11/8/99 SFR Workshop - Lithography 1 Small Feature Reproducibility A Focus on Photolithography...

11/8/99 SFR Workshop - Lithography

1

Small Feature Reproducibility

A Focus on Photolithography

UC-SMART Major Program Award

Spanos, Bokor, Neureuther

Second Annual Workshop

11/8/99


2

Agenda

8:30 – 9:00 Introductions, Overview / Spanos

9:00 – 10:15 Lithography / Spanos, Neureuther, Bokor

10:15 – 10:45 Break

10:45 – 12:00 Sensor Integration / Poolla, Smith, Solgaard, Dunn

12:00 – 1:00 lunch, poster session begins

1:00 – 2:15 Plasma, TED / Graves, Lieberman, Cheung, Aydil, Haller

2:15 – 2:45 CMP / Dornfeld

2:45 – 3:30 Education / Graves, King, Spanos

3:30 – 3:45 Break

3:45 – 5:30 Steering Committee Meeting in room 775A / Lozes

5:30 – 7:30 Reception, Dinner / Heynes rm, Men’s Faculty Club


3

Litho Milestones, Year 1 Demonstrate AFM aerial image inspection on 180nm features. Demonstrate Specular Spectroscopic Scatterometry CD

metrology for 180nm features. Demonstrate focus classification scheme for 180nm features. Complete 3D device simulations of mask errors and LER

effects in gate-level. Threshold voltage shifts, turn-off characteristics, and saturated drain current will be evaluated.

Complete a simulation feasibility study and verification experiment on novel in-lens filtering for resolution enhancement.

Evaluate the physical basis for novel effects in interaction of light with materials and low voltage electrons with resists.

Establish web based simulation capabilities for DUV resists, mask topography effects and electron-beam lithography.


4

Litho Milestones, Year 2 Demonstrate AFM aerial image inspection on 50nm features. Demonstrate 150nm Specular Spectroscopic Scatterometry CD

metrology. Demonstrate focus classification scheme for 150nm features. Test NMOS devices with programmed mask errors and LER,

compare measured characteristics to simulation. Integrate scattering, imaging, resist modeling for analyzing

inspection and printabilty of mask non-idealities in the context of use with OPC.

Establish a prototype system for process integration including the automatic generation of simulation-designed multi-step, short loop test structures.

Establish web based simulation capabilities for optical alignment and advanced electron-beam lithography.


5

Outline

• Simulation and Metrology– Lithography Simulator Calibration

– Scatterometry

– Plans for Statistical Process Optimization

• Line Edge Roughness• Lithography Simulation


6

Thin film Spin Coat&

Soft Bake

Exposure&

PEBDevelop

Thicknessn and k

Thicknessn and k

Thicknessn and k

CD, profile andThickness

In-situ / On-wafer thin film Metrology– Reflectometry / Ellipsometry / Scatterometry

– Thickness, n & k, chemical composition

– Run-to-run and real-time monitoring

– Resist surface analysis for aerial image evaluation


7

Motivation for Parameter Extraction

• Current lithography simulators are parameter limited as opposed to model limited.

• Traditional optimization techniques are unsuitable in complex, non-linear, high dimensional problems.

• Importance of predictive capabilities is increasing with increasing development costs and time-to-market pressures.


8

Some Critical Parameters in DUV Lithography Simulation

Amplification Rate (Pre-exp)Amplification Rate (Activation)Acid Loss Rate (Pre-exp)Acid Loss Rate (Activation)Dill’s A ParameterDill’s B ParameterDill’s C ParameterRelative Quencher Conc.PEB Diffusivity (Pre-exp)PEB Diffusivity (Activation)

Maximum Develop RateMinimum Develop RateDeveloper SelectivityDeveloper Threshold PACResist Refractive Index (Real)Resist Refractive Index (Imag.)ARC Refractive Index (Real)ARC Refractive Index (Imag.)Relative FocusAmplification Reaction Order

•Exact values obtained from experiments or resist vendor•Narrow range of values available from unpatterned experiments•Wide parameter range


9

Proposed DUV-SCAPE Framework

3: user specifiedparameter ranges

4: parameter interfacefront end

5: commercial simulation program

6: simulated profile

7: global optimizationengine (SAC)

2: image processingfront end

3: experimentalprofile

1: patterned resist experiments

1: unpatterned resist experiments

2: global optimizationengine (SAC)


10

Salient Features

• Unpatterned Resist Models– BCAM exposure and bake models

– Mack develop model

• Optimization Technique– Global optimization theory (Adaptive Simulated Annealing)

• Patterned Resist Model– Existing lithography simulators (e.g. SAMPLE, Prolith,

Solid-C, etc.)


11

Experiments - Commercial DUV Resist

• Unpatterned Resist Characterization Experiments– Process 4 wafers with flood exposed sites

– Measure ARC and Resist optical constants - Ellipsometry

– Measure exposure and PEB parameters - FTIR/DITL

– Measure develop parameters - DRM

• Patterned Resist Characterization Experiments– Process 1 wafer with a focus-exposure matrix

– Measure profiles for sub-quarter micron lines using AFM/cross-section CD-SEM/Specular Spectroscopic Scatterometry


12

Unpatterned ExperimentsD

epro

tect

ion 140C 135C

120C

110C

Exposure Dose (mJ/cm2)

Dev

elop

Rat

e in

A/s

ec

3000

2000

1000

0 0 0.5 1Normalized concentration of unreacted sites

Exposure+ PEB

Parameters

DevelopParameters

0 1 2 3 4 5 6 7

1

.5

0


13

Patterned Experiments: AFM vs Simulation

mask 1

mask 2

mask 3

mask 4

mask 5

-1 Focus +1 -1 Focus +1

Masks 1-10 differ in the line-space ratios

0.25 micron process technology

OPC assisted masks

mask 6

mask 7

mask 8

mask 9

mask 10


14

What is Scatterometry?

• Concept: Scattering (Diffraction) of light from features produces strong structure in reflected optical field.

• Analyze structure to obtain topography information.

• Periodic structures (gratings) can be numerically modeled “exactly”.

Incident LaserBeam

0th order

Incident PolarizedWhite Light

0th order

2- Scatterometry Specular Spectroscopic Scatterometry


15

Specular Spectroscopic Scatterometry0th order, broadband detection

1D gratings and 2D symmetric gratings

Use spectroscopic ellipsometersi 0

+1

-1

D

Cut-Off Pitch600 300400 200250 125 (in nm)

sinm = sini+m/D|sinm|<1


16

TimbreProfilerTM

LibraryGeneration

TimbreProfilerTM

Measurement

Timbre ProfilerTM Flow

Generate Profile Library

Generate Signal Library

Timbre ProfilerTM

ElectromagneticSimulationSoftware

Load Libraryon Ellipsometer

Ellipsometer / Reflectometer

Compiled Profiler Library

Test Grating (Scribe Lane)

CollectReflected Signal

Ellipsometry Measurement

Reconstructed ProfileTotal Measurement + Analysis = 5 seconds/site

Analysis

Compiled Profiler Library

Typical turnaround time = 6-12 hours


17

ProfilerTM Setup• Periodic grating on mask (~ 50 m * 50 m area - typical spot

size of production spectroscopic ellipsometers)– line/space specified

• Provide optical constants for each film in the stack– Broadband (240-800 nm)

• Specify variability expected in process (in CD & thickness)– range around nominal in nm

• Specify spectroscopic ellipsometer / reflectometer angle of incidence

• Save broadband tan and cos values

• Specify accuracy requirements– down to sub-nm (this automatically decides library size)


18

GTK Interface at http://sfr.berkeley.edu


19

Matching on tan() and cos()

Simulatedby GTK

Tan(

Cos(


20

Example of 0.25m Profile Extraction

Blue isactual (by Veeco AFM).Red isextracted from GTK Library.


21

Case I: Resist on ARC on Si (0.18 m technology)

Resist

ARC

Si

Focus-Exposure Matrix


22

Profile Extraction over the entire FEM

RED isAFM.

BLUE isextracted.


23

Offset between CD-SEM and ProfilerTM as a function of Sidewall Angle

bo

ttom

CD

(C

DS

EM

- P

XM

) in

nm

Sidewall angle in degrees


24

Case II: Resist on ARC on Metal (0.m technology)


Resist

ARC TiNAl

TiNTiTEOS

Si


25

Profile Extraction: Resist on ARC on Metal

CD-SEM (Bottom CD)

PXM (Bottom CD)

Correlation* = 0.93

CD

(in

nm

)

Site Number

Profiler Extraction


26

Case III: Etched Metal


AlTiN

TiTEOS

Si

TiN


27

Profile Extraction : Etched Metal

Profiler Extraction

CD-SEM (Top CD)

PXM (Top CD)

Site Number

CD

(in

nm

)

Correlation = 0.92


28

But What Is Our Real Goal? -- a good profile ?

-- or high yield ?• We cannot avoid process variations

– Recipe setting drift: focus ( ~0.2 m), dose, PEB temperature

– Model and material parameter variation: resist n & k, developer Rmax and Rmin, acid diffusivity

– System inherent variation: mask OPC feature variation

• Our goal is to maximize yield for the statistical distribution of parameters and operating points.


29

Parameter Variation Effect

Operating Point Settings

Pro

file

dev

iati

on f

rom

bes

t set

ting


30

Parameter and Operating Point Variances Extraction

Experimentdata

Recipe setting+ drift

Parameter mean+ variation

Lithographyprocess

In-die spatialvariation

Hierarchical process disturbance extraction


31

+-

RECIPEOPTIMIZER

Calibrated Lithography

Simulator

Simulated Output

distributions

Ope

rati

ng P

oint

dist

ribu

tion

s

Profileswithin spec.

Parameterdistributions

Spatialvariation

Overlapping to get yield

Recipe Optimization with Variations


32

Recipe Optimization with Multiple Feature Types

Poly layerisolated lineperiodic lines with OPC

metal layerisolated lineperiodic lines with OPCelbowscombination of above

Need to link recipe optimization to circuit performance!


33

Parameter relationship analysis

• In reality, all parameters have variations– too many dimensions for output distribution calculation

• Parameter relations can be analyzed to attribute the variation of some parameters to other parameters– diffusivity PEB temperature

– developer temperature Rmin and Rmax

• What are the fundamental reasons behind the variation?– Need a comprehensive list of disturbances, linked to physical

models, circuit performance.


34

ExperimentData

Spatial variation filter

Param. & op.point variance

Param. mean values

Calibrated Sim. Eng.

Target Specs. of features

In-line sensor measurement

Recipe of max. yield

Maximization of overlapping area

Summary


35

What is Next?

• Extend statistical optimization to other process steps– Plasma etching

– Metallization

– Device level

– Circuit level

• Process simulator for other steps needed– Simulator for full process procedure: Avant!, Solid C

– device model: BSIM3

– Circuit simulator: SPICE

• Study error budgets, linked to circuit performance.


36

Outline

• Simulation and Metrology• Line Edge Roughness• Lithography Simulation


37

Defining LER and Defect Specifications

SFR Workshop

November 08, 1999

Tho Nguyen, Shiying Xiong and J. Bokor

Berkeley, CA

The objective of this work is to understand and model the impact of lithography/etch line-edge roughness in the gate definition layer, on the electrical behavior of short channel

transistors


38

Progress Since May

• Hydrodynamic Model working

• 3D interaction of Defects

• Real LER Simulation


39

gate

n+ n+Cross-section

Layout views

Edge roughness

Single defects

Effect of Gate “Errors” on Device Characteristics

W

L

Threshold voltageTurn-off slopeDrive currentDevice reliability


40

Base Design Channel Doping Selected at 0.4 Volt Halo Implant Incorporated to Offset Vt rolloff Threshold Swing 70-80 mV/decade @ Vds = 2V and L = 100nm DIBL = 70 mV/V for Vds = 0.05-2V

250

300

350

400

450

500

0 0.2 0.4 0.6 0.8 1 1.2

Vt RollOff Characteristics

Without Halo ImplantWith Halo Implant

Channel Length (Microns)

Device Length = 200 nmChannel Length = 100 nmChannel Width = 50-200 nmBuried Oxide = 100 nmSi Film Thickness = 250ÅGate Oxide = 30 Å


41

160

Real 3D LER Construction and Simulation

• Real 3D LER Created by Matlab and incorporated into simulator language

• LER defined by band-limited white spectrum. 2 parameters: RMS roughness, correlation length

• Process simulation used for self-aligned S/D doping

• Current digitized LER resolution is 0.5-1nm due to limited memory


42

Simulation Results• Hydrodynamic model has been

successfully turned on in ISE simulator

• With hydro on, Ion is ~ 30% higher• Simulations of “real” 3D LER has

been successful ( @ W = 50nm) Zoom View of Leakage Current

I_V Curves for Different Real 3D LER

25 % increase in Ioff for 5nm rms roughness

140% increase in Ioff for 9nm rms roughness


43

Simulation Results• Defect shows 3D interaction for channel width

less than 100nm• To study LER, we have to use 3D models • Intel Work (T. Linton, et al. 1999):

• Simulation of square-wave modulation of LER with Neuman boundary conditions

• Shows similar 3D interaction

• Leakage control by length adjustment with reasonable Ion reduction 2 10-9

3 10-9

4 10-9

5 10-9

6 10-9

7 10-9

60 80 100 120 140 160 180 200 220

Ioff Varies With Channel Width

Ioff (No Defect)

Ioff(20nx20n Defect)

Channel With (nm)

0.00066

0.00068

0.0007

0.00072

0.00074

0.00076

60 80 100 120 140 160 180 200 220

Ion Varies with Channel Width

Ion (No Defect) [A/um]Ion(20nx20n Defect)

Channel With (nm)


44

Milestone Status

• June 1999

– Complete 3D device simulations of mask errors and LER effects in

gate-level. Threshold voltage shifts, turn-off characteristics, and

saturated drain current will be evaluated.

– Status: Late. Student (Tho Nguyen) started Jan. 1999. Second student

(Shiying Xiong) started Sept. 1999. Expect completion March 2000.

• June 2000

– Test NMOS devices with programmed mask errors as well as varied

LER and compare measured characteristics with simulation results.

– Status: Delayed. No company fab support. Will start Microlab run

Jan. 2000 if unable to arrange support from company fab.


45

Proposal for 2000-2002

Simulation• Effect of LER on GIDL• Effect of LER in isolation edge• Device reliability• Extend to 50 nm CD

Experiments• Complete gate roughness experiment for 100 nm CD• Isolation roughness experiment• Extend to 50 nm CD??


46

Outline

• Simulation and Metrology• Line Edge Roughness• Lithography Simulation


47

Implications of Polarization, Corner Rounding, OPC Design and OPC

Fidelity on Aerial Images

Konstantinos Adam

Prof. Andrew Neureuther UC Berkeley

• Use EM theory and rigorous TEMPEST simulations to investigate photomask technology issues• Current Investigations

• scattering bars - polarization effects• corners - interior versus exterior • OPC features - placement and corner rounding


48

Scattering Bar Simulation with TEMPEST

m

mm

m

TE : Ey polarization

TM : Ex polarization

CDSB

x-axis

z-ax

is

Incident radiation

y-axis

CDtarget=130nmMag=4X=193nm

|Ey|

|Ex|


49

SB Aerial Images

(m)

Nor

mal

ized

Int

ensi

ty=193nm, NA=0.7, =0.6, Mag=4X, CDtarget=130nm

Aerial Image (Best focus)

- Observe that the scatter bars (also the main feature) appear wider in TM excitation than in TE and narrower with SPLAT simulation (scalar theory)

0 0.1 0.2 0.3 0.4 0.50

0.2

0.4

0.6

0.8

1

1.2

1.4 SPLATTETM

No SB

SB size = 0.18/NA


50

SB Design Graphs

Size of SB (/NA)C

D (

nm)

Size of SB (/NA)

Inte

nsit

y

0 0.05 0.1 0.15 0.2 0.25 0.3 0.350

.2

.4

.6

.8

1SPLATTETM

Perturbation model

Intensity dip of SB

0 0.1 0.2 0.3110

120

130

140

150

160 SPLATTETM

CD Control with SB Size Control


51

Square

m

m m

m

Rounded

Corner Rounding (Clear Field Mask) - |Ey| Near fields

x-axis

y-ax

is

Ein

cide

nt (

TE

)

Ein

cide

nt (

TE

)

CDtarget=130nm

Mag=4X

=193nm


52

Corner Rounding Design Graph

0 0.04 0.08 0.12 0.16 0.20

2

4

6

8

10

radius of curvature in /NA

LE

S in

cre

ase

fro

m r

efe

ren

ce in

nm

Clear field mask

Dark field mask

- LES increase versus radius of curvature is quadratic, i.e. it is proportional to the area missing from the corner due to the roundness


53

External OPC – |Ey| Near Fieldsm

m m

m mm

Reference Square OPC “Mouse Ear” OPC

Example: 0.1/NA Square OPC and “Mouse Ear” OPC with radius=0.06/NA


54

OPC Design Graph

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

5

10

15

20

25

non-overlapping area in m2 (1X)

LE

S c

orr

ectio

n in

nm

x10-3

Square OPC

“Mouse ear” OPC

Data for OPC displaced along the diagonal


55

Resist modeling, Simulation and Line-End Shortening effects

Mosong Cheng

Prof. Andrew Neureuther, UC Berkeley

Use experiment and simulation to investigate photoresist performance and provide mechanism based models, characterization methodology, accurate profile simulation and support models/fast algorithms for including resist in OPC

Current investigations•chemically amplified resist modeling - LES and SFR K2G•electric-field-enhanced post-exposure bake •fast imaging algorithm for 2-dimensional OPC


56

Resist-model-based line-end shortening simulation• APEX-E , UVIIHS, K2G parameter-extraction methodology

• Simulation flow

Problem: Top to Top underestimates diffusionProblem: Micro-stepper at Berkeley has insufficient image quality


57

K2G resist: DRM curves and reaction/diffusion/outgasing model

• DRM curves, dissolution rate is lower at the top if no TARC.

• Reaction/diffusion/outgasing model

(x)CK- ).(

)1(

asC0

ae2

1

eDD

CKCDt

C

CCKt

C

aaa

maas

as

Collaborationwith Jacek TyminskiNikon


58

K2G resist: modeling and simulation• Modeling methodology

Large-area exposure

Extracting

reaction rate

Extracting dissolution parameters

Fitting with DRM data

Extracting diffusivity

Resist profile simulation

• Fitting DRM curvesK2G without TARC

0

2

4

6

8

10

12

14

16

18

0 200 400 600 800z-Position [ nm ]

Dev

elop

men

t Rat

e [ n

m/s

ec ]

Simulation fordose6.7mJ/cm^2

DRM curvefor dose6.7mJ/cm^2

• Resist profile simulation


59

Electric-field-enhanced post-exposure bake

• Goal: shorten PEB time, improve vertical resist profile uniformity, reduce lateral acid diffusion.

• Principle: vertical electric field enhance the vertical movement of photo-acid, hence enhance the reaction cross-section. PEB time as well as lateral acid diffusion can be reduced.

• Experimental Setup

Hotplate

Al foilwafer

Al foil

Resist Ephotoacid


60

Electric-field-enhanced post-exposure bake: status

• Experiment done in summer 1999, on UVII resist using JEOL.

• UVII resist, 0.5µm L/S, dose 20µC/cm2, PEB with 100kHz, 3.3V AC, 140oC, 60sec.

• UVII resist, 0.5µm L/S, dose 20µC/cm2, nominal PEB,140oC, 90sec.

RESIST RESIST


61

Fast resist imaging algorithm for 2-dimensional OPC(submitted to SPIE’99)

),(),,( gft

ggf

t

f

• Assume 2-D reaction/diffusion. Let f(x,y,t)=Cas(x,y,t), g(x,y,t)=Ca(x,y,t).

• Time-advancing scheme

factor relaxation:,,2

2)),,(),,,((.,

2

2)),,(),,,((.

,

)0,,(),,(,)0,,(),,(

222222

212

212

11

221

221

dddccct

tddtyxgtyxfd

t

tcctyxgtyxfc

t

gd

t

fc

tdtdyxgtyxgtctcyxftyxf

• Iterative solve c2,d2, to minimize the error E. 221

221 )2()2( tddtccE

Contains Spatial Laplacianand Uses 3rd Order Splines

Based on NT Aliasing and NL Relaxation

Very Fast as only requiresrepeated multiplication with fixed coefficients


62

Fast resist imaging algorithm: simulating flow and tuning parameters

• Simulating and tuning flow:

Mask pattern SPLAT

aerial image

Resist imaging

resist profile

SEM picture

DifferentialResist

parameter tuner

• Extract resist parameters by tuning the image to fit with SEM picture.

Method of FeasibleDirection


63

Progress on Milestones

• Year 1– simulate in-lens filtering (Done)

– resist exposure mechanisms (Not Started =>DARPA/SRC)

– web simulation resist and mask effects (In Progress 70%)

• Year 2– Integrate scattering, imaging and resist (Expanded by 3X in

the number of effects characterized, In Progress 70%)

– process flow generator for test structures (Not Started)

– web alignment and e-beam (alignment Ongoing 30%, e-beam Not Started => DARPA/SRC)


64

Future Opportunities in Lithography

• Photomask EM effects (How to move faster?)– impact of non-idealities

– inspection and repair

• Chemically-Amplified Resists– models that work

– methodology to calibrate models for production

• Optical Systems– high NA

– low k1


65

Targeted Opportunities in Photomasks and Optics

• Attenuating phase-shifting masks– high refractive index and physical height of the attenuating

material adversely influences light in adjacent areas

• Alternating phase-shifting masks– 3D problematical structures - resonate ridges and cross-talk

between features inside the photomask

• Phase-shifting mask repair– guidelines for adequate repair - height, slope, river bed,

stain• Optics

– role of laser bandwidth in image quality– high NA thin-film polarization effects


66

Targeted Opportunities in Resists and Tools

• Complete comparison of Simulation and SEM's of printed features in K2G resist, quantify the accuracy of the resist model.

• Complete coding of the fast but approximate image processing like algorithm and assess speed and accuracy against rigorous simulation in STORM.

• Initiate tool-process-dependent line-end shortening investigation by identifying key factors contributing to line-end shortening and suggesting approaches for control and compensation tuning.

11/8/99 SFR Workshop - Lithography 1 Small Feature Reproducibility A Focus on Photolithography...

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