surface microfields.

The dotted line shows the simulated trajectory of the electron without surface fields.

............................................................................................................................... 54

Fig. 3.8 – The second–order toroidal energy analyzer SEM attachment: (a)

Experimental layout in the SEM chamber (b) Schematic of the modified specimen

holder indicating the bias voltages applied to the various components of the holder.

............................................................................................................................... 56

Fig. 3.9 – Experimental SE signals obtained from an n–type semiconductor sample:

(a) Specimen biasing from – 10 to –13 volts with VC1 = –10 V, VC2 = 0 V. Inset

shows the biasing condition of the sample holder (b) Experimental SE signals at

different specimen biasing voltages where VS = VC1 (c) A plot of PMT signal

expectation value () for specimen potential change (ΔVs) from 0 to 3 V in presence

of specimen fringe fields. ...................................................................................... 59

Fig. 3.10 – Experimental SE signals obtained from a copper wire in presence of

surface fields: (a) Specimen arrangement to generate microfields above the point

of probing (b) SE signals obtained from the specimen for different biasing of the

ix

copper wire (c) A plot of PMT signal expectation value () for copper wire potential

change (ΔVs) from 0 to 4 V in presence of surface fields above the point of probing.

............................................................................................................................... 63

Fig. 3.11 – Experimental SE signals obtained by setting up a potential gradient

along a semiconductor sample: (a) Specimen arrangement using a button cell (b)

SE signals obtained from the specimen along the x direction (c) A plot of

expectation value µ of the SE signal against the change in potential ΔVS along

distance x. .............................................................................................................. 66

Fig. 3.12 – SE analyzer signal contrast from a n–ZnO / p–Si heterojunction: (a)

Schematic representation of the fabricated thin–film ZnO on Silicon substrate (b)

Experimental SE signals obtained from the p–side and the n–side of each

heterojunction sample for samples A, B, C and D (c) Plot of difference in

expectation value Δ of the SE analyzer signal obtained from the p and n sides of

the Si/ZnO heterojunction against the log of doping concentration of the p–type

silicon substrate. The solid bars at each point on the graph represent standard

deviation of Δ taken over 10 SE signals. ............................................................ 70

Fig. 4.1 – Layout of the specimen holder arrangement of the second–order focusing

toroidal energy analyzer showing the mounting of the LAO/STO specimen. ...... 79

Fig. 4.2 – Schematic representation of the specimen: (a) Representation of the

2DEG formed at the interface of crystalline LAO and crystalline STO substrate (b)

Conducting and insulating interface regions side by side on the same sample (the

interface was made insulating by proton irradiation). .......................................... 81

Fig. 4.3 – Experimental SE analyzer signals obtained from an uncoated STO

substrate (shown in dotted line) and from the LAO/STO heterointerface with

conducting interface (shown in solid line). A primary beam acceleration voltage of

3 kV was used. ...................................................................................................... 83

Fig. 4.4 – Experimental SE analyzer signals obtained from the LAO/STO

heterointerface with conducting interface (shown in solid line) and the insulating

LAO/STO heterointerface (shown in dotted line). A primary beam acceleration

voltage of 3 kV was used. ..................................................................................... 84

Fig. 4.5 – Experimental secondary electron signals obtained from LAO/STO

hetero–interface at various primary beam energies. The signals are obtained at

primary beam electron energies of 2 keV, 3 keV, 4 keV and 5 keV (shown in green,

brown, pink and blue respectively). ...................................................................... 86

Fig. 4.6 – Monte Carlo simulation of the electron trajectories: (a) Primary

beam/specimen interaction indicating the interaction volume of the electrons (b)

Energy contour of the percentage energy loss of primary beam electrons along the

depth of the specimen (c) A graphical plot of percentage energy loss of primary

x

beam electrons against the depth from the surface of the specimen. The red dotted

line indicates the LAO/STO interface at a depth of 8nm from the surface. ......... 89

Fig. 4.7 – Schematic representation of the specimen holder with a current carrying

solenoid placed under the specimen to produce magnetic field. (Cross–section view

of the specimen holder is shown here, while the solenoid is shown completely). 91

Fig. 4.8 – Experimental SE analyzer signals obtained from a metal specimen in

presence of magnetic field (B) created by current carrying solenoid under the

specimen: (a) SE analyzer signals obtained with B field along positive z direction

(b) SE analyzer signals obtained with B field along negative z direction (c) A plot

of SE analyzer signal expectation value (µ) against current flowing in the solenoid

creating the magnetic field (negative value of current indicates a current giving rise

to a B field along negative z–axis) ........................................................................ 93

Fig. 4.9 – Mounting of the Al coated silicon specimen inside the specimen holder

of the analyzer. ...................................................................................................... 95

Fig. 4.10 – (a) Experimental SE analyzer signals obtained from a thin film Al layer

under varying time of exposure to air (b) A plot of the SE analyzer signal

expectation value against the exposure time in air of the Al thin film. ................ 97

Fig. 5.1 – Simulated trajectory paths through the Radial Mirror Analyzer (RMA)

design by Hoang et al. [5.1], 13 rays are plot over a polar angular spread () of

6 in uniform angular steps, shown here from the specimen to the detector plane at

the central energy Ep. .......................................................................................... 102

Fig. 5.2 – Simulated trajectory paths through a planar ideal hyperbolic field

analyzer design at the energies 100, 200, 500, 1000, 3000 and 5000 eV. For each

energy, eleven trajectories are plot evenly between −1.1° and 1.1° around a 25°

polar entrance angle. ........................................................................................... 110

Fig. 5.3 – Simulated ray paths for energies 250, 750, 1250, 1750 and 2500 eV in

the ideal HFA electrode layout (R0 = 2 cm and V0 = –1500 volts) transformed into

axi–symmetric cylindrical coordinates. Nine trajectories plot with an angular

spread over 1.1. .............................................................................................. 112

Fig. 5.4 – Simulated trajectory paths through a first–order focusing PRMA design.

Electrons are plot for energies 50, 100, 200, 500, 1000, 1500, 2000 and 2500 eV

with 9 electron trajectories over a polar angular spread of ± 1.1˚ around a central

angle of 24.8˚. V1 = – 45V; V2 = – 120 V; V3 = – 285 V; V4 = –775V ; V5 = –

1150V; V6 = – 1675V; V7 = – 2020V. ................................................................. 113

Fig. 5.5 – Simulated spot size charcteristics of the first–order focsuing PRMA

design: (a) Direct ray paths at the focal plane for 2% energies around the central

energies of 500 eV and 1500 eV (b) Trace–width as a function of input polar

angular spread ranging from –20 mrad (–1.145) to +20 mrad (+1.145). ........ 116

xi

Fig. 5.6 – Schematic diagram showing the integration of the RMA attachment

inside the SEM chamber with other components. Such a mounting of the analyzer

facilitates operation of the SEM in the normal imaging mode. .......................... 119

Fig. 5.7 – Experimental layout of the RMA inside the SEM. ............................. 120

Fig. 5.8 – A prototype of the RMA attachment: (a) Cross–section 3D CAD model

(b) A photo of the attachment integrated inside the SEM.The azimuthal deflection

angle is 100. ....................................................................................................... 122

Fig. 5.9 – Experimental SE analyzer signals obtained using the first experimental

prototype of the RMA. ........................................................................................ 123

Fig. 6.1 – Proposed modification of the second order focusing toroidal analyzer

where the specimen is independent of the main analyzer body, allowing free

movement of the specimen. ................................................................................ 128

Fig. 6.2 – Proposed post analyzer deflector arrangement for the RMA attachment;

7 rays are plot over a polar angular spread () of 6 in uniform angular steps,

shown here from the specimen to the scintillator of the PMT through the post

analyzer deflector, at the central energy Ep. The magnitude of VPD was

experimentally calculated to be 0.436EP. ........................................................... 130

xii

List of Symbols

SYMBOL

DESCRIPTION

χ Analyzer voltage Resolution Constant

ρ Mass density

μ Signal expectation value / mean

Δμ Change in signal mean

Δθ Polar angular spread

ΔVS Change in specimen voltage,

ΔVR Change in Retarding grid voltage

Z Atomic number

W Working distance

VSC Scintillator Voltage

VS Specimen voltage

VR Retarding grid voltage

VPD Post analyzer deflector plate voltage

(magnitude)

VDEF Analyzer deflection electrode

VC2 Outer conical cap voltage

VC1 Inner conical cap voltage

V1, V2, V3, VD RMA electrode potentials

V1, V2, V3, V4, V5, V6, V7 First–Order PRMA electrode potentials

V0 Potential on a curved hyperbolic shaped

electrode

V(x,y) Potential field distribution

V Primary beam voltage

SEM Scanning Electron Microscope

SE1, SE2, SE3 Types of Secondary Electrons

SE Secondary electron

R Interaction volume

PO2 Partial pressure of Oxygen

PMT Photo multiplier tube

xiii

NS0 Total number of emitted secondaries

ND n-type doping level

I Current

EP Pass energy of an analyzer

EDS Energy Dispersive X-ray Spectroscopy

BSE Backscattered electrons

B Magnetic field

AE Auger electron

A Atomic weight

Chapter 1

1

Chapter 1 – Introduction to the thesis

The aim of this thesis is to devise and develop methods to improve the analytical

capabilities of the scanning electron microscope (SEM) by the use of electron

energy analyzer attachments. The SEM today is capable of providing high

resolution nanometer–level topographical images of a specimen. However, there is

potential to transform it into a nano-scale material science analytical tool.

Currently, the main analytical tool used inside the SEM is the well-known Energy

Dispersive X-ray Spectroscopy method (EDS or EDX). But EDS is limited by its

spatial resolution (typically about 1 μm) and also not suitable for low energy

primary beam applications [1.1].

There is a need for an energy spectral analyzer inside the specimen chambers of

SEMs, because generally, the detector system of conventional SEMs cannot

differentiate between scattered electrons of different energies that leave the

specimen when it is irradiated by the SEM primary beam. The type of information

that can be obtained by analyzing the energy spectrum of the scattered electrons

will be illustrated later in this chapter. The additional information obtained by the

use of electron energy analyzers in the SEM, designed to fit as add-on attachments,

can be collected concurrently with the normal topographical signal, and therefore

be mapped on to high resolution images of the specimen. Historically, SEM

electron energy spectrometers were first developed for the purpose of quantifying

specimen surface voltage changes. Electron beam testers were developed to make

contactless quantitative voltage measurements on integrated circuits (IC).

However, with the evolution of IC technology, multiple upper layers of metal lines

Chapter 1

2

were added to the IC, like power busses, high density routing signals, ground plane

and bond pads, preventing the probing of the circuit’s active regions by focused

electron beam testing methods.

At the turn of the 21st century, there was renewed interest in exploring possibilities

of using electron energy analyzers for applications other than voltage contrast,

mainly for material characterization purposes. The higher energy scattered

electrons, known as backscattered electrons (BSE), are commonly used for

qualitative material contrast mapping inside the SEM. However, by capturing their

energy spectrum, some degree of quantitative material characterization can be

performed since the shape of the BSE spectrum is dependent on the atomic number

of the specimen. This possibility was reported by Luo and Khursheed [1.2], who

correlated experimental BSE spectra with Monte Carlo simulations and applied the

technique for single elemental material analysis. Other researchers have reported

the possibilities of using the BSE energy spectrum for microtomography of layered

microstructures [1.3], measurement of surface potential and charge build-up on

insulator surfaces [1.4], and thickness measurements of ultrathin films on bulk

substrates [1.5].

It is in principle also possible to obtain signature Auger electron (AE) peaks in the

SEM scattered electron spectrum for elemental or compositional analysis.

Normally, Auger Electron Spectroscopy (AES) can only be performed under Ultra-

High Vacuum (UHV) conditions, however, Cubric [1.6] and El-Gomati [1.7]

demonstrated that it is possible to perform AES in vacuum High-Vacuum (HV)

level conditions, comparable to the HV inside SEM specimen chambers. In order

Chapter 1

3

to achieve this, a low voltage ion flood gun for cleaning of the specimen surface

must first be used, followed by relatively fast acquisition of the energy spectrum by

an energy analyzer (tens of milliseconds), before significant buildup of hydro-

carbon layers on the specimen surface.

Lower energy scattered electrons, known as secondary electron (SE) signals,

normally used to obtain topographical image of the specimen inside a conventional

SEM, also carry useful analytical information about the specimen. These can be

used to measure variations in parameters such as specimen surface potential,

semiconductor doping concentration and work function. Quantitative mapping of

doping concentration in semiconductors inside the SEM has received particular

attention recently. Recent studies have demonstrated that by monitoring changes in

the SE signal, it is possible to obtain quantitative dopant mapping in

semiconductors [1.8-1.17]. The most common method for doing this is to extract

contrast directly from an SE image [1.8-1.11], but this is not an accurate way to do

it, since the conventional SE detector captures a bulk signal formed from electrons

that leave the specimen over a wide range of different energies and angles, making

the output signal dependent on a number of other dynamic factors besides dopant

concentration levels in the specimen [1.1, 1.18-1.20]. More reliable quantitative

information about dopant concentration changes can be obtained via the use of an

electron energy analyzer, which relies on detecting shifts in the scattered SE energy

spectrum, in a manner similar to that used in Electron Beam Testers [1.21]. This

approach has been reported in a recent work by Kazemian et al [1.16, 1.17] and by

some other researchers [1.12-1.14]. However, they use relatively poor electron

Chapter 1

4

energy analyzer designs, from a signal-to-noise point of view, limiting the accuracy

to which shifts in the SE energy spectrum can be monitored. The minimum shift in

the SE energy spectrum which can be detected by their methods is typically in the

“a-tenths of an eV” range. To determine dopant concentration levels in a

semiconductor specimen, better accuracy is required; shifts typically less than a few

meV need to be detected. The accuracy of measurement is fundamentally

determined by the signal–to–noise characteristics of the SE electron energy

analyzer used to obtain the SE spectrum. Better energy analyzer designs have

already been presented within the context of quantitative voltage contrast, and an

obvious starting point is to use some of these ideas for the application of dopant

concentration mapping. Apart from dopant concentration mapping, the technique

of using SE energy analyzers inside the SEM can be applied to other types of

specimens, in a search to find more useful contrast mechanisms.

Recently, high signal-to-noise experimental results have been obtained from a

second–order focusing toroidal electron energy analyzer by Khursheed et al.[1.22];

they were able to measure shifts in a signal related to the SE energy spectrum in the

sub eV range [1.23]. However these results were obtained under the idealized

condition of a field free region above the specimen. In practice, the SEs that leave

the specimen are affected significantly by a variety of different surface fields and

fringe fields. Fringe fields are generated from potential differences between the

sample and surrounding electrodes, while surface fields occur due to localized

potential variations caused by primary beam induced effects such as specimen

charging and contamination. More work is required in order to establish whether

Chapter 1

5

the superior signal-to-noise characteristics, reported for the second–order focusing

toroidal analyzer, can be obtained under more realistic specimen conditions like

where fringe fields and surface fields are present.

After their work on the second–order toroidal analyzer, Hoang and Khursheed

presented the Radial Mirror Analyzer (RMA) attachment design for the SEM

[1.24]. Simulation results predict that the RMA design has several advantages over

the second–order focusing toroidal energy analyzer, both in terms of its integration

to the SEM’s primary beam optics, and its own dispersive/focusing properties.

However, a practical RMA prototype needs to be made and tested in order to verify

the simulations predictions. Another promising area for research is to find a feasible

parallel energy analyzer attachment design, where the SE spectrum is captured by

a number of detection channels, all operating simultaneously, instead of the

conventional approach of using a single detection channel operating sequentially.

This promises to greatly speed up data-acquisition times, and may therefore provide

a practical way of mapping secondary electron energy spectral information and

overlaying it on top of the SEM’s topographical image.

The main objective of this thesis work is to further develop the use of secondary

electron energy analyzer attachments for the SEM. The first aim is to investigate

how the second–order focusing toroidal energy analyzer attachment functions in

the presence of surface fields, and whether it can be used to make high signal-to-

noise voltage and dopant concentration measurements on semiconductor

specimens. Experimental results were obtained to demonstrate that although the SE

analyzer signals are greatly changed under the influence of fringe fields and surface

Chapter 1

6

fields, they can nevertheless provide high signal-to-noise voltage and dopant

concentration measurements on semiconductor specimens. The second aim of the

thesis is to use the technique of secondary electron energy filtering in the SEM to

find new useful contrast mechanisms. A new application of detecting trapped

charge at the interface of multi-layer thin insulator films was found, and the results

point towards the development of a new SEM analytical technique. The third aim

of the thesis is to experimentally test the RMA design and compare its performance

to simulation predictions. A prototype of the RMA was made and tested inside a

SEM, and the experimental results verified the design principle of the analyzer. The

fourth objective of the thesis is to develop a viable multi-channel secondary

electron energy analyzer design, one that can capture the SE energy spectrum in

parallel. The work carried out in this section of the thesis led to the development of

new Parallel Radial Mirror Analyzer design [1.25].

Chapter 1

7

References

1.1. Goldstein, J., et al., Scanning electron microscopy and X-ray microanalysis.

2003: Springer.

1.2. Luo, T. and A. Khursheed, Elemental identification using transmitted and

backscattered electrons in an SEM. Physics Procedia, 2008. 1(1): p. 155-

160.

1.3. Niedrig, H. and E. Rau, Information depth and spatial resolution in BSE

microtomography in SEM. Nuclear Instruments and Methods in Physics

Research Section B: Beam Interactions with Materials and Atoms, 1998.

142(4): p. 523-534.

1.4. Jbara, O., et al., Surface potential measurements of electron-irradiated

insulators using backscattered and secondary electron spectra from an

electrostatic toroidal spectrometer adapted for scanning electron

microscope applications. Review of Scientific Instruments, 2001. 72(3): p.

1788-1795.

1.5. Schlichting, F., D. Berger, and H. Niedrig, Thickness determination of

ultra‐thin films using backscattered electron spectra of a new toroidal

electrostatic spectrometer. Scanning, 1999. 21(3): p. 197-203.

1.6. Cubric, D., et al., Parallel acquisition electrostatic electron energy analyzers

for high throughput nano-analysis. Nuclear Instruments and Methods in

Physics Research Section A: Accelerators, Spectrometers, Detectors and

Associated Equipment, 2011. 645(1): p. 227-233.

1.7. El-Gomati, M., C. Walker, and X. Zha, Towards quantitative scanning

electron microscopy: Applications to nano-scale analysis. Nuclear

Chapter 1

8

Instruments and Methods in Physics Research Section A: Accelerators,

Spectrometers, Detectors and Associated Equipment, 2011. 645(1): p. 68-

73.

1.8. Tsurumi, D., K. Hamada, and Y. Kawasaki, Energy-filtered imaging in a

scanning electron microscope for dopant contrast in InP. Journal of Electron

Microscopy, 2010. 59(S1): p. S183-S187.

1.9. Chung, S., et al., Secondary electron dopant contrast imaging of compound

semiconductor junctions. Journal of Applied Physics, 2011. 110(1): p.

014902.

1.10. Tsurumi, D., K. Hamada, and Y. Kawasaki, Energy-Filtered Secondary-

Electron Imaging for Nanoscale Dopant Mapping by Applying a Reverse

Bias Voltage. Japanese Journal of Applied Physics, 2012. 51(10R): p.

106503.

1.11. Tsurumi, D., K. Hamada, and Y. Kawasaki, Highly Reproducible

Secondary Electron Imaging under Electron Irradiation Using High-Pass

Energy Filtering in Low-Voltage Scanning Electron Microscopy.

Microscopy and Microanalysis, 2012. 18(02): p. 385-389.

1.12. Heath, J.T., C.-S. Jiang, and M.M. Al-Jassim, Measurement of

semiconductor surface potential using the scanning electron microscope.

Journal of Applied Physics, 2012. 111(4): p. 046103.

1.13. Rau, E. and A. Tagachenkov, Image contrast of impurity regions of

semiconductor crystals in scanning electron microscopy. Bulletin of the

Russian Academy of Sciences: Physics, 2013. 77(8): p. 943-947.

Chapter 1

9

1.14. Chee, A.K., et al., A quantitative model for doping contrast in the scanning

electron microscope using calculated potential distributions and Monte

Carlo simulations. Journal of Applied Physics, 2011. 109(1): p. 013109.

1.15. El‐Gomati, M., et al., Why is it possible to detect doped regions of

semiconductors in low voltage SEM: a review and update. Surface and

interface analysis, 2005. 37(11): p. 901-911.

1.16. Kazemian, P., et al., High resolution quantitative two-dimensional dopant

mapping using energy-filtered secondary electron imaging. Journal of

Applied Physics, 2006. 100(5): p. 054901.

1.17. Kazemian, P., et al., Quantitative secondary electron energy filtering in a

scanning electron microscope and its applications. Ultramicroscopy, 2007.

107(2–3): p. 140-150.

1.18. Oatley, C.W., The scanning electron microscope. Sci. Prog., Oxf, 1966. 54:

p. 483-495.

1.19. Reimer, L., Scanning electron microscopy: physics of image formation and

microanalysis. Measurement Science and Technology, 2000. 11(12): p.

1826.

1.20. Wells, O.C., Scanning electron microscopy. 1974: McGraw-Hill.

1.21. Thong, J.T., Electron beam testing technology. 1993: Plenum Publishing

Corporation.

1.22. Khursheed, A. and H.Q. Hoang, A second–order focusing electrostatic

toroidal electron spectrometer with 2π radian collection. Ultramicroscopy,

2008. 109(1): p. 104-110.

Chapter 1

10

1.23. Hoang, H., M. Osterberg, and A. Khursheed, A high signal-to-noise ratio

toroidal electron spectrometer for the SEM. Ultramicroscopy, 2011. 111(8):

p. 1093-1100.

1.24. Hoang, H.Q. and A. Khursheed, A radial mirror analyzer for scanning

electron/ion microscopes. Nuclear Instruments and Methods in Physics

Research Section A: Accelerators, Spectrometers, Detectors and Associated

Equipment, 2011. 635(1): p. 64-68.

1.25. Khursheed, A., H.Q. Hoang, and A. Srinivasan, A wide-range Parallel

Radial Mirror Analyzer for scanning electron/ion microscopes. Journal of

Electron Spectroscopy and Related Phenomena, 2012. 184(11): p. 525-532.

Chapter 2

11

Chapter 2 – Introduction to the SEM

A good understanding of the working of the SEM is essential to understand and

appreciate how electron energy analyzers inside the SEM work and how the SEM

can be used to obtain useful analytical information about the sample in addition to

high resolution topographical images, extracted by the use of energy analyzers.

Fig. 2.1 [2.1] shows a schematic drawing of the layout of a conventional SEM. A

typical SEM column consists of an electron gun, two condenser lenses, an aperture,

an objective lens, an electron detection system, and a set of deflectors, all operating

in a vacuum.

The electron gun, which can be of thermionic tungsten or LaB6 gun or field

emission type, acts as a source of electrons which are accelerated to energies in the

range of 1 to 30 keV inside the column and then focused into an electron probe of

diameter 1 to 10 nm carrying current in the range of 1 to 100 pA. For obtaining

higher current, larger probe diameters may be used, this however would result in a

trade–off on the spatial resolution of the SEM.

This electron probe, also called the primary beam spot, is scanned in a raster–like

pattern across the specimen by the deflection system in front of the final lens and

is operated in synchronization with the detector electronics to produce

topographical images of the specimen. Depending on the type of scattered electron

detected from specimen, the SEM can produce different types of high resolution

images like SE images or BSE images.

Chapter 2

12

Fig. 2.1 – Schematic drawing of a conventional SEM

The primary beam/specimen interaction produces various types of signals which

are a useful source of both topographical and analytical information about the

specimen. A schematic representation of this beam/specimen interaction is shown

in Fig. 2.2a. The primary beam penetrates into the specimen, and in the process

scatters electron of various energies through elastic and inelastic collisions.

Electrons which are scattered inelastically near the surface of the specimen are

Electron Gun

Chapter 2

13

known as secondary electrons (SEs), while electrons that are generated through

multiple elastic collisions from deeper levels are known as backscattered electrons

(BSEs). Secondary electrons and backscattered electrons make up the most

common signals for imaging using the SEM. Auger electrons (AEs) are electrons

having characteristic energies that are ejected from atoms by absorbing the energy

released by the relaxation of another electron into a lower energy inner–shell

vacancy. The energy distribution of the SEs, BSEs and AEs is shown in Fig. 2.2b.

SEs are low energy electrons, usually defined to be below 50 eV. Even in this range,

most secondary electrons lie between 0.5 eV and 5 eV. BSEs on the other hand, by

definition, are electrons with energies from 50 eV up to the primary beam energy.

It is important to understand how the primary beam is scattered inside the specimen.

This can be done by using Monte Carlo simulation programs developed for this

purpose.

a

Chapter 2

14

Fig. 2.2 – Beam/Specimen interaction: (a) Interaction volume and emitted signals

(b) Energy spectrum of electrons that leave the specimen.

Fig. 2.3 shows the results of Monte Carlo simulations carried out using one such

program, Casino [2.2]. For a thick specimen (thickness > 1 µm), it can be seen that

the depth of interaction volume, R (refer Fig. 2.2a) increases with increasing

primary beam energy. The depth of interaction volume also depends on the nature

of the specimen such as mass, density and atomic number.

An approximate formula for estimating R has been given by Kanaya and Okayama

[2.3]

𝑅 =0.0276𝐴𝑉1.67

𝑍0.889𝜌(µm)

where V is the primary beam voltage, A is the atomic weight, is the mass density

and Z is the atomic number.

b

Chapter 2

15

Fig. 2.3 – Monte Carlo simulation of primary electrons striking a silicon sample at

energies 1, 5, 10 and 15 keV.

2.1 Output signals inside the SEM

Fig. 2.4 schematically depicts the detector systems inside the SEM to detect

secondary electrons and backscattered electrons. As already stated, these signals

are the two most common electron signals inside the SEM.

The most common type of secondary electron detector was proposed by Everhart

and Thornley [2.4] and is often simply referred to as the E–T detector. The E–T

detector is electrically isolated from the rest of the SEM and consists of an outer

wire mesh that is typically biased up at 200 to 300 V, attracting the low–energy

1 µ

m

1 keV

10 keV

5 keV

15 keV

Chapter 2

16

secondaries inside the mesh, where they are accelerated by a positive voltage on a

scintillator, typically biased up at 10 – 12 keV.

Fig. 2.4 – Conventional detector layout inside the SEM.

The accelerated electrons produce photons when they hit a scintillator, which are

then amplified by a photomultiplier tube to convert the light into amplified

electrical signals.

Backscattered electron detectors on the other hand, are placed under the final lens

lower pole piece and are typically in the form of a disc with a hole in the center

through which the primary beam can pass. These detectors may either be of a

micro–channel plate type or a silicon p–n junction photodiode type. Recent electron

energy analyzers [2.5, 2.6] have also been designed to occupy a similar position as

BSE detectors, since it does not obstruct other detectors (EDS), and this provides

the opportunity for concurrent SE imaging while acquiring SE spectral information.

Chapter 2

17

Fig. 2.5 [1] shows the different ways in which the secondary electrons are generated

inside the SEM. While SE1 are the SEs generated by the primary beam within a few

nanometers from the surface of the specimen, SE2 are SEs generated within the

same region by backscattered electrons. Secondaries generated by the scattering of

backscattered electrons on external surfaces other than the specimen (such as

chamber walls, the lower lens pole–piece) are called SE3. As SE1 emanate from the

top "few–nanometers" layer of the specimen, they are capable of providing high

resolution information about the specimen. SE2 and SE3 on the other hand emanate

from indirect interactions from backscattered electrons and therefore, in general,

degrade the final image resolution.

Fig. 2.5 – Secondary electron signal generation.

Chapter 2

18

In general, the Chung–Everhart distribution [2.7] is a good approximation to the

energy distribution of secondary electrons. The distribution is given by

𝑑𝑁

𝑑𝐸=

6𝑊2𝑁𝑠𝑜𝐸

(𝐸 + 𝑊)4

where E is the kinetic energy of the SEs leaving the specimen, W is the specimen

work function, and NS0 is the total number of secondaries that are emitted. A plot

of this distribution for gold (W = 5.1 eV) is shown below in Fig. 2.6.

As seen in Fig. 2.6, the distribution of SE increases steeply at lower energies and

then falls down gradually for higher energies, indicating that most secondaries have

energies below 5 eV. This graph is usually referred to as the normal SE energy

distribution.

Fig. 2.6 – The SE Chung–Everhart energy distribution.

Gold

Chapter 2

19

Clearly, the SE spectrum will vary for various types of specimens (as their work

functions differ) and for different specimen conditions (like biasing of the

specimen). To illustrate this, Fig. 2.7 below shows the variation of the SE spectrum

for specimens with work functions 4, 4.5 and 5 eV.

Fig. 2.7 – SE energy distribution with work function variations.

Other analytical information that SE signals can provide and which are commonly

extracted from the SE energy distribution inside a SEM are specimen surface

potential and dopant concentration. Fig. 2.8a illustrates the variation of the SE

energy spectrum with specimen voltage. The kinetic energy of a secondary electron

is increased or decreased depending on the sample biasing, and this causes the SE

spectrum to shift. For negative changes in the specimen potential, the SE spectrum

shifts to the right.

The SE spectrum also varies with dopant type and dopant levels, as depicted in Fig.

2.8b above for a p-n junction.

Work Function (eV)

4

4.5

5

Chapter 2

20

Fig. 2.8 – Variation of SE energy distribution with changes in (a) Specimen

potential and (b) Dopant type and concentration across a p–n junction.

Conventional SEMs are not able to extract the information shown in Fig. 2.8, as

they are not designed to capture the energy spectrum of the scattered electrons that

leave the specimen. The bulk output signal, used to form a conventional SEM

image, is formed from SEs that are emitted over a wide range of energies and

angles. In order to capture the SE energy spectrum inside a SEM, some form of

energy analyzer needs to be incorporated into its specimen chamber.

The accuracy with which specimen voltage or dopant concentration changes can be

quantified depends primarily on the ability of the SE energy analyzer to detect small

shifts (fractions of an eV) in the SE energy distribution. For monitoring shifts in

the SE spectrum the usual practice was to track its peak position [2.8], however a

more general and holistic method was suggested by Khursheed [2.9] who

monitored the change in the expectation value of the SE energy curve to quantify

its shifts. The expectation value not only tracks the peak position of a signal but

a b

Chapter 2

21

also responds to changes in its shape and therefore is a more useful parameter for

asymmetric distributions like the SE spectrum. This has been discussed in detail in

chapter 3 of this thesis.

Other common factors that affect the accuracy of the voltage measurement are

surface fields on the specimen to be discussed in more detail in the next chapter. A

variety of different analyzers for quantitative voltage contrast have been developed

and their relative weaknesses and strengths will be discussed in the subsequent

sections.

2.2 Objective lens improvements

One important factor determining the design of a SE energy analyzer design

attachment is how it fits together with the SEM objective lens. A variety of

objective lenses have been developed for the SEM, as shown in Fig. 2.9. In the

conventional SEM, the specimen is placed in the free–field region below the final

pole–piece of the objective lens as illustrated in Fig. 2.9a [2.10]. The working

distance in this case is defined by the distance between the final pole piece of the

SEM objective lens and the specimen, normally ranging from 5 mm to 30 mm.

Electron energy analyzers designed to integrate with such an objective lens

arrangement need to be directly placed in between the lower pole–piece of the

objective lens and the specimen, in the same general region as the standard SE or

BSE detectors, as illustrated in Fig. 2.10.

The main drawback of this arrangement is that placing the analyzer below the SEM

objective lens results in a large working distance (W). A larger working distance

increases the on–axis aberrations of the primary beam spot on the specimen, which

Chapter 2

22

in turn significantly degrades the image resolution. Also, another challenge lies in

acquiring signals from the analyzer while concurrently allowing operation of the

SEM in its imaging mode (using the conventional E–T detector). Analyzer designs

and prototypes reported in chapter 5 allow for this possibility.

Fig. 2.9 – Different types of SEM objective lenses: (a) Conventional lens (b)

Magnetic In–lens (c) Single pole lens below the specimen (d) Single pole lens

above the specimen (e) Retarding field lens and (f) Mixed–field immersion lens

[2.10, 2.11].

c d

a b

e f

Chapter 2

23

Fig. 2.10 – Arrangement of an energy spectrometer for conventional objective lens

type SEMs.

The objective lens designs shown in Figs. 2.9b–f were developed to either to

improve the SEM spatial resolution (smaller primary beam spot) and/or lower the

landing energy of the primary beam on the specimen. They include a magnetic in–

lens design, where the specimen is placed in the lens gap region, as shown in Fig.

2.9b; semi–in lenses where the magnetic field extends beyond a single lens pole–

piece (Figs. 2.9c–d), a retarding field lens, where the primary beam is slowed down

just before it strikes the specimen (Fig. 2.9e); and a mixed field immersion lens,

where the specimen is immersed in both a retarding electric field and a strong

magnetic field (Fig. 2.9f). A more detailed review of these types of objective lens

improvements can be found in the work presented by Khursheed [2.10]. In the

present work, only secondary electron energy analyzers for conventional lenses will

be considered (shown in Fig. 2.9a), since they can be made as attachments that can

be readily placed in the specimen chamber. For the other types of objective lenses,

Chapter 2

24

secondary electrons must first travel back through the objective lens bore before

their energies can be analyzed. General purpose energy analyzer attachments for

SEMs that use such objective lenses are difficult to design, since access to the

region either above or inside the objective lens is not usually provided.

2.3 Secondary electron energy analyzers SEM attachments

Even within the category of conventional objective lenses, a wide variety of

different analyzer designs have been developed. As mentioned earlier, traditionally,

analyzers were developed to fit between the final pole piece of the objective lens

and the sample. This has the undesirable effect of increasing the working distance,

increasing on–axis aberrations of the primary beam spot on the specimen, and

therefore resulting in a poorer image resolution. Ideally, the spectrometer needs to

fit into the vacuum chamber of the specimen chamber, without increasing the

working distance. In addition, it should also be designed to have high transmittance,

high energy resolution and/or high signal–to–noise characteristics. Transmittance

in this context is the collection efficiency of the spectrometer, defined as the

fraction of the number of electrons at a particular energy which reach the detector

to the number of electrons that leave the sample. Depending on the application, the

energy resolution of the analyzer may also be important; that is the ability of the

analyzer to distinguish between two different peaks in the energy spectrum. In

general, a high transmittance and a high energy resolution are preferred for most

applications. However, for SE energy analyzers, energy resolution is not as

important as the ability to detect shifts in the spectrum or changes in its shape,

which requires minimizing the effects of noise on the spectrum (maximizing

signal–to–noise). More will be said about this important point in the next section

Chapter 2

25

and in a later chapter. In the following section, various types of spectrometers for

different applications in the SEM are discussed.

2.4 Retarding Field Analyzers

As already mentioned, SE energy analyzers in the SEM have generally been used

for quantifying voltage contrast. One of the first types of analyzers used for

quantifying voltage contrast was the retarding field analyzer, as illustrated in the

schematic diagram shown in Fig. 2.11.

Retarding field analyzers work on the principle that the scattered SE electrons are

made to travel in a retarding electric field, defined by the difference between a

retarding grid voltage, VR, and the specimen voltage, VS. Only the secondaries with

an energy greater than e(VR– VS) will surmount the retarding grid and reach the

detector. The signal at any particular value of VR is the sum of the contributions of

all the electrons beyond the potential barrier and is represented by the shaded region

in the SE spectrum shown in Fig. 2.11. This type of analyzer therefore works like

a high pass filter, and the SE energy spectrum is collected in its integrated form.

When the retarding field spectrometer is used for voltage contrast applications, it is

operated in a closed feedback mode [2.12]. In such a mode of operation, the strength

of the potential barrier is varied using a feedback loop to maintain a constant current

output. In this case, ΔVR is the change in VR needed to maintain a constant current

output equals the change in specimen voltage. The output signal of the retarding

field analyzer is an S–curve, as illustrated in Fig. 2.12, the integrated form of the

SE spectrum. The figure also shows the shift in the S–curve when the voltage of

the specimen changes from VS1 to VS2.

Chapter 2

26

Fig. 2.11 – General layout of a closed loop retarding field spectrometer with

hemispherical grid.

Fig. 2.12 – Output S–curve signals of the retarding field analyzer.

Objective lens

PE

Extraction Grid

Retarding Grid VR E2

E1 Specimen VS

VS

VS1 VS2

VR

Signal offset

Chapter 2

27

Fentem and Gopinath [2.13] proposed an early voltage contrast retarding field

analyzer using hemispherical grids for voltage contrast applications. Subsequent

designs of retarding field analyzers using planar grids were reported by Plows

[2.14], Flemming and Ward [2.12], and Gopinath and Sanger [2.15].

Several variations of the retarding field analyzer design as an SEM attachment have

been made in the context of electron beam testing of Integrated Circuits [2.16-2.18].

Retarding Field analyzer designs were also developed for magnetic immersion

objective lenses, such as those shown in Figs. 2.9c–e, where the secondaries travel

back through the objective lens bore. These “through–the–lens” arrangements were

reported by Menzel and Buchanan [2.19], Garth [2.20], Frosien and Plies [2.21]

and Dinnis [2.22], decreasing the working distance significantly to about 2–5 mm.

It is important to note that these types of spectrometers were mainly designed to

monitor the shifts in the SE spectrum, primarily for the application of probing tracks

in Integrated Circuits.

2.5 Signal–to–Noise considerations

There are several processes that contribute to the noise of any voltage measurement

carried out inside the SEM. These are variations in the primary beam current, noise

generated when electrons scatter inside the specimen and electron analyzer, and

noise of the detection system. A detailed analysis of this can be found in a book by

Reimer [2.23] and in a book chapter by Dubbeldam [2.24].

The generation of electrons in the electron gun is a random process following a

Poisson distribution that arises from statistical fluctuations in the number of emitted

Chapter 2

28

electrons, and is generally referred to as shot noise. The signal-to-noise ratio of the

primary beam electrons (𝑆

𝑁)

𝑃𝐸 is given by [2.23]

(𝑆

𝑁)

𝑃𝐸= √(

𝐼𝑃𝐸

2𝑒𝑓)

where IPE is the primary beam current, e is the electron charge and f is the

bandwidth of the detector system.

A primary beam electron can either be absorbed or be elastically scattered inside

the specimen and therefore backscattered electron (BSE) generation statistically

has a binomial distribution. The overall effect of the Poisson distribution of

electrons in the primary beam and the binomial distribution of the BSEs is a Poisson

distribution and the signal-to-noise of this process (𝑆

𝑁)

𝐵𝑆𝐸 is given as [2.23]

(𝑆

𝑁)

𝐵𝑆𝐸= √(

𝐼𝑃𝐸

2𝑒𝑓)

where is the backscattering coefficient, a parameter dependent on nature of the

specimen.

In contrast to the statistics that govern the generation of primary beam electrons

and BSEs, the statistics of Secondary electrons (SE) that emanate from the

specimen is neither a Binomial distribution nor a Poisson distribution because a

single primary electron (or a BSE generated by a PE) can generate zero, one or

many SEs. The signal-to-noise on account of the SE generation process is given as

[2.23]

Chapter 2

29

(𝑆

𝑁)

𝑆𝐸= √(

𝐼𝑃𝐸

2𝑒𝑓(1 + 𝑏))

where the variable b is a noise factor which takes into account the fluctuations of

primary electrons and their probability of generating SEs inside the specimen, b is

dependent on the SE yield factor .

The detector noise is relatively small compared to the shot noise of the primary

beam and the SE emission noise, under standard operating conditions [2.24, 2.25].

In the context of retarding field analyzers used for voltage contrast applications, the

shift in the energy spectrum is dominated by shot noise. Gopinath reported that the

minimum resolvable specimen voltage change was mainly limited by shot noise of

the primary beam [2.26]. He derived a formula to characterize voltage resolution of

retarding field analyzers, where the voltage resolution VS is given by

𝑉𝑆 = 𝐾2 (𝑓

𝐼𝐷)

where ID is the detector current, ∆f is the bandwidth of measurement system and

K is a spectrometer constant. This formula established an experimentally verified

figure of merit for retarding field analyzers, and was widely used for quantitative

voltage contrast applications.

The most important demerit of the retarding field analyzer is its relatively low

output signal–to–noise ratio. As the analyzer works in a high pass filter mode, only

a small number of electrons that reach the detector are sensitive to variations of the

filter grid potential. Therefore a small change in the threshold potential causes the

signal to vary on large noise background, reducing the sensitivity of the voltage

Chapter 2

30

change measurement. The contribution of the BSEs and SE3s generated from the

grids add to the output noise.

Detailed signal–to–noise analysis was first carried out by Dubbledam and Kruit

[2.27], comparing the predicted voltage resolution, ΔVS, analyzers that capture the

integrated form of the Chung–Everhart SE energy spectrum (retarding field

analyzer) and energy analyzers that acquire the SE energy spectrum directly (non–

integrated form). The results are summarized by Fig. 2.13, where the Voltage

Resolution Constant χ, links the voltage resolution to the number of electrons that

leave the specimen, N, by χ = (ΔVS)2N. The cut–off energy denotes the value of the

energy barrier in the retarding field spectrometer, e(VR– VS). The voltage resolution

constant χ is therefore proportional to the number of electrons required to obtain a

given voltage resolution, and its value for retarding field spectrometers is compared

to multi–channel spectrometers, which in this context, denotes spectrometers that

capture the SE spectrum directly, without integrating it. Fig. 2.13 indicates that for

small potential barriers (for points close to the top of the S–curve), the number of

electrons that retarding field analyzers need to attain a given voltage resolution is

one to two orders of magnitude higher than that required by analyzers that are able

to capture the SE energy spectrum directly. As the potential barrier strength grows,

where only higher energy secondaries make up the output signal, the difference in

the signal–to–noise characteristics of both analyzer types becomes smaller. These

results show that from a signal–to–noise point of view, there is an optimum point

mode of operation for retarding field analyzers, typically where the internal

potential barrier lies between 1 to 2 volts. They also indicate that operating close to

Chapter 2

31

the top of the S–curve (low potential barrier) should be avoided. These results

predicted analytically by Dubbledam and Kruit [2.27], were later confirmed

numerically by Khursheed using Monte–Carlo simulations [2.9].

Fig. 2.13 – Comparison of the signal–to–noise characteristics of retarding field

analyzers with multi–channel energy analyzers as a function of cut–off energy in

the SE Chung–Everhart spectrum [2.27].

Following on from the development of quantitative voltage contrast for probing of

IC circuits, SE energy analyzers have been proposed for quantification of

semiconductor dopant mapping of p–n junctions. Kazemian et al. recently reported

on using energy filtered SE signals inside the SEM, where shifts in SE spectra are

measured and used to quantify dopant concentration across a p–n junction [2.28,

2.29]. Fig. 2.14 shows the general layout of the “through–the–lens” detector used

for these experiments. Kazemian et al. use a field emission magnetic immersion

Chapter 2

32

objective lens SEM where an electrostatic deflector and off–axis detector are

inserted into the upper pole–piece of the lens.

The specimen is placed below the upper pole piece at the peak position of the axial

magnetic field (or just below it) as shown in Fig. 2.14. An extraction field is applied

to extract the secondaries. Due to the presence of a magnetic field, the secondaries

spiral up, past the lens–bore, and depending on the extraction field strength,

experience some degree of collimation. These electrons are then deflected on to a

detector placed on one side by electrostatic deflector plates. Although the deflection

action is a relatively broad one in terms of the secondary electron energy range that

is detected, there is however, a filtering effect on the higher energy electrons. The

deflector voltage is swept over a certain range and shifts in a signal related to the

SE spectra are obtained.

Fig. 2.14 – Schematic of magnetic immersion lens SE analyzer layout of Kazemian

et al. [2.28, 2.29] used for quantitative dopant mapping [2.1].

Chapter 2

33

The shape of the S–curves as reported by Kazemian et al. are irregular and deviate

from the shape of regular S–curves. This is because, in addition to it being a

retarding field analyzer, the setup also filters higher energy scattered electrons

which travel up through the lens bore. Monitoring of the shifts in the SE spectrum

was therefore limited to the top linear region of the spectra. For the reasons

indicated by Fig. 2.14, this led to poor signal–to–noise ratios. These reasons were

however, not mentioned by Kazemian et al. [2.28, 2.29]. The precision to which

they measured the p–n junction voltage was 0.72 ± 0.15 V, a signal–to–noise ratio

of 4.8 [2.29]. A later attempt measured the surface potential to be 0.81 ± 0.1 V

[2.28].

2.6 Deflection/multi–channel analyzers

Deflection analyzers, in contrast to retarding field analyzers, are band–pass

analyzers and at any given time, they only detect a very small part of the SE energy

range (in the meV range), a narrow pass range. They function by ramping an

electrode voltage inside the analyzer, which has the effect of changing the pass

range, so that the whole SE energy spectrum can be detected as a time varying

signal. In this case, the output signal is not an integrated form of the SE energy

spectrum, but as long as the pass range has a relatively small energy width, the

signal will directly represent the shape of the SE spectrum. An example of a

deflection band–pass analyzer developed for quantitative voltage contrast

measurements on IC circuits was given by Hannah [2.8], and is shown in Fig. 2.15a.

After secondary electrons are extracted up from the specimen, they are deflected

by the lower and upper deflection plates, which travel through an opening, defined

Chapter 2

34

by collimator plates, and are detected by the SEM scintillator. The collimator plates

can be adjusted to pass a small secondary electron energy range, and the deflection

plates are ramped in time. An example of the experimental output signals obtained

by Hannah are shown in Fig. 2.15b, illustrating how they shift as a function of

specimen voltage.

Fig. 2.15 – The 63° CDA Hannah voltage contrast spectrometer [2.8] (a)

Spectrometer layout (b) Experimentally acquired SE spectra for different specimen

voltages.

b

a

Chapter 2

35

Since bandpass analyzers capture the SE energy spectrum directly, they will, for

reasons already explained (Fig. 2.13), have better signal–to–noise ratio

characteristics than retarding field analyzers. Also, bandpass analyzers can track

changes in the shape in the SE energy spectrum instead of only detecting changes

in the overall number of collected electrons, as with the case of retarding field

analyzers. Furthermore, band–pass analyzers have a distinct advantage over

retarding field secondary electron analyzers in situations where the point to be

measured takes high negative potential values; their signals continue to shift right,

unlike the retarding analyzer whose signals remain approximately constant beyond

a value (top of the S–curve).

SE energy analyzer design for voltage contrast applications led to several multi–

channel SE analyzers, where the entire SE spectrum is acquired in parallel by an

array of energy channels, each capturing a different portion of the energy spectrum.

As long as the energy–width of each channel is small, like band–pass analyzers,

they capture the SE energy spectrum directly, not in its integrated form as in the

case of retarding field analyzers. They do not need any analyzer voltage electrode

to be ramped in time, and are therefore have much faster data–acquisition times

than both retarding field analyzers and band–pass analyzers. Multi–channel SE

energy analyzers were reported by Dubbledam and Kruit [2.30], Khursheed and

Dinnis [2.9], Khursheed [2.31], Khursheed and Karuppiah [2.32] and Kienle and

Plies [2.33] and discussed in detail in a book by Khursheed [2.34].

2.7 Full range deflection/multi–channel analyzer designs

The energy analyzers described so far, were designed primarily to capture the

secondary electron energy range. However, there have been some bandpass/multi–

Chapter 2

36

channel energy analyzer proposals designed to capture the complete energy

spectrum of scattered electrons in the SEM. One such spectrometer is an

electrostatic toroidal deflection analyzer attachment reported by Rau and Robinson

[2.35] (depicted in Fig. 2.16) and was used to capture the BSE spectrum from the

specimen under test. This analyzer attachment is designed to be placed in between

the objective lens and the specimen, resulting in a large working distance.

Therefore, it is not suitable for capturing energy spectral information on the nano–

scale range. However, Rau et al. demonstrated that this analyzer can be used both

as an analytical and an imaging tool inside the analyzer; as an imaging tool, the

analyzer was able to provide tomography information of subsurface structures and

as an analytical tool it was used to produce BSE spectra from different materials.

Fig. 2.16 – Schematic layout of the electrostatic toroidal deflection analyzer

reported by Rau and Robinson [2.35].

Recently, two new full range deflection analyzer design attachments were reported

by Hoang and Khursheed, namely the second–order focusing toroidal electron

energy analyzer [2.36] and later, the radial mirror analyzer (RMA) [2.6]. In addition

Chapter 2

37

to capturing both the SE and BSE energy spectra, these electric band–pass analyzer

attachments are designed to have high energy resolution optics, comparable to or

better than energy analyzers that are normally used for Auger Electron

Spectroscopy [2.37, 2.38]. Both analyzers are rotationally symmetric about the

primary beam axis and function concurrently with the SEM’s normal imaging mode

of operation. They are designed to minimize the working distance (distance from

specimen to lower pole–piece of the objective lens) and maximize transport

efficiency of scattered electrons to the analyzer detector. In the category of general

purpose add–on energy analyzer attachments for the SEM, they are the most

versatile designs reported so far, and they form an important starting point for the

work to be carried out here.

Fig. 2.17 shows the layout of the second–order toroidal spectrometer prototype

reported by Khursheed and Hoang [2.39]. This analyzer is predicted to have an

energy resolution that is comparable to the well–known Cylindrical Mirror analyzer

for the same acceptance angle [2.37]. The prototype was designed as an attachment

that fits on to the specimen stage. Although capable of full 2π collection, the

spectrometer was manufactured to collect 90˚ in the azimuthal direction, in order

to enable simultaneous viewing of the specimen by the conventional SE E–T

detector. The electrons which pass through the spectrometer are detected by a small

photo–multiplier tube (PMT) detector located beneath the specimen.

Experimental results obtained from the second–order focusing toroidal analyzer

have been shown to have excellent signal–to–noise characteristics, thereby

demonstrating that the analyzer inherently offers very high signal–to–noise ratios,

Chapter 2

38

typically allowing spectral shift as small as 12 mV or lower to be monitored.

Furthermore, when the specimen is biased at higher negative voltages, the signal–

to–noise of the output improves, allowing spectral changes as low as 4 mV to be

recorded. However, these results were obtained under idealized specimen

conditions; more work is required to investigate whether these high signal–to–noise

characteristics can be made for real applications such as quantitative dopant

concentration mapping.

Fig. 2.17 – Layout of a second–order focusing toroidal analyzer prototype

attachment [2.11].

Experimental results obtained from the second–order focusing toroidal analyzer

have been shown to have excellent signal–to–noise characteristics, thereby

demonstrating that the analyzer inherently offers very high signal–to–noise ratios,

typically allowing spectral shift as small as 12 mV or lower to be monitored.

Furthermore, when the specimen is biased at higher negative voltages, the signal–

Chapter 2

39

to–noise of the output improves, allowing spectral changes as low as 4 mV to be

recorded. However, these results were obtained under idealized specimen

conditions; more work is required to investigate whether these high signal–to–noise

characteristics can be made for real applications such as quantitative dopant

concentration mapping.

The RMA reported by Hoang et al. [2.6], is predicted to have a relative energy

resolution of better than 0.025% for a polar angular spread of ±6°. This is around

an order of magnitude better than the Cylindrical Mirror analyzer for the same

acceptance angle [2.37] and comparable to the Hemispherical Deflection Analyzer

(HDA) [2.38]. The layout of the RMA, designed to fit as attachment inside scanning

electron/ion microscopes is presented later in this thesis (Refer Fig. 5.1).

The RMA simulation predictions, although promising, need to be tested

experimentally. Both the second–order focusing toroidal analyzer and the RMA

provide good starting points for further developing energy analyzer attachments for

the SEM.

2.8 Objectives of the thesis

The work carried out in this thesis aimed to explore new possibilities of using the

electron energy analyzer as an analytical tool inside the SEM. Firstly, the behavior

of the second–order focusing toroidal analyzer prototype of Hoang et al. for more

realistic conditions, like presence of surface fields and fringe fields above the

specimen was investigated. Experimental results were obtained which demonstrate

that the analyzer can be used to obtain high signal–to–noise signals even in the

presence of such fields, and how it can be applied for voltage and dopant

concentration measurements of semiconductors. Secondly, the toroidal energy

Chapter 2

40

analyzer was used on a variety of different specimens, looking for new contrast

mechanisms. This work led to the discovery of a new quantitative measurement

method for probing the buried charge present at interfaces of multifunctional

oxides. Thirdly, a proof–of–concept prototype of the RMA [2.6] was built and

experimentally tested to obtain results that establish the working principle of the

analyzer. Fourthly, numerical simulation techniques were used to design a new

promising full range parallel radial mirror analyzer (PRMA) design, one that is

capable of directly quantitatively mapping SE energy spectral information on to the

SEM’s conventional image.

Chapter 2

41

References

2.1. A. Khursheed, Scanning Electron Microscope Optics and Spectrometers:

World Scientific, 2011.

2.2. D. Drouin, A. R. Couture, D. Joly, X. Tastet, V. Aimez, and R. Gauvin,

"CASINO V2. 42—A Fast and Easy‐to‐use Modeling Tool for Scanning

Electron Microscopy and Microanalysis Users," Scanning, vol. 29, pp. 92-

101, 2007.

2.3. K. Kanaya and S. Okayama, "Penetration and energy-loss theory of

electrons in solid targets," Journal of Physics D: Applied Physics, vol. 5, p.

43, 1972.

2.4. T. Everhart and R. Thornley, "Wide-band detector for micro-microampere

low-energy electron currents," Journal of Scientific Instruments, vol. 37, p.

246, 1960.

2.5. A. Khursheed, H. Q. Hoang, and A. Srinivasan, "A wide-range Parallel

Radial Mirror Analyzer for scanning electron/ion microscopes," Journal of

Electron Spectroscopy and Related Phenomena, vol. 184, pp. 525-532,

2012.

2.6. H. Q. Hoang and A. Khursheed, "A radial mirror analyzer for scanning

electron/ion microscopes," Nuclear Instruments and Methods in Physics

Research Section A: Accelerators, Spectrometers, Detectors and Associated

Equipment, vol. 635, pp. 64-68, 2011.

Chapter 2

42

2.7. M. S. Chung and T. E. Everhart, "Simple calculation of energy distribution

of low‐energy secondary electrons emitted from metals under electron

bombardment," Journal of Applied Physics, vol. 45, pp. 707-709, 1974.

2.8. J. M. Hannah, "SEM applications to Integrated Circuit Testing," PhD,

University of Edinburgh, Scotland, Scotland, 1974.

2.9. A. Khursheed and A. Dinnis, "A time-of-flight voltage contrast detector for

measurements on VLSI circuits," Measurement Science and Technology,

vol. 1, p. 581, 1990.

2.10. A. Khursheed, "Recent developments in scanning electron microscope

design," in Advances in Imaging and Electron Physics. vol. Volume 115,

W. H. Peter, Ed., ed: Elsevier, 2001, pp. 197-285.

2.11. H. Hoang, "Energy spectrometers for the SEM," PhD Thesis, Electrical and

Computer Engineering, National Univeristy of Singapore, 2010.

2.12. J. Fleming and E. Ward, "A technique for accurate measurement and display

of applied potential distributions using the SEM," Scanning Electron

Microscopy, pp. 465-470, 1970.

2.13. P. Fentem and A. Gopinath, "Voltage contrast linearization with a

hemispherical retarding analyser," Journal of Physics E: Scientific

Instruments, vol. 7, p. 930, 1974.

2.14. G. Plows, "Stroboscopic scanning electron microscopy and the observation

of microcircuit surface voltages," University of Cambridge, 1969.

Chapter 2

43

2.15. A. Gopinath and C. Sanger, "A technique for the linearization of voltage

contrast in the scanning electron microscope," Journal of Physics E:

Scientific Instruments, vol. 4, p. 334, 1971.

2.16. Y. Goto, A. Ito, Y. Furukawa, and T. Inagaki, "Hemispherical retarding type

energy analyzer for IC testing by electron beam," Journal of Vacuum

Science and Technology, vol. 19, pp. 1030-1032, 1981.

2.17. L. Balk, H. Feuerbaum, E. Kubalek, and E. Menzel, "Quantitative voltage

contrast at high frequencies in the SEM," Scanning Electron Microscopy.

IIT Research Institute, Chicago. 1976, 615-624, 1976.

2.18. H. Feuerbaum, "VLSI testing using the electron probe," Scanning Electron

Microscopy, vol. 1, pp. 285-296, 1979.

2.19. E. Menzel and R. Buchanan, "In-the-lens secondary electron analyser for

IC internal voltage measurements with electron beams," Electronics letters,

vol. 20, pp. 408-409, 1984.

2.20. S. Garth, J. Sackett, and D. Spicer, "An in-the-lens spectrometer for high

performance E-beam testing," Microelectronic Engineering, vol. 7, pp. 155-

161, 1987.

2.21. J. Frosien and E. Plies, "High performance electron optical column for

testing ICs with submicrometer design rules," Microelectronic Engineering,

vol. 7, pp. 163-172, 1987.

2.22. A. Dinnis, "Detectors for quantitative voltage contrast on submicron

devices," Microelectronic Engineering, vol. 7, pp. 139-146, 1987.

Chapter 2

44

2.23. R. Ludwing, "Scanning electron microscopy: physics of image formation

and microanalysis," ISBN 978-3-642-08372-31998.

2.24. L. Dubbeldam, "Electron spectrometers and voltage measurements," in

Electron Beam Testing Technology, ed: Springer, 1993, pp. 211-239.

2.25. K. Sim, J. Thong, and J. Phang, "Effect of shot noise and secondary

emission noise in scanning electron microscope images," Scanning, vol. 26,

pp. 36-40, 2004.

2.26. A. Gopinath, "Estimate of minimum measurable voltage in the SEM,"

Journal of Physics E: Scientific Instruments, vol. 10, p. 911, 1977.

2.27. L. Dubbeldam and P. Kruit, "Signal-to-noise ratio improvement in electron-

beam testing by using a dispersive analyzer," Scanning Microscopy, vol. 1,

pp. 1647-1650, 1987.

2.28. P. Kazemian, S. A. M. Mentink, C. Rodenburg, and C. J. Humphreys,

"Quantitative secondary electron energy filtering in a scanning electron

microscope and its applications," Ultramicroscopy, vol. 107, pp. 140-150,

2// 2007.

2.29. P. Kazemian, S. Mentink, C. Rodenburg, and C. Humphreys, "High

resolution quantitative two-dimensional dopant mapping using energy-

filtered secondary electron imaging," Journal of Applied Physics, vol. 100,

p. 054901, 2006.

2.30. L. Dubbeldam and P. Kruit, "First experimental results of an e-beam tester

with dispersive secondary electron energy analyzer," Microelectronic

Engineering, vol. 7, pp. 231-234, 1987.

Chapter 2

45

2.31. A. Khursheed, "Multi-channel vs. conventional retarding field

spectrometers for voltage contrast," Microelectronic Engineering, vol. 16,

pp. 43-50, 1992.

2.32. A. Khursheed and N. Karuppiah, "An add-on secondary electron energy

spectrometer for scanning electron microscopes," Review of Scientific

Instruments, vol. 72, pp. 1708-1714, 2001.

2.33. M. Kienle and E. Plies, "An off-axis multi-channel analyzer for secondary

electrons," Nuclear Instruments and Methods in Physics Research Section

A: Accelerators, Spectrometers, Detectors and Associated Equipment, vol.

519, pp. 325-330, 2004.

2.34. A. Khursheed, "Secondary Electron Spectrometers," in Scanning Electron

Microscope Optics and Spectrometers, ed, 2011, pp. 223-261.

2.35. E. Rau and V. Robinson, "An annular toroidal backscattered electron energy

analyser for use in scanning electron microscopy," Scanning, vol. 18, pp.

556-561, 1996.

2.36. A. Khursheed and H. Q. Hoang, "A second-order focusing electrostatic

toroidal electron spectrometer with 2π radian collection," Ultramicroscopy,

vol. 109, pp. 104-110, 12// 2008.

2.37. H. Z. Sar‐El, "Criterion for Comparing Analyzers," Review of Scientific

Instruments, vol. 41, pp. 561-564, 1970.

2.38. E. Benis and T. Zouros, "The hemispherical deflector analyser revisited: II.

Electron-optical properties," Journal of Electron Spectroscopy and Related

Phenomena, vol. 163, pp. 28-39, 2008.

Chapter 2

46

2.39. H. Hoang, M. Osterberg, and A. Khursheed, "A high signal-to-noise ratio

toroidal electron spectrometer for the SEM," Ultramicroscopy, vol. 111, pp.

1093-1100, 2011.

Chapter 3

47

Chapter 3 – Voltage and dopant concentration measurements of

semiconductors using a band–pass toroidal energy analyzer inside

a SEM

3.1 Introduction

In the previous chapter, a brief introduction to the second–order focusing toroidal

energy analyzer attachment for the SEM reported by Khursheed and Hoang was

presented [3.1]. This toroidal analyzer design is predicted to have an energy

resolution comparable to the well–known Cylindrical Mirror analyzer for the same

acceptance angle [3.2]. Fig. 3.1a below shows the original layout of the second–

order focusing toroidal energy analyzer prototype attachment.

Fig. 3.1 – Original layout of the second–order focusing toroidal analyzer prototype

attachment: (a) Experimental layout (b) Original specimen holder layout [3.3].

a b

Hemispherical caps

Specimen

Specimen Holder

Chapter 3

48

Fig. 3.2a shows the experimentally acquired SE spectrum from the toroidal analyzer

prototype reported by Hoang et al., while Fig. 3.2b shows a selected part of the

same spectrum [3.3]. Both the specimen and the inner cap were kept at ground

potential. It can be clearly seen that the noise is very small and the analyzer

inherently offers very high signal–to–noise ratio, allowing spectral shifts as small

as 12 mV or lower to be monitored.

Fig. 3.2 – Experimental SE spectrum reported by Hung et al. [3.3] (a) full range

and (b) selected range in which curve 2 (dotted line) is obtained by shifting curve

1 by 12 mV in order to demonstrate the noise limit.

Hoang et al. further demonstrated that when the specimen and the inner cap are

together biased at higher negative voltages with reference to the outer cap (at

ground potential), the SE signal no longer represents the SE energy spectrum but

becomes more symmetrical and has a more distinct sharp peak. In addition the

signal becomes higher and shifts to the right as the specimen bias is increased. The

b

a

Chapter 3

49

SE energy spectrum signal is transformed into a much more convenient form for

open–loop specimen voltage measurements than the original SE spectrum. The

effect of biasing the specimen and the inner cap at higher negative voltages with

reference to the outer cap (at ground potential) is shown in Fig. 3.3.

Fig. 3.3 – Experimental secondary electron output signals at different specimen

biasing voltages reported by Hoang et al. [3.3].

The improvement of the signal–to–noise ratio was also reported at negative

specimen/inner cap voltages. As seen in Fig. 3.4, when the bias voltage on the

specimen/inner cap changes from –10 to –10.1 V, there is a distinct shift in the peak

value. In this case, the spectrometer deflector voltage is restricted to a small range

(1 volt) around the peak signal value. The presence of shot noise on these signals

is relatively small, less than 4 mV, a few times better than the case of 0 V bias.

Chapter 3

50

a

b

These results demonstrate that the analyzer inherently has a high signal–to–noise

capability in detecting specimen voltage changes, well into the sub–mV region.

Fig. 3.4 – Experimental secondary electron signals showing improved signal–to–

noise when specimen/inner cap is biased at −10 and −10.1 V shown around the

peak value: (a) Deflection voltage range from 7 to 8 V and (b) deflection voltage

range from 7.1 to 7.16 V [3.3].

The signal–to–noise results reported by Hoang et al. and shown in Fig. 3.4 are

promising; they were obtained from large metal samples in a field free region where

the voltage of the specimen and the first analyzer electrode above it were fixed to

be at the same voltage. However, in practice, for a wider range of specimens, there

will be other effects that act to change the SE analyzer signals shown in Fig. 3.4.

The first effect arises from the fact that the applied voltage to the specimen may

need to be different to the one applied to the inner cap, and this will create fringe

Chapter 3

51

electric fields between the specimen and inner cap. This effect will be referred to

here as specimen fringe fields. Also, there are always local variations of specimen

surface potential, which in turn, create microfields above the specimen surface.

Local surface fields can arise due to a variety of reasons, such as variations in

semiconductor doping levels, a difference in voltage between neighboring

microstructures (IC tracks), beam induced contamination and specimen charging.

The experimental work presented in this chapter first starts by investigating how

the second–order toroidal energy analyzer signals change in the presence of

specimen fringe fields and local surface microfields.

3.2 The problem of specimen fringe fields and local surface microfields

A simple illustration of how specimen fringe fields can change the trajectory path

of an electron emitted from the specimen is shown by the simulation results shown

in Fig. 3.5. These simulations were carried out by use of the Lorentz 2EM software

[3.4]. In this simple example, 0.5 eV trajectories leave the specimen with a polar

emission angle of 45 degrees, and the specimen fringe fields are created by a

negative one voltage difference between the specimen and inner cap (– 11 V and –

10 V respectively). The form of the specimen fringe fields is indicated by the

simulated equipotential lines in Fig. 3.5, and their collective effect is to significantly

deflect the electron away from the straight–line path it would have taken if no fringe

fields were present. This effect changes the analyzer’s entrance optics. Electrons

no longer appear to come from a single point located on the specimen; their

apparent starting position is now energy dependent, and the output signal

characteristics are therefore considerably changed. Just how the analyzer output

Chapter 3

52

signals change in the presence of these kinds of accelerating fringe fields is

experimentally investigated in the next section.

Fig. 3.5 – Direct ray tracing of a 0.5 eV electron (polar launch angle 45 degrees)

with fringe fields above the specimen; the specimen is biased more negative with

reference to the inner cap. The dotted path shows the electron trajectory without

fringe fields (Specimen = – 10 V).

How surface microfields change trajectory paths of electrons that leave the

specimen can also be simply illustrated by simulation. Studies on effects of surface

microfields on voltage contrast have been undertaken by researchers over many

years [3.5 – 3.7]. Within this context, surface fields have been classified into Type

I and Type II depending on the nature of the potential variation that occurs around

the point being probed inside the SEM. Type I local field effects are created when

Specimen = – 11 V

Inner cap = – 10 V

Outer cap = – 0 V Electron trajectory – Initial

energy 0.5 eV, emission angle

45

Electron trajectory

(dotted) in absence of

fringe fields.

Specimen

fringe fields

5 mm

Chapter 3

53

the point being probed is more positive with respect to the neighborhood specimen

region, while Type II local surface fields effects are created when the point being

probed is more negative with respect to its surroundings. Fig. 3.6 shows simulated

electron trajectories through the potential distribution above a sample created by

Type I local fields. As a function of height, the potential above the central track

drops below 0 V before rising again. This drop creates a potential barrier for the

emitted electrons, preventing all electrons having initial energies below the barrier

to reach the analyzer entrance. Slightly higher energy electrons which marginally

surpass the potential barrier, escape and are deflected from their original path. In

Fig. 3.6, the simulated electron ray path trapped by the potential barrier has an

emission energy of 0.4 eV, while the ray which manages to escape has an emission

energy of 0.5 eV.

Fig. 3.7 shows a simple simulation example of Type II surface microfields caused

by neighboring IC tracks. It simulates how a 0.5 eV low energy secondary electron

emitted from the central track is deflected by a positive one volt change in the

neighboring track (located at a distance 50 µm away). From an analyzer optics point

of view, this surface field effect changes the apparent position of the source point,

making it energy dependent, and it therefore changes the shape of the analyzer

output signal.

Chapter 3

54

Fig. 3.6 – Simulated potential distribution and electron trajectories of 0.5 eV and

0.4 eV electrons (polar launch angle 45) in the presence of Type I surface

microfields. The dotted line shows the simulated trajectory of the electron without

surface fields.

Fig. 3.7 – Simulated potential distribution and electron trajectory of a 0.5 eV

electron (polar launch angle 45) in the presence of Type II surface microfields.

The dotted line shows the simulated trajectory of the electron without surface fields.

Electron trajectory in

absence of surface fields Trajectory of a

0.5 eV electron

Trajectory of a

0.4 eV electron

0 V –1 V –1 V

Type I surface field

equipotentials

50 µm

100 µm

0 V 0 V +1 V

Electron trajectory in absence

of surface fields

Type II surface field

equipotentials

Deflected 0.5 eV electron

trajectory

50 µm

100 µm

Chapter 3

55

Historically, surface fields caused large changes to occur in the output signals from

the secondary electron energy analyzers used for Electron Beam Testing of ICs.,

and in practice, greatly limited the accuracy to which quantitative voltage contrast

measurements could be made [3.8, 3.9]. In the present context of performing

material analysis using the second–order focusing toroidal analyzer in the SEM,

large changes in the output signal created by local surface fields and fringe fields

will also occur, and just how much it compromises on the performance of the

analyzer needs to be investigated in the next section.

3.3 Experimental Results

In the previous section, preliminary results obtained from the initial prototype of

the second–order focusing toroidal energy analyzer were presented for large bulk

metal specimens. In this section, experimental results are presented for

semiconductor samples in the presence of fringe/surface fields.

3.3.1 The experimental setup

Fig. 3.8a shows the layout of the present second–order focusing toroidal analyzer

SEM attachment. This is the same setup reported by Hoang and Khursheed [3.3]

except that the specimen holder is now modified from the hemispherical

arrangement reported earlier, to a concentric conical structure in which the

specimen and inner/outer caps can be independently biased. The redesign of the

sample holder also allows for bigger sample sizes to be examined. A schematic of

the modified specimen holder is shown in Fig. 3.8b. It must, however, be clarified

here that the redesign of the specimen holder into a concentric conical structure

does not change the fundamental electron optics of the analyzer. The specimen

Chapter 3

56

holder consists of the specimen surrounded by two concentric conical caps. The

voltage bias to the specimen, the inner conical cap and the outer conical cap are

denoted as VS, VC1, and VC2 respectively.

Fig. 3.8 – The second–order toroidal energy analyzer SEM attachment: (a)

Experimental layout in the SEM chamber (b) Schematic of the modified specimen

holder indicating the bias voltages applied to the various components of the holder.

b

VC2

VC1

Vs

52.5

mm

13 mm

a

b

Chapter 3

57

For all the results discussed here, VC2 was set to 0 V. The scattered electron energy

distribution is obtained by ramping the analyzer deflection electrode (VDEF) and

monitoring the photomultiplier (PMT) output. The sample and conical caps are

biased to negative voltages in order to further increase the SE signal sensitivity to

specimen voltage changes [3.3].

All experiments in this chapter were carried out inside a Philips ESEM XL30 FEG

SEM where a 4 kV, 75 pA primary beam was focussed on to a spot on the specimen.

A personal computer (PC) was used to control VDEF and the PMT output was

obtained through a National Instruments Data Acquisition (NI–DAQ) board [3.10].

The deflection voltage was ramped in steps of 200 mV and each point had a primary

beam dwell time of approximately 150 ms. The scintillator voltage of the PMT,

VSC, was biased to 5 kV. The SE signal was collected from regions which were

exposed to the primary beam for the first time in order to minimize the effects of

contamination.

3.3.2 Experimental analyzer SE signals on a doped silicon specimen in

presence of specimen fringe fields

Experimental analyzer SE signals from an n–type doped Silicon wafer (ND ~ 1018

cm–3) were obtained, where the specimen voltage (VS) was varied from – 10 V to –

13 V and inner cap voltage (VC1) was maintained at – 10 V; outer cap voltage (VC2)

was held at 0 V. Fig. 3.9a shows that as the sample becomes more negative with

respect to the inner cap voltage, the SE signal decreases in amplitude as well as

shifts towards the right. This happens because, as the specimen becomes more

negative, low energy secondaries are deflected upwards by accelerating fringe

Chapter 3

58

fields, causing some electrons to be pulled away from the analyzer entrance slit, as

illustrated in Fig. 3.5, and some (smaller angle) electrons, to be pulled into the

analyzer. However, the new electrons pulled into the analyzer do not compensate

for the electrons that are pulled away from it. This is because these electrons go

into it at steeper entrance angles than the previous ones (absence of fringe fields),

and they as a result, strike the analyzer deflector plates and do not contribute to the

SE signal output. The shift of the output signal to the right is caused by the fact that

the kinetic energies of all SEs increase with negative specimen voltage biasing.

These analyzer signals are very different to the case where VS = VC1 (field free

region above the specimen), as shown in Fig. 3.9b, where the SE signal shifts to the

right but grows significantly in height, similar to the results reported previously by

Hoang and Khursheed [3.3].

a

Chapter 3

59

Fig. 3.9 – Experimental SE signals obtained from an n–type semiconductor sample:

(a) Specimen biasing from – 10 to –13 volts with VC1 = –10 V, VC2 = 0 V. Inset

shows the biasing condition of the sample holder (b) Experimental SE signals at

different specimen biasing voltages where VS = VC1 (c) A plot of PMT signal

expectation value () for specimen potential change (ΔVs) from 0 to 3 V in presence

of specimen fringe fields.

VS = – 10 V

VC1 = VS

VC2 = 0 V

b

c

Chapter 3

60

For the case of the specimen being more positive than the first cap, VS = – 9 V, it is

important to note that apart from the expected shift to the left, the signal also falls

in height. This can be explained simply in terms of the creation of a retarding

electric field, where low energy electrons (<1 eV) are now returned back to the

specimen, since the specimen is now more positive than VC1 (by 1 volt).

To better quantify the specimen voltage change in presence of fringe fields above

the specimen (Fig. 3.9a), the output signal mean µ is plot against the change in

specimen voltage, ΔVS, given by the expectation value E(V):

𝜇 = 𝐸(𝑉) = ∑ 𝑃𝑗𝑉𝑗

𝑁

𝑗=1

where the index j runs from 1 to the number of points in the output signal, N; V

refers to the deflection voltage; Pj refers to the probability of each point in the

output signal, obtained from the output height normalized to the area under the

output curve. The expectation function is a convenient way of monitoring small

changes in the peak value, since the peak position shifts significantly as the

specimen voltage changes. Also the expectation value changes with variations in

the shape of the SE signal. Therefore two signals with the same peak amplitude

occurring at the same value of deflection voltage but with variations in their shapes

will yield different values of expectation value.

The relationship between and ΔVS found from the experimental results of Fig.

3.9a is plot in the graph shown in Fig. 3.9c. It shows that they vary in an

approximately linear way, demonstrating that it is possible to quantify surface

Chapter 3

61

specimen voltage changes in non–metallic specimens with the toroidal analyzer

attachment even in the presence of fringe fields above the sample, where the

specimen voltage and inner cap voltage differ. Despite there being a considerable

loss in parts of the SE analyzer signal, the overall shift due to specimen voltage

change can be reliably obtained by calculating the SE analyzer signal expectation

value. After suitable calibration, the SE analyzer signal can therefore be used to

quantify specimen voltage changes.

3.3.3 Experimental analyzer SE signals in presence of surface microfields

In the previous section, SE signals and their variations in the presence of fringe

fields above the sample were studied. However in most cases, the voltage variations

that occur on the sample are typically localized to the micrometer/nanometer scale,

in the form of surface microfields, as discussed earlier in this chapter. A thin piece

of copper enameled winding wire of diameter 200 microns was mounted on top of

a metal base, as shown in Fig. 3.10a. The outer enamel paint surrounding the wire

makes it possible to bias the wire and the metal base to a different voltage. The

enamel covering is carefully scraped off from the top of the wire using a surgical

blade in order to prevent the wire from charging when illuminated by the primary

electron beam. Experimental SE signals were obtained from the center of the wire

for various values of wire voltage, denoted as VS, while VC1 and VC2 are maintained

at –10 V and 0 V respectively.

Chapter 3

62

PM

T O

utp

ut

(a.u

)

Deflection Voltage (volts)

VS = – 10 V

– 11 V

– 12 V

– 13 V

– 14 V

VC1 = – 10 V

VC2 = 0 V

b

PE

VC1 = – 10 V

VC2 = 0 V

Enamelled

Copper wire

VS = VC1 – ΔVS

a

Metal

Specimen (VC1)

PE

Exposed copper

wire (φ 200 µm)

Enamel

insulation

Chapter 3

63

Fig. 3.10 – Experimental SE signals obtained from a copper wire in presence of

surface fields: (a) Specimen arrangement to generate microfields above the point

of probing (b) SE signals obtained from the specimen for different biasing of the

copper wire (c) A plot of PMT signal expectation value () for copper wire potential

change (ΔVs) from 0 to 4 V in presence of surface fields above the point of probing.

The experimental results shown in Fig. 3.10b indicate that as the wire becomes

more negative with respect to the metal base/inner cap voltage, changing from –10

to –14 V (while VC1 and the metal base remain at –10 V), the SE signal shifts to the

right due to an increase in the kinetic energy of the scattered electrons that pass

through the analyzer, however, the amplitude of the SE signal goes through a

maximum value; it first increases, after which (< –12 V), it decreases. The situation

seems to be a combination of the field–free region case, where the amplitude rises

as the specimen voltage becomes more negative, and the specimen fringe field case,

where the SE analyzer signal amplitude goes progressively down. These results

seem to suggest for VS > –12 V, the effect of Type II surface microfields is

c

ΔVs (Volts)

Ex

pec

tati

on

va

lue (

μ)

of

ou

tpu

t si

gn

al

(vo

lts)

Chapter 3

64

compensated by the acceleration fringe fields created between the specimen and

inner cap, however, for VS < –12 V, the specimen fringe fields dominate. Despite

the variations in analyzer signal amplitude, there is a consistent shift in the peak

position as the specimen voltage is biased more negatively. This is demonstrated

by Fig. 3.10, which plots the analyzer signal expectation value with change in

specimen potential, indicating that it increases monotonically. These experimental

results therefore show that the second–order focusing toroidal energy analyzer can

be used to quantify specimen voltage changes even in the presence of surface fields.

3.3.4 Experimental analyzer SE signals along a semiconductor sample with

a potential gradient

Figs. 3.9 and 3.10 show that the second–order focusing toroidal analyzer can

reliably track changes in specimen voltages at a single point on the specimen. The

following experiment sets out to detect voltage changes across a semiconductor

surface. An n–type doped Silicon sample (ND ~ 1018 cm–3) was mounted on top of

a button cell and the two ends of the specimen were biased in order to create a linear

potential gradient along its surface as shown in Fig. 3.11a. The two electrodes of

the button cell are connected to the two far ends of the silicon wafer using metal

wires. The distance between the two ends of the specimen is 6 mm, across which a

potential drop of 1.5 V is applied. The entire setup is biased at – 10 V, as a result

of which the two ends of the specimen are effectively at – 8.5 V and – 10 V

respectively. Experimental SE analyzer signals were obtained from the specimen

at consecutive points on a straight line along the x direction starting from the centre

of the specimen, and are shown in Fig. 3.11b. The distance between each point of

Chapter 3

65

measurement on the specimen was approximately 120 microns. Assuming that the

specimen voltage changes linearly across its surface, there is a voltage change of

30 mV between each measurement point.

Fig. 3.11b shows that as the potential along the surface of the sample becomes more

negative, there is a distinct shift in the SE analyzer signal; the amplitude increases

and shifts to the right. Again, the specimen voltage change ΔVS can be tracked by

calculating and plotting the output signal expectation value , which in this case

changes with distance x, as shown in Fig. 3.11c. The plot of against the change

in potential ΔVS (proportional to the distance moved along the x direction) is, as

expected, almost linear; hence a small change in the voltage along the surface of

the sample can be measured (via the electron beam) by calculating the expectation

of the SE analyzer signal.

a

Chapter 3

66

Fig. 3.11 – Experimental SE signals obtained by setting up a potential gradient

along a semiconductor sample: (a) Specimen arrangement using a button cell (b)

SE signals obtained from the specimen along the x direction (c) A plot of

expectation value µ of the SE signal against the change in potential ΔVS along

distance x.

b

c

Chapter 3

67

The close fit to the theoretical straight line in Fig. 3.11c confirms that the method

of monitoring the expectation value of the SE analyzer signal in order to measure

small voltage changes on the semiconductor specimen seems to be a good one. An

estimate of the voltage measurement accuracy can be obtained by calculating the

standard deviation between the dotted and the solid line in Fig. 3.11c, translating it

into an uncertainty in voltage measurement by using the /ΔVS gradient. For the

experimental conditions and results shown in Fig. 3.11c, the voltage accuracy is

calculated to be 5.1 mV, corresponding to an average signal–to–noise ratio of 7.3.

These experimental results therefore demonstrate that surface voltage variations on

a semiconductor specimen can be measured to millivolt accuracy by the second–

order focusing toroidal analyzer attachment.

3.3.5 Experimental SE analyzer dopant contrast signals from abrupt

semiconductor heterojunctions

Apart from voltage measurement on semiconductors, an important application of

energy analyzers for the SEM is to obtain quantitative dopant concentration

measurements. The following experiment sets out to do this using Zinc Oxide

(ZnO) on p–doped Si substrate. ZnO is a direct wide band gap (3.37 eV)

semiconductor [3.11] and has a wide variety of applications in molecular and nano–

scale electronics, especially for opto–electronics [3.12, 3.13]. For the purpose of

this study, sol–gel synthesized n–ZnO/Si (n–p) thin film heterojunctions were

fabricated using standard processes [3.14, 3.15]. Four differently doped p–type

silicon samples were taken, on which ZnO thin films were grown to form abrupt p–

n junctions. They were cleaved and then examined in the SEM, as shown in Fig.

Chapter 3

68

3.12a. In this way abrupt p–n junctions with different p–doped concentrations were

fabricated under controlled conditions, providing convenient test samples for

quantitative dopant concentration measurements. At thermal equilibrium, the built–

in potential of each p–n junction depends on the doping levels on the p and the n

side. However in this case, the n–ZnO doping level (carrier concentration 2.2 1018

cm–3) was approximately constant for all the samples, as all the ZnO films were

grown using an identical process and under near–identical conditions. Therefore

variations of the built–in potential between the p–n junction samples are dependent

only on the doping level difference between the p–type silicon substrates. The p–

doping levels for the samples were: A – 5.18 1014 cm–3, B – 1.53 1015 cm–3, C

– 2.08 1016 cm–3 and D – 3.83 1018 cm–3, for which the theoretical built–in

potential values were calculated using first principles to be 0.52 V, 0.56 V, 0.62 V

and 0.75 V respectively. Experimental analyzer SE signals were collected from the

p–side and the n–side of each heterojunction sample (for VS = VC1 = – 10 V, VC2 =

0 V), from points far away from the depletion region, and are shown in Fig. 3.12b.

The expectation value was calculated for each signal. The difference Δ between

the two values of (from the p and the n side) is plot as a function of the p–side

dopant concentration (NA) in Fig. 3.12c. The experimental standard deviation (σ) of

Δ was obtained by repeating these measurements; each signal shown in Fig. 3.12b

was acquired 10 times.

Chapter 3

69

a

b

Chapter 3

70

Fig. 3.12 – SE analyzer signal contrast from a n–ZnO / p–Si heterojunction: (a)

Schematic representation of the fabricated thin–film ZnO on Silicon substrate (b)

Experimental SE signals obtained from the p–side and the n–side of each

heterojunction sample for samples A, B, C and D (c) Plot of difference in

expectation value Δ of the SE analyzer signal obtained from the p and n sides of

the Si/ZnO heterojunction against the log of doping concentration of the p–type

silicon substrate. The solid bars at each point on the graph represent standard

deviation of Δ taken over 10 SE signals.

The shift in the SE energy spectrum which arises from p and n doped sides of p–n

junctions has been previously explained in terms of various mechanisms, which

include a band–bending potential at the surface [3.16] and patch fields occurring

due to the built–in potential across the junction [3.17]. Kazemian et al. [3.18, 3.19]

proposed an empirical model wherein the shift in the SE analyzer signal comes

from a linear combination of these two mechanisms.

c

Chapter 3

71

Therefore parameter Δ is expected to be closely related to the p–n junction built–

in potential. In Fig. 3.12b, the theoretical value of the built–in potential is plot

together with Δ, indicating that Δ maintains a small offset below the built–in

potential. Taking Kazemian et al.’s interpretation, this small difference may be

caused by surface band bending. In the present context, the results shown in Fig.

3.12c demonstrate how quantitative dopant concentration measurements of a p–n

junction sample can be made with the second–order focusing toroidal analyzer

attachment in the SEM. Using interpolation on the curve shown in Fig. 3.12c any

subsequent measurement of Δ on a similar p–n junction ZnO/Si thin film sample

will provide an accurate estimate of NA in its substrate. The accuracy to which this

can be achieved is determined primarily by the uncertainty in Δ caused by noise,

which in this case, is indicated by the length of the error bars in Fig. 3.12c. These

results are given explicitly in Table 3.1. They indicate that the experimental signal–

to–noise varies roughly from 31 to 63, for a shift in expectation value (Δ) ranging

from 0.43 to 0.65 volts, where the noise varies between 9 to 18 mV.

Table 3.1 – Dopant concentration measurement results for the Si/ZnO p–n

heterojunction for different p–doped samples.

Chapter 3

72

These results therefore demonstrate that the high signal–to–noise characteristics

predicted for the second–order focusing toroidal analyzer attachment for dopant

concentration measurements can be obtained in the presence of surface fields, on

more realistic samples than previously examined (bulk metal ones). The millivolt

accuracy of the present results are over one order of magnitude better than previous

p–n junction dopant concentration measurements obtained by a retarding field

analyzer [3.18, 3.19]. These results confirm what was already known in the subject

of quantitative voltage contrast that band–pass analyzers have inherently better

signal–to–noise characteristics than retarding field analyzers, they have a lower

background noise level and their signals are more sensitive to specimen voltage

changes [3.20, 3.21].

3.4 Conclusions

Voltage and dopant concentration measurements on Silicon samples by a second–

order focusing toroidal electron energy analyzer operating in a SEM as an add–on

attachment have been presented. These results were obtained in the presence of

electric fields above the sample, originating from the surface voltage on the sample

differing from the first analyzer electrode by several volts. They demonstrate that

it is possible to obtain high signal–to–noise measurements from the second–order

focusing toroidal analyzer even in the presence of such fields above the specimen.

The accuracy of voltage measurements on the surface of silicon test samples

typically lay between 9 to 18 mV, corresponding to signal–to–noise ratios of 31 to

63. These experimental results therefore establish that the analyzer can be applied

to measure semiconductor surface voltage variations and can be used for 2D dopant

Chapter 3

73

profiling of p–n junction based devices like solar cells by monitoring the shift in

the SE signal obtained from point–to–point on the cross section of such devices.

Chapter 3

74

References

3.1. Khursheed, A. and H.Q. Hoang, A second–order focusing electrostatic

toroidal electron spectrometer with 2π radian collection. Ultramicroscopy, 2008.

109(1): p. 104–110.

3.2. Sar‐El, H.Z., Criterion for Comparing Analyzers. Review of Scientific

Instruments, 1970. 41(4): p. 561–564.

3.3. Hoang, H., M. Osterberg, and A. Khursheed, A high signal–to–noise ratio

toroidal electron spectrometer for the SEM. Ultramicroscopy, 2011. 111(8): p.

1093–1100.

3.4. LORENTZ – EM. 2011, Integrated Engineering Software Inc., Canada.

3.5. Nakamae, K., H. Fujioka, and K. Ura, Local field effects on voltage contrast

in the scanning electron microscope. Journal of Physics D: Applied Physics, 1981.

14(11): p. 1939.

3.6. Wager, W.E. and E.D. Wolf, The effects of local electric fields and

specimen geometry on voltage contrast in the scanning electron microscope.

Journal of Vacuum Science & Technology B, 1986. 4(1): p. 209–212.

3.7. Clauberg, R., Microfields in stroboscopic voltage measurements via

electron emission. II. Effects on electron dynamics. Journal of Applied Physics,

1987. 62(10): p. 4017–4023.

3.8. Khursheed, A. and A. Dinnis, A time–of–flight voltage contrast detector for

measurements on VLSI circuits. Measurement Science and Technology, 1990.

1(7): p. 581.

Chapter 3

75

3.9. Khursheed, A. and A. Dinnis, A theoretical comparison of the data‐

acquisition time characteristics of the time of flight voltage contrast detector with

retarding field detectors. Journal of Vacuum Science & Technology B, 1990. 8(6):

p. 1841–1847.

3.10. National Instruments LabVIEWTM 2010. National Instruments.

3.11. Klingshirn, C., The Luminescence of ZnO under High One‐and Two‐

Quantum Excitation. Physica status solidi (b), 1975. 71(2): p. 547–556.

3.12. Gudiksen, M.S., et al., Growth of nanowire superlattice structures for

nanoscale photonics and electronics. Nature, 2002. 415(6872): p. 617–620.

3.13. Huang, M.H., et al., Room–temperature ultraviolet nanowire nanolasers.

Science, 2001. 292(5523): p. 1897–1899.

3.14. Paul, G. and S. Sen, Sol–gel preparation, characterization and studies on

electrical and thermoelectrical properties of gallium doped zinc oxide films.

Materials letters, 2002. 57(3): p. 742–746.

3.15. Sarkar, S., et al., Rectifying properties of sol–gel synthesized Al: ZnO/Si

(N–n) thin film heterojunctions. Physica E: Low–dimensional Systems and

Nanostructures, 2012. 46: p. 1–5.

3.16. Perovic, D., et al., Field–emission SEM imaging of compositional and

doping layer semiconductor superlattices. Ultramicroscopy, 1995. 58(1): p. 104–

113.

3.17. Sealy, C.P., M.R. Castell, and P.R. Wilshaw, Mechanism for secondary

electron dopant contrast in the SEM. Journal of Electron Microscopy, 2000. 49(2):

p. 311–321.

Chapter 3

76

3.18. Kazemian, P., et al., High resolution quantitative two–dimensional dopant

mapping using energy–filtered secondary electron imaging. Journal of Applied

Physics, 2006. 100(5): p. 054901.

3.19. Kazemian, P., et al., Quantitative secondary electron energy filtering in a

scanning electron microscope and its applications. Ultramicroscopy, 2007. 107(2–

3): p. 140–150.

3.20. Khursheed, A., Scanning Electron Microscope Optics and Spectrometers.

2011: World Scientific.

3.21. Khursheed, A., Multi–channel vs. conventional retarding field

spectrometers for voltage contrast. Microelectronic Engineering, 1992. 16(1): p.

43–50.

Chapter 4

77

Chapter 4 – New contrast mechanisms and material

characterization by energy filtered secondary electron signals

inside the SEM

4.1 Introduction

In the previous chapter, experimental results were presented to demonstrate that the

second–order focusing toroidal energy analyzer [4.1] can provide high signal–to–

noise and dopant concentration measurements on semiconductor specimens, even

though the SE signals are greatly changed by fringe fields and surface fields. A

natural continuation to this work is to look for new contrast mechanisms inside the

SEM using the second–order focusing toroidal analyzer and apply these contrast

mechanisms to develop novel material characterization techniques. Analytical

information about the specimen can be obtained using electron analyzers such as

the second–order focusing toroidal analyzer by monitoring changes in the SE

analyzer signal obtained from the specimen and this can be done together with

capturing nanometer–level topographical images of the specimen, with the SEM’s

conventional SE detector. The secondary electron (SE) spectrum inside a Scanning

Electron Microscope (SEM) has been used for a number of applications like dopant

mapping [4.2, 4.3], monitoring specimen charging [4.4] and Electron Beam Testing

(EBT) of Integrated Circuits [4.5]. In this chapter, SE analyzer signals are presented

that point towards a new application of detecting trapped charge at the interface of

multi–functional oxide layers. This chapter also presents results that illustrate how

SE signals obtained using the second–order focusing toroidal analyzer vary in the

Chapter 4

78

presence of magnetic fields above the specimen surface, and how SE analyzer

signals also change due to spontaneous oxidation of a metal surface to metal oxide.

4.2 Probing and analyzing buried interfaces of multifunctional oxides

using a secondary electron energy analyzer.

4.2.1 Introduction

Recently, the discovery of the formation of a two–dimensional electron gas (2DEG)

at the interface of complex oxides such as LaAlO3/SrTiO3 (LAO/STO) reported by

Ohtomo and Hwang [4.6], has formed the basis of many new device concepts [4.7].

The experimental results presented here highlight the possibility of using SE energy

analyzers inside the SEM as a high resolution contactless way to detect and analyze

hidden interfaces between multifunctional oxides such as the presence of 2DEG at

the interface of LAO and STO.

In the following experiments, a second–order focusing toroidal analyzer SEM

attachment, previously designed by Hoang and Khursheed [4.8] for voltage and

dopant concentration measurements is used to detect the 2DEG at the interface of

a LAO/STO sample with high SE analyzer signal contrast. Conditions for obtaining

significant SE analyzer signal contrast in the SEM between conducting and

insulating LAO/STO interface samples were also investigated and the primary

beam energy was found to be an important factor affecting SE signal contrast.

Monte Carlo simulations of the beam/sample interaction were performed to explain

why the SE contrast mechanism is sensitive to primary beam energy and how it can

be optimized.

Chapter 4

79

4.2.2 Materials and methods

Fig. 4.1 shows the mounting of a LAO/STO sample inside the specimen holder

arrangement of the second–order focusing toroidal analyzer SEM attachment (refer

Chapter 3, Fig. 3.8). In the present arrangement, the specimen is mounted on top of

a metal base and placed inside a concentric conical arrangement of the first and

second analyzer electrodes (holder). The specimen and the first analyzer electrode,

denoted by VS and VC1, were biased to the same voltage ( –10 V) and the second

analyzer electrode (V2) was set to 0 V. It may be recalled that the analyzer is

designed to capture an angular spread of 8 with respect to the central entrance

angle of 45 in the polar direction. The input angular spread in the azimuthal

direction is 100.

Fig. 4.1 – Layout of the specimen holder arrangement of the second–order focusing

toroidal energy analyzer showing the mounting of the LAO/STO specimen.

The sample and the first analyzer electrode are biased to negative voltages in order

to increase the SE analyzer signal sensitivity to specimen voltage changes [4.8]. In

VC2 = 0 V

VC1 = – 10 V

LAO / STO

Specimen

PE

VS = – 10 V

Chapter 4

80

the previous chapter it was shown that the second–order focusing toroidal energy

analyzer is able to detect specimen voltage changes with high signal–to–noise

characteristics. The scattered electron energy distribution can be obtained by

ramping the analyzer deflection electrode (VDEF) and monitoring the

photomultiplier (PMT) output, where the deflection electrode voltage is directly

related to the SE energy.

All experiments were carried out inside a Philips ESEM XL30 FEG SEM whose

primary beam was focussed on to a spot on the surface of the specimen in order to

generate secondary electrons. A personal computer (PC) was used to control VDEF

and monitor the PMT output through a National Instruments Data Acquisition (NI–

DAQ) board [4.9]. The deflection voltage was ramped in steps of 200 mV and each

point had a primary beam dwell time of approximately 150 ms. The scintillator

voltage of the PMT, VSC, was biased to 5 kV. The SE analyzer signal was collected

from regions which were exposed to the primary beam for the first time in order to

minimize the effects of contamination. At primary beam energy of 4 keV, the beam

current was measured to be 75 pA.

Fig. 4.2a is a schematic representation of the LAO/STO heterointerface specimen.

The specimen was fabricated by depositing a thin film of crystalline LAO,

equivalent to a thickness of 18 unit cells (U.C) of LAO, on crystalline STO

substrate.

Chapter 4

81

Fig. 4.2 – Schematic representation of the specimen: (a) Representation of the

2DEG formed at the interface of crystalline LAO and crystalline STO substrate (b)

Conducting and insulating interface regions side by side on the same sample (the

interface was made insulating by proton irradiation).

The deposition of LAO was done by using a process called pulsed laser deposition,

which involves ablating a LAO target onto TiO2 terminated STO (100) substrates.

Samples were prepared in a range of oxygen pressures (PO2) of 1 – 5 × 10–3 Torr

Chapter 4

82

at 750 °C. A nanometer thick 2DEG is formed at the buried LAO/STO

heterointerface. One half of the surface area of this sample was exposed to high

energy proton irradiation, while keeping the other half shielded from the proton

beam. A collimated ion beam was used to raster–scan under normal incidence to

expose a specific region to high energy protons. The regions are electrically

isolated, which was confirmed by the absence of conductivity between the regions

when subjected to direct conductivity measurements using Al wire bonding to the

interface. The proton irradiation causes the embedded interface to become

insulating while the other half, not exposed to the high energy proton irradiation, is

unaffected. The conductivity of the interface is controlled by adjusting the fluence

of the proton beam. However for the irradiated samples investigated in this work,

the interface was made completely insulating. The fabrication process of this

specimen has been described in detail by Mathew et al. [4.10].

4.2.3 Results and Discussion

SE analyzer signals were obtained separately from the conducting LAO/STO

heterointerface specimen and an uncoated STO substrate, and are shown in Fig. 4.3.

As seen in the plot, the SE analyzer signal obtained from the STO substrate contains

a single peak, as expected. However the nature of the SE analyzer signal changes

completely when taken from the surface directly above the conducting LAO/STO

heterointerface. In addition to the regular SE peak, which is similar in amplitude

and position to the only SE analyzer signal peak obtained from the uncoated STO

substrate, a second high amplitude SE peak also occurs. This second peak occurs

at a higher deflection voltage (SE energy) in comparison to the first SE peak and

Chapter 4

83

has amplitude, almost twice as high as that of the first SE peak, indicating the

presence of a high SE yield region.

Fig. 4.3 – Experimental SE analyzer signals obtained from an uncoated STO

substrate (shown in dotted line) and from the LAO/STO heterointerface with

conducting interface (shown in solid line). A primary beam acceleration voltage of

3 kV was used.

SE analyzer signals were then obtained from surfaces directly above both the

conducting and insulating LAO/STO parts of the heterointerface, and are shown in

Fig. 4.4.

Chapter 4

84

Fig. 4.4 – Experimental SE analyzer signals obtained from the LAO/STO

heterointerface with conducting interface (shown in solid line) and the insulating

LAO/STO heterointerface (shown in dotted line). A primary beam acceleration

voltage of 3 kV was used.

The process of transforming the conducting LAO/STO heterointerface into an

insulating one has been reported in detail by Mathew et al. [4.10]. Fig. 4.4 shows

that the SE analyzer signals obtained from the surface exposed to the proton

irradiation (insulating LAO/STO interface) are significantly different from the SE

analyzer signals obtained from the surface unexposed to the proton irradiation

(conducting interface) in both amplitude and position of the second peak. While the

first peak in the SE analyzer signal for both cases occurs at the same position,

relatively unchanged, the amplitude of the second peak in the SE analyzer signal

obtained from the surface above the insulating interface goes down by almost a

Chapter 4

85

factor of 2.5 in comparison to its amplitude for the conducting LAO/STO interface,

and its position shifts by around 10 volts. These results primarily show that when

the LAO/STO interface changes from conducting to insulating, significant contrast

occurs in the SE energy analyzer signals. Unlike the normal SE signal, which has a

single peak, there is an additional high amplitude SE analyzer signal peak obtained

when the interface is conducting. This indicates that there is more trapped charge

at the interface. These trapped charges are emitted easily due to interactions with

the primary beam and back scattered electrons (BSEs) and come out at energies

higher than the usual SE electrons, which shows up as a high amplitude second

peak in the SE signal. This is in sharp contrast to the SE signal obtained from the

specimen when the interface is insulating, the second SE peak is much reduced in

height and now shifts to the right, indicating that the electrons are more difficult to

remove after the interface becomes insulating, since higher deflection voltages

capture higher SE energies. Secondary electrons can be generated either by direct

interaction of the primary beam with the specimen volume or the interaction of

BSEs with the specimen. In this case, the specimen is a complex arrangement of a

thin LAO layer on bulk STO substrate and therefore to understand the exact

contribution to SEs from each material and the effect of BSEs on the SE signal is a

matter of future investigation. However the excellent contrast of SE signals

obtained from the LAO/STO sample when the interface is conducting and

insulating confirms the existence of the 2DEG at the LAO/STO interface, as

reported earlier [4.6, 4.11–4.13] and as verified by Mathew et al. by the use of

contact measurements [4.10]. The high contrast between the second peak of the SE

Chapter 4

86

analyzer signal obtained from the conducting and insulting parts of the LAO/STO

interface can only be attributed to the change in the electrical properties of the

interface, because the physical structure of the specimen (film thickness, material

density) remains unaltered by the high energy proton irradiation. These results

suggest that the SEM together with an energy analyzer can provide a contactless

way of monitoring charge present at the interface of thin film oxides.

Fig. 4.5 – Experimental secondary electron signals obtained from LAO/STO

hetero–interface at various primary beam energies. The signals are obtained at

primary beam electron energies of 2 keV, 3 keV, 4 keV and 5 keV (shown in green,

brown, pink and blue respectively).

The primary beam energy was found to be an important parameter in maximizing

contrast in the SE analyzer signals on the LAO/STO heterointerface sample. Fig.

4.5 shows SE analyzer signals obtained from the surface area of the specimen above

Chapter 4

87

the conducting LAO/STO interface at various primary beam energies. The SE

analyzer signal has a high dependency on the primary beam energy; the distinct

high amplitude second peak occurs only at a particular value of primary beam

energy, 3 keV in this case. At the primary beam energies of 2 and 5 keV, the second

peak is not present. At 4 keV, the second peak does occur in the SE analyzer signal

but the amplitude is reduced by around 75% of the 3 keV signal and the peak shifts

to the right.

Monte Carlo simulation of primary beam electron trajectories were carried out

using a software package called Casino [4.14] to help understand the dependence

of SE analyzer signal with primary beam energy. The simulation results, shown in

Fig. 4.6a, indicate that the interaction volume of the primary beams increases as the

primary beam energy increases, as expected.

The percentage energy loss of primary beam electrons is plot against depth from

the specimen surface and is shown in Fig. 4.6b. Using the percentage energy loss

of the primary beam electrons as a measure of the degree of interaction of the

primary beam with the sample, only the 10–50% 3 keV energy loss curve crosses

the interface (depth 8 nm form the surface), the 2 keV curve lies below it, while the

5 keV curve lies well above it. These simulations indicate that a primary beam of 3

keV interacts the most with the interface, confirming the results obtained by

experiment (shown in Fig. 4.5).

Chapter 4

88

a

2keV

4keV

3keV

5keV

b

Dep

th a

lon

g s

pec

imen

(n

m)

LAO/STO Interface

LAO/STO Interface

% Energy

Loss of PE

Chapter 4

89

Fig. 4.6 – Monte Carlo simulation of the electron trajectories: (a) Primary

beam/specimen interaction indicating the interaction volume of the electrons (b)

Energy contour of the percentage energy loss of primary beam electrons along the

depth of the specimen (c) A graphical plot of percentage energy loss of primary

beam electrons against the depth from the surface of the specimen. The red dotted

line indicates the LAO/STO interface at a depth of 8nm from the surface.

In the case of the 2 keV beam, the majority of the primary beam interaction occurs

within the top LAO layer, for higher energies of the primary beam (4 keV and 5

keV), most of the interaction of the beam with the sample occurs within the bulk

substrate. In general, the optimal value of primary beam energy is dependent on the

thickness of the deposited thin film (LAO in this case) and is proportional to the

film thickness. The results shown in Fig. 4.6 demonstrate that Monte Carlo

simulation of the primary beam/sample interaction is able to provide a good guide

on which beam energy should be used to maximize interaction with the interface.

c

Chapter 4

90

4.3 SE signal contrast in presence of magnetic fields above the specimen

In the previous section, experimental SE analyzer signals from multifunctional

oxide interfaces were obtained, and it was demonstrated how they could be used to

determine the conductivity of interfaces between thin–film oxides. In this section,

experimental SE analyzer signals in presence of magnetic fields above the specimen

are studied. A current carrying air–core solenoid coil of radius 13 mm, made up of

20 turns of enameled copper wire (thickness 0.2 mm) was placed under a stainless

steel disc (thickness 1 mm and radius 13 mm) as shown in Fig. 4.7. A 200 nm layer

of gold was thermally evaporated on top of the specimen to enhance the SE yield

and to avoid surface oxidation effects. The specimen and the first analyzer

electrode, denoted by VS and VC1, were biased to the same voltage ( – 10 V) and the

second analyzer electrode (VC2) was set to 0 V. The experiments were carried out

inside a Philips ESEM XL30 FEG SEM where a 5 kV, 100 pA primary beam was

focussed on to a spot on the surface of the specimen in order to generate secondary

electrons. As before, a personal computer (PC) was used to control VDEF and the

PMT output was obtained through a National Instruments Data Acquisition (NI–

DAQ) board [4.9]. The deflection voltage was ramped in steps of 250 mV and each

point had a primary beam dwell time of approximately 150 ms. The scintillator

voltage of the PMT, VSC, was biased to 5 kV.

Chapter 4

91

Fig. 4.7 – Schematic representation of the specimen holder with a current carrying

solenoid placed under the specimen to produce magnetic field. (Cross–section view

of the specimen holder is shown here, while the solenoid is shown completely).

Let the current flowing through the solenoid be positive if the magnetic field created

by the current points in the positive z–axis direction (see Fig. 4.7) at the center of

the solenoid, and conversely, let it be negative if this magnetic field points in the

negative z direction. Fig. 4.8a presents experimental SE analyzer signals in

presence of a B field along the positive z axis at the center of the solenoid. As the

current (I) through the coil increases, the amplitude of the SE analyzer signal

increases and the SE analyzer signal peak shifts to the left indicating a net decrease

in the kinetic energy of SEs passing through the final slit of the analyzer. This is in

sharp contrast to the experimental SE analyzer signals shown in Fig. 4.8b where

PE VC2 = 0 V

VC1 = – 10 V

VS = – 10 V

Current carrying

enameled copper

wire coil (20 turns)

Silver coated

(500 nm) Metal

specimen

z

13 mm

Chapter 4

92

the direction of the B field is now reversed by reversing the direction of the current

flowing through the coil.

B

B

No Current

25 mA

50 mA

75 mA

VC2 = 0 V

VC1 = – 10 V

VS = – 10 V

Deflection Voltage (VD)

PM

T O

utp

ut

(a.u

)

b

Deflection Voltage (VD)

PM

T O

utp

ut

(a.u

)

Current through

solenoid 75 mA

50 mA

25 mA

No current

B

B

VC2 = 0 V

VC1 = – 10 V

VS = – 10 V

a

Chapter 4

93

Fig. 4.8 – Experimental SE analyzer signals obtained from a metal specimen in

presence of magnetic field (B) created by current carrying solenoid under the

specimen: (a) SE analyzer signals obtained with B field along positive z direction

(b) SE analyzer signals obtained with B field along negative z direction (c) A plot

of SE analyzer signal expectation value (µ) against current flowing in the solenoid

creating the magnetic field (negative value of current indicates a current giving rise

to a B field along negative z–axis)

In this case, an increase in the field strength causes a decrease in the SE analyzer

signal while the signal peak shifts to the right. To further quantify these variations,

the output signal mean µ (otherwise referred to as expectation value) of the SE

analyzer signal is plot against the current (I) flowing through the solenoid at the

time of measurement. To reiterate, a negative current value simply means that the

direction of the B field setup by the current I at the centre of the solenoid points in

along the negative z–axis. This plot is shown in Fig. 4.8c.

Although the plot is not completely linear, it shows a definite trend in expectation

value of SE analyzer signal with change in the magnitude and direction of the B

field created by the current carrying solenoid under the specimen. The SE analyzer

Current (I) through the solenoid (mA)

Exp

ecta

tio

n v

alu

e (µ

) of

ou

tpu

t si

gn

al

(vo

lts)

c

Chapter 4

94

signal contrast observed here illustrates that SE analyzer signals obtained from the

second–order focusing toroidal analyzer are sensitive to magnetic field variations

above the specimen and therefore the technique can, in principle, be applied to the

characterization of magnetic samples, like mapping magnetic domain variations on

the surface of magnetic specimens. Further investigation is required to understand

how this magnetic contrast effect changes when the magnetic field is localised into

micro–magnetic domains on the specimen surface. However, these preliminary

experimental results point towards the basis of a new possible application for the

toroidal second–order focusing analyzer. Also, direct ray tracing simulation needs

to be carried out to better understand how specimen magnetic fields change the

trajectory paths of SEs, especially low energy SEs.

4.4 SE analyzer signal contrast due to surface oxidation of a thin film metal

layer specimen

Spontaneous surface oxidation of thin film metal layers is an important effect in the

field of microelectronics. As feature sizes of devices continue to shrink, even

minimal surface oxidation of thin films has a profound effect on device

characteristics especially for a metal like Aluminum, which has a tendency of

readily oxidizing in air to form a passivation layer. This effect has been studied

extensively in the past [4.15–4.19] and continues to be an area of investigation for

present day researchers [4.20–4.23]. In this section, experimental results are

presented which demonstrate that the second–order focusing toroidal analyzer is

capable of detecting changes in the nature of thin film aluminum layers due to

surface oxidation in air.

Chapter 4

95

A 500 nm thick Al layer was thermally evaporated on an undoped silicon substrate

(thickness 550 microns) which was mounted on a metal base and placed inside the

specimen holder arrangement of the toroidal analyzer as shown in Fig. 4. 9. The

experimental conditions and the data acquisition process were kept the same as in

the earlier experiment reported in section 4.3 of this chapter. The spontaneous

oxidation of the aluminum thin film was allowed to take place at room temperature

(22 C) and at ambient atmospheric partial pressures of oxygen.

Fig. 4.9 – Mounting of the Al coated silicon specimen inside the specimen holder

of the analyzer.

The time of exposure (to air) in our context is defined as the time from which the

SEM chamber was vented and the specimen was left in air to the time the specimen

was placed back inside the SEM chamber and the pumping of the chamber was

initiated. The beam conditions and the working distance were kept unchanged for

the entire duration of the experiment.

VS = VC1 = –10 V

VC2 = 0 V

Silicon substrate coated

with Al (500 nm)

PE

Chapter 4

96

Fig. 4.10a shows the experimentally obtained SE analyzer signals for different

times of exposure and they indicate that substantial contrast between signals

obtained between successive exposure times. The SE analyzer signal peak initially

tends to shift to the left and decreases in amplitude indicating a decrease in work

function and a decrease in the SE yield of the specimen. However longer exposure

to air causes the SE analyzer signal peak to shift to the right while the amplitude

increases initially but continues to decrease thereon with exposure time.

Fig. 10b shows a plot of the SE analyzer signal expectation value (µ) against the

exposure time of the specimen in air and as observed in Fig. 4.10a, the expectation

value initially decreases and then increases consistently with subsequent exposure

in air.

Researchers generally agree that oxygen is first chemisorbed on the surface of Al

and then gradually transformed into oxide, but the specifics of the process, as well

as the adsorption sites of the chemisorbed oxygen atoms, are still being debated

upon [4.15–4.19]. In the present context, it is sufficient to note that SE analyzer

signals obtained using the second–order focusing toroidal energy analyzer, show

significant contrast when acquired from Al thin films exposed to air for different

lengths of time, and that these variations can be quantified by simply monitoring

parameters like the signal expectation value. These preliminary results point

towards another possible application of the toroidal second–order focusing analyzer

in the SEM, that of quantifying the degree of oxidation that occurs on metal

surfaces.

Chapter 4

97

Fig. 4.10 – (a) Experimental SE analyzer signals obtained from a thin film Al layer

under varying time of exposure to air (b) A plot of the SE analyzer signal

expectation value against the exposure time in air of the Al thin film.

Deflection Voltage (VD)

PM

T O

utp

ut

(a.u

)

Exposure time = 0 min

10 mins

15 mins

30 mins

45 mins

a

Exp

ecta

tion

valu

e (µ

) of

ou

tpu

t si

gn

al

(volt

s)

Exposure time (mins)

b

Chapter 4

98

4.5 Conclusions

This chapter has presented new possible applications for energy analyzer

attachments inside the SEM. The first new application is the probing of interfaces

between insulating materials, where high contrast SE analyzer signals between

conducting and insulating LAO/STO heterointerface samples can be obtained. The

method may provide an attractive alternative to contact methods [4.10]. In

principle, it can be used to obtain high resolution spatial mapping of the interface

over a large area. This may be useful in situations where interface properties have

been patterned by lithography techniques. Future work is required to investigate the

role and contribution of back–scattered electrons (BSE) to the characteristic SE

analyzer signals obtained from the sample. Other new possible applications of

energy analyzers in the SEM are the probing of magnetic fields above the specimen

and the quantification of metal surface oxidation.

Chapter 4

99

References

4.1. Khursheed, A. and H.Q. Hoang, A second–order focusing electrostatic

toroidal electron spectrometer with 2π radian collection. Ultramicroscopy,

2008. 109(1): p. 104–110.

4.2. Kazemian, P., et al., High resolution quantitative two-dimensional dopant

mapping using energy-filtered secondary electron imaging. Journal of

Applied Physics, 2006. 100(5): p. 054901.

4.3. Gostev, A., et al., Updating of the toroidal electron spectrometer intended

for a scanning electron microscope and its new applications in diagnostics

of micro-and nanoelectronic structures. Technical Physics, 2013. 58(3): p.

447–454.

4.4. Mizuhara, Y., et al., Quantitative measurement of surface potential and

amount of charging on insulator surface under electron beam irradiation.

Journal of Applied Physics, 2002. 92(10): p. 6128–6133.

4.5. Thong, J.T., Electron beam testing technology. 1993: Plenum Publishing

Corporation.

4.6. Ohtomo, A. and H. Hwang, A high-mobility electron gas at the

LaAlO3/SrTiO3 heterointerface. Nature, 2004. 427(6973): p. 423–426.

4.7. Bogorin, D.F., et al., LaAlO3/SrTiO3-based device concepts. arXiv preprint

arXiv:1011.5290, 2010.

4.8. Hoang, H., M. Osterberg, and A. Khursheed, A high signal-to-noise ratio

toroidal electron spectrometer for the SEM. Ultramicroscopy, 2011. 111(8):

p. 1093–1100.

Chapter 4

100

4.9. National Instruments LabVIEWTM 2010. National Instruments.

4.10. Mathew, S., et al., Tuning the Interface Conductivity of LaAlO3/SrTiO3

Using Ion Beams: Implications for Patterning. ACS nano, 2013. 7(12): p.

10572–10581.

4.11. Kalabukhov, A., et al., Effect of oxygen vacancies in the SrTiO 3 substrate

on the electrical properties of the LaAlO 3∕ SrTiO 3 interface. Physical

Review B, 2007. 75(12): p. 121404.

4.12. Schoofs, F., et al., Carrier density modulation by structural distortions at

modified LaAlO3/SrTiO3 interfaces. Journal of Physics: Condensed

Matter, 2013. 25(17): p. 175005.

4.13. Siemons, W., et al., Origin of charge density at LaAlO 3 on SrTiO 3

heterointerfaces: Possibility of intrinsic doping. Physical review letters,

2007. 98(19): p. 196802.

4.14. Drouin, D., et al., CASINO V2. 42—A Fast and Easy‐to‐use Modeling Tool

for Scanning Electron Microscopy and Microanalysis Users. Scanning,

2007. 29(3): p. 92–101.

4.15. Batra, I.P. and L. Kleinman, Chemisorption of oxygen on aluminum

surfaces. Journal of electron spectroscopy and related phenomena, 1984.

33(3): p. 175–241.

4.16. Lauderback, L. and S. Larson, An AES and SIMS study of the effect of

temperature on the interaction of oxygen with Al (100). Surface Science,

1990. 233(3): p. 276–282.

Chapter 4

101

4.17. Michel, R., et al., Initial interaction of oxygen with aluminium single crystal

faces: a LEED, AES and work function study. Surface Science, 1980. 95(1):

p. 309–320.

4.18. McConville, C., et al., Synchrotron radiation core level photoemission

investigation of the initial stages of oxidation of Al (111). Surface Science,

1987. 188(1): p. 1–14.

4.19. Agarwala, V.K. and T. Fort Jr, Nature of the stable oxide layer formed on

an aluminum surface by work function measurements. Surface Science,

1976. 54(1): p. 60–70.

4.20. Li, J.–T., et al., The initial oxidation of poly-crystalline aluminum studied

with x-ray photoelectron spectroscopy. Journal of Physics D: Applied

Physics, 2014. 47(10): p. 105301.

4.21. Benka, O. and M. Steinbatz, Oxidation of aluminum studied by secondary

electron emission. Surface science, 2003. 525(1): p. 207–214.

4.22. Lanthony, C., et al., On the early stage of aluminum oxidation: An

extraction mechanism via oxygen cooperation. The Journal of chemical

physics, 2012. 137(9): p. 094707.

4.23. Kreiter, O., et al., Ion-induced oxidation of aluminum during reactive

magnetron sputtering. Journal of Applied Physics, 2013. 113(14): p.

143303.

Chapter 5

102

Chapter 5 – New secondary electron energy analyzer designs for

the SEM

5.1 Introduction

Recently, a Radial Mirror Analyzer (RMA), designed to be fitted as an attachment

inside the specimen chambers of scanning electron/ion microscopes has been

reported [5.1]. The analyzer is rotationally symmetric about the primary beam axis,

and functions by using an electric field to mirror scattered electrons/ions emitted

from the specimen in a radial direction, transporting them onto a flat ring shaped

detector plane as shown in the analyzer schematic in Fig. 5.1.

Fig. 5.1 – Simulated trajectory paths through the Radial Mirror Analyzer (RMA)

design by Hoang et al. [5.1], 13 rays are plot over a polar angular spread () of

6 in uniform angular steps, shown here from the specimen to the detector plane at

the central energy Ep.

Chapter 5

103

The analyzer is predicted to have a relatively high energy resolution– transmittance

performance arising from its second–order focusing properties; a relative energy

resolution of better than 0.025% for an opening entrance polar angular spread of

6, this is around an order of magnitude better than the well–known Cylindrical

Mirror Analyzer (CMA) [5.2]. The analyzer is also expected to have a relatively

large bandwidth in its parallel energy mode of operation, over 12% ( 6%) of the

central pass energy, a factor of around four times better than the Hemispherical

Deflection Analyzer (HDA) [5.3].

This chapter follows on from the theoretical design of the RMA, using the design

to make and test a first RMA prototype. The prototype analyzer operates as an add–

on attachment that is placed in the same position as a typical backscattered electron

detector in the SEM specimen chamber, thereby allowing for concurrent usage of

the SEM imaging mode.

Since there are significant advantages to widening the energy range of a SE

analyzer, and detecting different electron energies in parallel, another theme of the

research work reported in this chapter is directed towards designing a wide–range

parallel energy analyzer, one in which the energy of detection varies by an order of

magnitude. Starting with the RMA design, simulation methods based upon direct

ray tracing successively led to the design of new analyzer, a wide–range first–order

focusing Parallel Radial Mirror Analyzer (PRMA).

Chapter 5

104

5.2 A wide–range parallel energy analyzer design

5.2.1 Need for a high transmittance wide–range parallel energy analyzer

The potential advantages of using wide–range parallel energy detection of charged

particles to speed–up spectrometer data–acquisition times are already well known.

One class of parallel analyzer designs is based upon the Hyperbolic Field Analyzer

(HFA), first reported by Curtis and Hsieh [5.4], and later rediscovered by Jacka et

al. working in the context of Auger Electron Spectroscopy (AES) [5.5–5.7]. The

Jacka et al. HFA design detects electrons in parallel over an energy range typically

from 75 to 2600 eV [5.7]. Recently, the HFA has been developed into an AES

attachment for Scanning Electron Microscopes (SEMs) by Cubric et al. [5.8], the

Shimadzu PAG4 analyzer, to be used in combination with a low voltage Argon ion

source. The entire Auger electron spectrum from the HFA can be captured in 1–2

seconds after the specimen surface has been cleaned by the ion gun, before any

appreciable hydrocarbon contamination on the specimen surface is allowed to

build–up. In this way, the HFA opens up the possibility of performing AES at high

vacuum pressures (10–7 to 10–6 Torr), obviating the usual requirement of AES

having to be carried out in Ultra High Vacuum (UHV) conditions (10–10 to 10–9

Torr). There are of course, similar possible data–acquisition time speed–up

advantages for SE energy analysis inside the SEM, and this forms the main

motivation for developing a wide–range energy analyzer design here.

Results from earlier chapters in this thesis using the second–order focusing toroidal

analyzer, a sequential bandpass energy analyzer, demonstrated that it can obtain

high signal–to–noise SE analyzer signals with a dwell time of approximately 150

Chapter 5

105

ms per sample (refer chapter 3 and 4), which means a SE spectrum with 100 points,

can be acquired in around 15 seconds. There are many instances where the speed–

up of SE analyzer signal data–acquisition time is required. It is necessary for

applications such as monitoring of hydrocarbon contamination build–up on the

specimen surface inside the SEM or characterization of insulators that tend to

charge up under the primary beam, or when energy filtered SE analyzer signals are

used to form images. Unlike Auger spectroscopy, which requires analyzers to have

high transmittance and high energy resolution at the same time, SE spectroscopy

applications require primarily high transmittance, which translates into good

signal–to–noise characteristics of the analyzer’s output signal. SE energy analyzer

applications typically require monitoring of changes in parameters like analyzer

signal peak position and/or the analyzer signal shape, which do not depend on the

energy resolution of the analyzer. Therefore, it is the transmittance of a wide–range

parallel energy analyzer that is more important when designing it for SE energy

analysis applications.

At present, analyzers based upon the HFA design have relatively small

transmittance; in the Jacka et al. proposal, the analyzer is reported to have an energy

resolution of 0.8% at 100 eV and 0.16% at 2500 eV, and the entrance angular spread

is limited to around 2.2 ( 1.1) in both polar and angular directions, translating

into less than 0.05% of all electrons emitted from the specimen reaching the

detector [5.7]. Although this has been improved by Cubric et al. to around 2.4 in

the polar angular direction and 5 in the azimuthal angular direction, the overall

transmittance is still relatively small, typically 0.1%, around 100 times smaller than

Chapter 5

106

that of the CMA (for a comparable energy resolution). This relatively low

transmittance comes from two limitations. Firstly, current HFA designs are

characterized mainly by first–order focusing properties on the detector plane,

limiting the angular spread in the plane of deflection (polar angular direction) to

relatively small values, typically less than 1.2. Secondly, since HFA designs

have been up to now, planar in geometry, electrons are detected over a narrow out–

of–plane angular range (azimuthal angular direction), typically less than 2.5.

Recognizing the need to improve the HFA transmittance, some authors have

proposed rotationally symmetric wide–range parallel energy analyzer designs.

However, within the context of scanning electron/ion microscopes, none of the

parallel analyzer designs proposed so far are rotationally symmetric with respect to

the scattered electrons/ions that are emitted from the specimen (primary beam axis).

They are, like the planar HFA, located to one side of the specimen, and limit the

range of out–of–plane electrons that can be detected. Cizmar et al. proposed a

rotationally symmetric version of the HFA, where the analyzer has a similar cross–

sectional field distribution through its axis of rotation to the planar HFA field

distribution. However, the axis of symmetry of the analyzer is in the horizontal

direction (perpendicular to the primary beam axis) and the range of energies on the

detection plane only varies by a factor of two [5.9]. Read proposed a wide–range

parallel analyzer design based upon the CMA layout, with its rotational axis of

symmetry lying in the horizontal direction, and refers to it as the Parallel

Cylindrical Mirror Analyzer (PCMA) [5.10]. The PCMA is similar to the CMA,

except that a linear potential variation is applied to the outer cylinder in the axial

Chapter 5

107

direction. The most practical class of PCMA designs was later developed by Read

et al. into an “axis to axis” PCMA configuration, where both the source and

detection plane lie on the analyzer’s axis of rotational symmetry [5.11]. They

assume that the source is located on the PCMA rotational axis, and that it emits

electrons/ions uniformly around it, different to the scanning electron/ion

microscope case, where secondary electrons/ions are emitted above and about the

primary beam axis. The axis to axis PCMA reported by Read et al. has an energy

range that varies from 300 to 1500 eV (change of detection energy by a factor of

5), and its predicted transmittance is over a magnitude better than that for the planar

HFA Jacka et al. design [5.10]. The polar angular spread is, like that of the planar

HFA design, relatively small, 2.1 ( 1.05). Cubric et al. have recently adapted

the PCMA Read et al. design to make it more suitable as an attachment for scanning

electron/ion microscope [5.8]. They relocate the entrance point to lie on the

analyzer front plate, instead of on the inner cylinder plate, so that the distance

between the analyzer entrance and the primary beam axis can be increased,

providing more room to fit it into place. They also redesign the analyzer so that

scattered electrons/ions land over a rectangular region on the detection plane,

instead of producing a line focus along the rotational axis of symmetry, in order to

reduce the intensity of focus on the detector. In the Cubric et al. design, the energy

range is widened so the detected energy range varies by a factor of 25. The

azimuthal angular spread (out–of–plane angular spread) that can be accepted into

the analyzer is 30.

Chapter 5

108

The following work is based upon designing analyzers that are fully rotationally

symmetric with respect to the primary beam axis, and do not place restrictions on

the scattered electron/ion azimuthal angular range, that is, they have a range of 360

in the out–of–plane direction. The following section presents the design of a first–

order focusing wide–range parallel Radial Mirror Analyzer (RMA), which will be

referred to here as a first–order Parallel Radial Mirror Analyzer (PRMA). Although

the analyzer has first–order focusing properties at the detector plane, for SE signal

acquisition, the exit slit may be widened and the polar entrance angle can be

increased to increase the transmittance of the analyzer. This becomes possible as

signal–to–noise characteristics and not energy resolution of the analyzer is the main

consideration as far as SE analyzer signal acquisition is concerned.

The design approach taken in the following work is essentially a simulation based

one, where all field distributions and electron trajectory ray paths were simulated

using the Lorentz–2EM program [5.12]. This program utilizes the boundary

element method to solve for electrostatic field distributions, in which an adaptive

segment technique automatically optimizes the number of charge segments used on

conductor surfaces, refining them according to the local field strength, and therefore

achieving higher accuracy for a given program run time. A 5th order Runge–Kutta

method variable step method is used for direct ray tracing of charged particle

trajectories, where the trajectory step is adjusted according to the local truncation

error. The accuracy of all simulations were continually checked by repeating all

results with smaller boundary segments and trajectory step sizes, ensuring that

important ray tracing parameters, such as the final focal spot–size of the electron

Chapter 5

109

beam at the spectrometer exit did not change significantly (by less than 1 %). Apart

from estimating the energy resolution visually by observing simulated electron ray

paths around the focal plane, it was calculated numerically from trace–width and

energy dispersion characteristics along the detection plane as a function of electron

energy.

5.2.2 A first–order focusing wide–range PRMA design

Fig. 5.2 shows simulated trajectories through the conventional ideal HFA design,

in which the potential field distribution V(x,y) is described by the following simple

analytical equation

𝑉 (𝑥, 𝑦) =2𝑉0

𝑅02 𝑥𝑦

where V0 is the potential on a curved hyperbolic shaped electrode whose tip (at x =

y) is located at a distance R0 from the analyzer bottom left–hand corner (x= 0, y=0).

The bottom and left–hand side boundaries of the analyzer are fixed to be at zero

volts, and an ideal grid is assumed at the bottom boundary where electrons/ions

enter the analyzer. Note that the distance R0 here, corresponds to 2 times the

variable b used by Jacka et al. [5.6]. Eleven trajectories from the specimen (located

outside the analyzer) are evenly plot over a polar angular spread of – 1.1 to 1.1

around a central entrance polar angle of 25 with respect to the x axis for the

electron energies of 100, 200, 500, 1000, 2000, 3000, and 5000 eV. Equipotential

lines of 500 – 4000 volts in 500 volt steps are also indicated. The simulated energy

resolution, corresponding to half the trace–width on the detector plane, starts out

around 0.65% at 100 eV and drops to 0.2% at 5000 eV. If the polar angular spread

Chapter 5

110

ranges from – 3 to 3, the simulated energy resolution varies from 1.68% at 100

eV, reaches a maximum of 2.25% at 500 eV and drops to 1.33% at 5000 eV.

Fig. 5.2 – Simulated trajectory paths through a planar ideal hyperbolic field

analyzer design at the energies 100, 200, 500, 1000, 3000 and 5000 eV. For each

energy, eleven trajectories are plot evenly between −1.1° and 1.1° around a 25°

polar entrance angle.

The HFA layout shown in Fig. 5.2 is the one reported to have a single second–order

focusing point at 100 eV, and first–order focusing properties for all other energies

[5.6], where the energy (E) to voltage ratio (V0) for R0 = 14.14 mm is 1.19 (V0 = –

84.03 volts). However, the simulation work performed here finds the 2nd order focus

to be located at 50 eV for these conditions, and not at 100 eV. In order to obtain 2nd

order focusing at 100 eV, the present simulations indicate that V0 needs to be –

166.67 volts at R0 = 14.14 mm, which corresponds to (E/V0) = 0.6 and not 1.19 as

reported previously. If a (E/V0) ratio of 0.6 is used, then the simulated energy

resolution for the higher energy range is predicted to be 0.38% at 2000 eV and

0.27% at 5000 eV, instead of 0.29% and 0.2% respectively at a (E/V0) ratio of 1.19.

In the present context, this difference is not important, the main point here is that

Primary

Beam 5 cm

100 200 500 1000 2000 3000 5000 eV

Chapter 5

111

there is only one energy for which second–order focusing occurs, while for all other

energies, the analyzer is characterized by first–order focusing properties. To be

consistent with what has been reported previously, a (E/V0) ratio of 1.19 is taken to

be representative of previous HFA designs.

As a first step towards transforming the HFA into a wide–range parallel first–order

RMA, let us use the electrode layout of the HFA depicted in Fig. 5.3, and map it

into a rotational symmetric geometry, where the axis of rotational symmetry lies on

the primary beam axis.

A hyperbolic shaped mirror conductor boundary at –1500 volts for R0 = 2 cm (in

the ideal HFA described by equation 1) becomes a fixed boundary condition in the

new axi–symmetric coordinate system, the zero boundaries maintain their relative

positions, and the resulting field distribution is then solved numerically by the

Lorentz–2EM [5.12] software with the origin of the coordinate system placed at the

specimen. Fig. 5.3 shows simulated ray paths for energies 250, 750, 1250, 1750 and

2500 eV in the transformed rotationally symmetric geometry. They indicate that

simulated electron trajectory paths no longer focus on to a horizontal detector plane.

In general, for rotationally symmetric structures, a different electrode layout to the

ideal HFA one is therefore required.

Chapter 5

112

Fig. 5.3 – Simulated ray paths for energies 250, 750, 1250, 1750 and 2500 eV in

the ideal HFA electrode layout (R0 = 2 cm and V0 = –1500 volts) transformed into

axi–symmetric cylindrical coordinates. Nine trajectories plot with an angular

spread over 1.1.

A rotationally symmetric analyzer, modeled on the geometrical layout of the

present RMA (shown in Fig. 5.1), but using deflection potentials from the ideal

HFA formula (equation 5.1) as starting values was specified. Simulated trajectory

paths indicated that more than three conical deflectors were required in order to

provide better control of the focal point positions on the final detection plane, and

that the main deflector could be successfully represented by a single straight

electrode (in the cross–sectional plane). Continual refinement of the deflection

electrode potentials and geometry was carried out in order to focus all energies on

to the bottom detection plane, and this led to the wide range parallel rotational

symmetric analyzer design shown in Fig. 5.4.

Rotational axis

Specimen

Focal plane

V0

0 V

0 V

Radius 2500 1750 1250 750 250 eV

Chapter 5

113

Fig. 5.4 – Simulated trajectory paths through a first–order focusing PRMA design.

Electrons are plot for energies 50, 100, 200, 500, 1000, 1500, 2000 and 2500 eV

with 9 electron trajectories over a polar angular spread of ± 1.1˚ around a central

angle of 24.8˚. V1 = – 45V; V2 = – 120 V; V3 = – 285 V; V4 = –775V ; V5 = –

1150V; V6 = – 1675V; V7 = – 2020V.

A set of deflection electrodes inside the analyzer, at voltages V1 to V6, lie along a

conical surface above the entrance grid, and can be used to control the focal point

position for different energies. The top curved mirror electrode in the ideal HFA

design is substituted with a single straight electrode V7 (straight in the cross–

sectional plane). Electrons are plot for energies 50, 100, 200, 500, 1000, 1500, 2000

and 2500 eV with 9 electron trajectories over a polar angular spread of ± 1.1˚ around

a central angle of 24.8˚, and the equipotentials in uniform steps of 135 volts range

from 0 to –2020 volts. The electrode voltages (in volts) are: V1 = –45, V2 = –120,

V3 = –285, V4 = –775, V5 = –1150, V6 = –1675, and V7 = –2020.

The voltages V1 to V7 were systematically adjusted to focus electrons on to the

horizontal bottom analyzer plane, starting with the lower energy range. Focusing

Chapter 5

114

onto a horizontal detection plane is predicted for a variety of different electrode

geometries, and for each layout, its electrode voltages need to be systematically

adjusted (starting with the lower energies). As a general guide, for the analyzer

layout shown in Fig. 5.4, the voltages V1 and V2 largely control focal point positions

in the lower energy range (0 – 200 eV), V3 to V5 mostly control the focal point

positions in the middle energy range (200 to 1500 eV), while V5 and V6 mainly

control the focal point positions of higher energy electrons (1500 to 2500 eV). The

voltage V3 has an effect on focal point positions in the lower energy range, but this

can be easily compensated by changing V2. The voltage V7 has the overall effect of

shifting the focal point position horizontally. Although the voltage V1 affects the

focusing of the entire energy range, its effect greatly diminishes as the electron

energy increases, and since only small changes in V1 are required to control the

focal point positions of the lower energy electrons, the effect of these changes on

the higher energy electrons is negligible.

Fig. 5.5a shows simulated rays paths around the focal plane in the rotationally

symmetric wide–range analyzer design for electron energies 2% below and above

the central energies of 500 and 1500 eV (angular spread of 1.1). They provide a

visual estimation of the relative energy resolution (half trace–width) to be in the

0.25 to 0.3% range. A more rigorous approach, based upon calculating the trace–

width and energy dispersion characteristics along the detection plane is presented

in Table 5.1.

Chapter 5

115

Table 5.1 – Simulated energy resolution for first–order focusing PRMA designs.

The simulated energy resolution typically varies from 0.46 to 0.25% across the 50

to 2500 eV energy range, comparable to those predicted for the ideal planar HFA

design, where there is a maximum simulated energy resolution of 0.68% in the

lower energy range (at 200 eV), falling to 0.265% at 2500 eV. Fig. 5b shows the

simulated trace–width as a function of angular spread, indicating that the analyzer

design is predicted to have first–order focusing properties (second–order spherical

aberration) across its entire detected energy range.

Simulated % relative energy resolution

1.1 angular spread

Energy (eV) First–order focusing PRMA

Previous ideal HFA

design

50 0.463 0.114

100 0.408 0.588

200 0.462 0.680

500 0.274 0.514

1000 0.241 0.387

1500 0.250 0.325

2000 0.238 0.291

2500 0.255 0.265

Chapter 5

116

Fig. 5.5 – Simulated spot size charcteristics of the first–order focusing PRMA

design: (a) Direct ray paths at the focal plane for 2% energies around the central

energies of 500 eV and 1500 eV (b) Trace–width as a function of input polar

angular spread ranging from –20 mrad (–1.145) to +20 mrad (+1.145).

a

b

Chapter 5

117

5.3 Experimental prototype of a RMA attachment inside a SEM specimen

chamber

Fig. 5.1 shows the layout of the RMA design and simulated ray paths for scanning

electron/ion microscopes, similar to the one recently reported by Hoang and

Khursheed [5.1]. Scattered electrons/ions leave the specimen located below the

analyzer on its rotational plane of symmetry (primary beam axis), they enter the

analyzer through a grid and are mirrored down by negatively biased electrodes, exit

the analyzer through another grid, and are brought to focus beneath it on a

horizontal detector. The analyzer has an outer zero volt plate, conical in shape on

the top so that it fits under the lower pole–piece of a scanning electron/ion

microscope objective lens. This arrangement minimizes the working distance (the

distance between the objective lens lower pole–piece and the specimen), allowing

the scanning electron/ion microscope to operate in a high spatial resolution imaging

mode. The first series of deflector plates within the analyzer are three conical

electrodes at potentials, V1, V2 and V3, and they are followed by a main top deflector

plate, biased to VD. The required take–off angle from the specimen, with respect to

the horizontal direction, is . The analyzer focal properties, position and quality of

focus on the horizontal detector plane, as well as the energy bandwidth, are all

determined and controlled by the deflector plate voltages and take–off angle. For

the analyzer layout shown in Fig. 1, these design parameters are as follows: =

33.4, V1 = – 0.172EP, V2 = – 0.470EP, and V3 = – 0.570EP, and VD = – 0.540EP,

where EP is the analyzer central (pass) energy (in electron volts), and 13 simulated

rays in uniform angular steps are plot within an angular spread () of 6 at

Chapter 5

118

energy Ep. Although the analyzer design shown in Fig. 5.1 is similar to the one

reported by Hoang and Khursheed, it does however, incorporate a small

improvement which is important to highlight in the present context. Instead of the

main top deflector (at voltage VD) having a concave curved shape (in the cross–

sectional plane), it consists of two straight segments. This not only makes it easier

to manufacture, but it also seems to improve the simulated energy resolution at the

detector plane by approximately a factor of two. The fact that the main curved

deflector plate of the RMA design can be simply substituted by two straight

segments (straight in the cross–sectional plane), suggests that there is no advantage

to be gained by using curved electrodes, and straight deflector electrodes in the

radial cross–section are likely to be adequate also for the present analyzer design.

Based on this theoretical design, the first prototype of the RMA was fabricated to

fit as an attachment inside a Philips ESEM XL30 FEG SEM. The main design

philosophy was to allow the SEM to operate in the normal imaging mode while

concurrently acquiring signals using the analyzer. Fig. 5.6 illustrates how the RMA

prototype fits inside the SEM; the analyzer is mounted on a push-pull linear

manipulator fitted onto one of the ports of the SEM chamber. The push-pull linear

manipulator facilitates the movement of the analyzer to bring it closer to the final

pole piece of the SEM and occupy the typical position of a BSE detector during

operation and to withdraw the analyzer when not in use. In this way, the analyzer

can be used to acquire the energy filtered scattered electron signals while the

conventional SE detector can continue to operate normally, acquiring high

resolution topographical images of the specimen.

Chapter 5

119

Fig. 5.6 – Schematic diagram showing the integration of the RMA attachment

inside the SEM chamber with other components. Such a mounting of the analyzer

facilitates operation of the SEM in the normal imaging mode.

The experimental layout of the RMA, to fit as an attachment inside the SEM, is

depicted in Fig. 5.7. A potential divider arrangement is used to bias the deflector

electrodes at their respective voltages for a given pass energy. The voltage to the

30

cm

Electron Column final

pole piece Conventional SE

detector

PE

Philips ESEM XL30

Vacuum Chamber

Linear manipulator

Radial mirror analyzer

attachment prototype

Specimen

Specimen stage

Chapter 5

120

potential divider is ramped to capture the scattered electron spectrum. The

spectrometer is designed to capture an angular spread of ± 6 with respect to the

central entrance angle of 33.4 in the polar direction, which is achieved by varying

the height of the specimen and position of the analyzer. The effective input angular

spread in the azimuthal direction is 100.

Fig. 5.7 – Experimental layout of the RMA inside the SEM.

SEM

column

Specimen

VD

V1

V2

V3

θ = 33.4

0 V

3.4 cm Rotational

symmetry

Primary

Analyzer

0 V

0 V

shielded

casing

PMT

+

Scintillator

+5 kV

0 V

0 V

80% open

Metal grids

Exit slit (500 µm)

7 cm

Potential divider

Voltage

SEM STAGE

Electron

Trajectory

Chapter 5

121

The outer cover is grounded in order to prevent electric field leakage into the SEM

specimen chamber. Two grounded electrostatic grids are also used to cover the

entrance and the exit of the spectrometer in order to avoid distortion of the electric

field near these regions. The RMA design focuses the transmitted electrons in such

a way that electron trajectories travel radially out upon exit, and do not naturally

converge to a point like they do in the toroidal analyzer. Ideally, an electrostatic

deflector (some kind of post–analyzer toroidal deflector) is required to redirect all

out–of–plane electrons towards the primary beam axis and focus them on to a single

electron detector placed below the specimen stage. However, for this preliminary

prototype experiment, it was not done due to space and time constraints. Instead, a

PMT/scintillator fixed to the bottom of a 0 volt shielded box was placed below the

RMA exit slit aperture, as shown in Fig. 5.7. The shielding prevents electrons from

being affected by other electrostatic fields while they travel to the PMT. The

transport efficiency from the RMA exit slit to the PMT is expected to be low,

however, for these preliminary proof–of–concept experiments, this arrangement

was found to be adequate for capturing the SE energy spectrum. A 3D drawing of

one half of spectrometer attachment prototype and a photo of the fabricated

attachment integrated with the SEM is given in Fig. 5.8.

Chapter 5

122

Fig. 5.8 – A prototype of the RMA attachment: (a) Cross–section 3D CAD model

(b) A photo of the attachment integrated inside the SEM.The azimuthal deflection

angle is 100.

3.4 cm

Metallic Grids

Exit Slit

PMT with

Scintillator

Analyzer deflector

electrodes

a

b

Chapter 5

123

Experimental SE spectra, obtained from the initial prototype of the RMA are

presented in Fig. 5.9. The experiments were conducted inside a Philips ESEM

XL30 FEG SEM with a primary beam energy of 10 keV (beam current 150 pA)

and the deflection voltage was ramped in steps of 200 mV. A silicon wafer coated

with 300 nm of gold was used as the specimen.

The experimental SE analyzer signals obtained here are similar to the expected

Chung–Everhart SE distribution (refer chapter 2) [5.13], and they shift to the right

as the specimen is biased to – 2 V, indicating an increase in initial kinetic energy

(also expected).

Fig. 5.9 – Experimental SE analyzer signals obtained using the first experimental

prototype of the RMA.

Analysis of the SE analyzer signals shown in Fig. 5.9 reveals that the SE signal

levels are much lower than expected, typically a factor of 100 lower than the signal

strength obtained by the second–order focusing toroidal analyzer used for the

PM

T o

utp

ut

(a.u

)

Deflection Voltage (Volts)

Specimen Voltage = 0 V

Specimen Voltage = – 2 V

VS = VC1

Chapter 5

124

earlier experiments as described in chapters 3 and 4 of this thesis. A factor of only

one half is expected due to the 80% transparency of the entrance and exit grids

together with the smaller entrance angular spread (± 6º instead of ± 8º). These

experimental results points towards low transport efficiency from the RMA slit to

the PMT, which is at present not designed to capture the out–of–plane electrons. A

new detection strategy is required, in order to redirect and focus the out–of–plane

electrons. This proposal is discussed in more detail in the next chapter, nevertheless,

preliminary experimental have been carried out which validate the working

principle of the RMA analyzer.

5.4 Conclusion

This chapter has presented a new wide–energy parallel analyzer attachment design

for the SEM, the first–order PRMA, which can be used to speed–up the data–

acquisition time of SE analyzer signals. This chapter has also presented

experimental results from a prototype RMA spectrometer operating as an

attachment inside the SEM chamber, occupying the same position as a typical BSE

detector. The preliminary SE spectral results validate the general principle of the

analyzer, however, further work is required to devise and implement an efficient

technique to collect the transmitted electrons from the RMA exit slit to the detector.

Chapter 5

125

References

5.1. Hoang, H.Q. and A. Khursheed, A radial mirror analyzer for scanning

electron/ion microscopes. Nuclear Instruments and Methods in Physics

Research Section A: Accelerators, Spectrometers, Detectors and Associated

Equipment, 2011. 635(1): p. 64–68.

5.2. Sar‐El, H.Z., Criterion for Comparing Analyzers. Review of Scientific

Instruments, 1970. 41(4): p. 561–564.

5.3. Benis, E. and T. Zouros, The hemispherical deflector analyser revisited: II.

Electron–optical properties. Journal of Electron Spectroscopy and Related

Phenomena, 2008. 163(1): p. 28–39.

5.4. Curtis, C. and K. Hsieh, Compact wide‐aperture hyperbolic analyzers.

Review of scientific instruments, 1988. 59(11): p. 2424–2428.

5.5. Jacka, M., et al., A fast, parallel acquisition, electron energy analyzer: The

hyperbolic field analyzer. Review of scientific instruments, 1999. 70(5): p.

2282–2287.

5.6. Jacka, M., A. Kale, and N. Traitler, Hyperbolic field electron energy

analyzer with second–order focusing. Review of scientific instruments,

2003. 74(10): p. 4298–4300.

5.7. Jacka, M., Scanning Auger microscopy: recent progress in data analysis and

instrumentation. Journal of Electron Spectroscopy and Related Phenomena,

2001. 114–116(0): p. 277–282.

5.8. Cubric, D., et al., Parallel acquisition electrostatic electron energy analyzers

for high throughput nano–analysis. Nuclear Instruments and Methods in

Chapter 5

126

Physics Research Section A: Accelerators, Spectrometers, Detectors and

Associated Equipment, 2011. 645(1): p. 227–233.

5.9. Cizmar, P., et al., New multichannel electron energy analyzer with

cylindrically symmetrical electrostatic field. Review of scientific

instruments, 2007. 78(5): p. 053714.

5.10. Read, F.H., The parallel cylindrical mirror electron energy analyzer.

Review of Scientific Instruments, 2002. 73(3): p. 1129–1139.

5.11. Read, F.H., et al., The parallel cylindrical mirror analyzer: axis–to–axis

configuration. Nuclear Instruments and Methods in Physics Research

Section A: Accelerators, Spectrometers, Detectors and Associated

Equipment, 2004. 519(1–2): p. 338–344.

5.12. LORENTZ – EM. 2011, Integrated Engineering Software Inc, Canada.

5.13. Chung, M.S. and T.E. Everhart, Simple calculation of energy distribution

of low‐energy secondary electrons emitted from metals under electron

bombardment. Journal of Applied Physics, 1974. 45(2): p. 707–709.

5.14. Khursheed, A., H.Q. Hoang, and A. Srinivasan, A wide–range Parallel

Radial Mirror Analyzer for scanning electron/ion microscopes. Journal of

Electron Spectroscopy and Related Phenomena, 2012. 184(11): p. 525–532.

Chapter 6

127

Chapter 6 – Conclusions and Suggestions for future work

6.1 Conclusions

The main objective of this thesis was to improve upon the current analytical

capabilities of the SEM by the use of secondary electron energy analyzer

attachments, transforming it into a more powerful tool for nanometer scale material

analysis.

Experimental results were presented to demonstrate that it is possible to obtain high

signal-to-noise voltage and dopant concentration measurements on semiconductor

specimens using the second–order focusing toroidal energy analyzer attachment

even in the presence of fringe fields and surface fields above the specimen. A

variety of new applications for SE energy analyzers in the SEM were also reported.

High contrast SE analyzer signals were obtained from: multi-functional oxide

interfaces; from specimen in changing magnetic fields; and from oxidizing thin film

metal layers. A new wide-range parallel SEM energy analyzer attachment design,

the first–order parallel Radial Mirror Analyzer (PRMA), was reported. The first-

order PRMA can be used to acquire SE analyzer signals simultaneously across the

complete SE energy range, speeding up data acquisition time by more than an order

of magnitude. Finally, an experimental prototype of the Radial Mirror Analyzer

SEM attachment was made, and preliminary experimental results were obtained to

verify its working principle. The RMA attachment can be placed in the SEM

chamber in the same position occupied by BSE detector attachments, and has the

Chapter 6

128

advantage of having high performance optics while at the same time allowing for

short SEM working distances (< 10 mm).

6.2 Suggestions for future work

The work presented in this thesis forms a good basis for future work in the areas

elaborated below.

The current prototype of the second order focusing toroidal analyzer has a limited

circular field of view of about 1 mm in diameter. Also movement of the specimen,

once they are loaded inside the specimen holder, is not possible. Therefore the

analyzer prototype may be modified in such a way that the analyzer becomes part

of the SEM chamber which can be brought into operation using a linear manipulator

when required as shown in Fig. 6.1.

Fig. 6.1 – Proposed modification of the second order focusing toroidal analyzer

where the specimen is independent of the main analyzer body, allowing free

movement of the specimen.

Chapter 6

129

The results obtained from p-Si/n-ZnO heterojunction samples are a good starting

point for an in-depth study of other p-n junction specimen, like solar cells and these

results can be compared with those obtained using established methods for p-n

junction characterization.

The experimental results obtained from buried interfaces of multi-functional oxides

hold great promise of being the basis of a new contactless technique of

characterizing the conductivity of thin film oxide interfaces. In order to gain a better

understanding of its potential, the technique needs to be applied to multifunctional

oxide devices made up of different materials. The SE analyzer signal contrast

obtained from a specimen in presence of magnetic fields (created by a current

carrying solenoid placed under the specimen) naturally leads to the question of how

this technique might be applied to the study of local micro-magnetic domains on

the specimen.

Another important direction of future work that needs to be carried out is to design

and develop a post analyzer deflector for the Radial Mirror Analyzer (RMA), to

redirect and focus the transmitted electrons exiting at different azimuthal angles to

a single point or line that can be conveniently detected by a single PMT or

channeltron detector. One strategy, shown in Fig. 6.1 is to use a toroidal electric

sector analyzer placed below the RMA exit aperture slit, deflecting all transmitted

electrons back towards the primary beam axis, and focusing them on to single

detector placed below the specimen stage. The simulation results shown in Fig. 6.1

were obtained through the use of Lorentz 2EM. Finally, future work should also be

directed towards making a prototype of the first–order focusing PRMA design and

Chapter 6

130

use it to speed up data acquisition time, and thereby create new possible

applications, such as acquiring nanoscale quantitative SE analyzer images.

Fig. 6.2 – Proposed post analyzer deflector arrangement for the RMA attachment;

7 rays are plot over a polar angular spread () of 6 in uniform angular steps,

shown here from the specimen to the scintillator of the PMT through the post

analyzer deflector, at the central energy Ep. The magnitude of VPD was

experimentally calculated to be 0.436EP.

Radial Mirror

Analyzer attachment

SEM stage

Analyzer exit

+ VPD – VPD

Scintillator voltage

VSC = + 5000 V

SEM Column

Post analyzer deflector

arrangement

θ = 33.4

Appendix A

131

Appendix A: Publications resulting from this project

Journal

1. Khursheed, A., H.Q. Hoang, and A. Srinivasan, A wide-range Parallel Radial

Mirror Analyzer for scanning electron/ion microscopes. Journal of Electron

Spectroscopy and Related Phenomena, 2012. 184(11): p. 525-532.

2. Srinivasan, A., and A. Khursheed., Probing and Analyzing Buried Interfaces

of Multifunctional Oxides Using a Secondary Electron Energy Analyzer.

Microscopy and microanalysis: the official journal of Microscopy Society of

America, Microbeam Analysis Society, Microscopical Society of Canada

(2014): 1-5.

3. Srinivasan, A., and A. Khursheed. "Voltage and dopant concentration

measurements of semiconductors using a band-pass toroidal energy analyzer

inside a SEM" - Submitted to Elsevier-Ultramicroscopy.

Conference Proceedings

1. Srinivasan and A. Khursheed , “Detection of surface voltage changes using a

second–order Focusing toroidal energy analyzer SEM attachment”, Proceeding of

the 13th International Seminar on Recent Trends in charged particle optics and

Surface Physics Instrumentation, Skalsky Dvur near Brno Czech Republic, pp73,

2012.