Optimizing Processing Parameters of Direct MetalLaser Deposition for Porosity Reduction of Thin Film

TiB2+AlMgB14 on High Carbon Steel Tracks

Prepared by:Mackenzie J. Ridley

Back to the Future Research Experience for UndergraduatesNational Science Foundation Grant NSF DMR-1460912

Research Completed Under the Supervision of:

Dr. William Cross, Associate Professor Materials and MetallurgicalEngineering

Dr. Michael West, REU Site Director, Department of Materials andMetallurgical Engineering

Dr. Alfred Boysen, Professor, Department of Humanities

South Dakota School of Mines and Technology

August 2016

Contents

1 Abstract 4

2 Introduction 52.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

2.2 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2.3 Broad Impact . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

3 Procedure 83.1 Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

3.2 Equipment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

3.3 Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

3.3.1 Sample Preparation for Direct Laser Deposition . . . . . . . . . . . . . . . . . . . . . 9

3.3.2 VDK 3000 Direct Laser Deposition . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

3.3.3 Sample Preparation for Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

3.3.4 XRadia MicroXCT 400 Scanner . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

3.3.5 Avizo Imaging Software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

3.3.6 Buehler Micromet 4 Microhardness System . . . . . . . . . . . . . . . . . . . . . . . 12

3.3.7 Scanning Electron Microscope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

4 Results 144.1 XRadia-400 Micro-computed Tomography . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

4.1.1 X-Ray Attenuation Density Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

4.1.2 Artifacts and Manual Reconstruction . . . . . . . . . . . . . . . . . . . . . . . . . . 16

4.1.3 Avizo Modelling Software for Porosity Separation . . . . . . . . . . . . . . . . . . . 17

4.2 Microhardness Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

4.3 Scanning Electron Microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

4.3.1 Energy Dispersive Spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

5 Discussion 23

6 Conclusion 256.1 Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

2

7 Acknowledgments 27

A Steps for Porosity Analysis 28

B XRadia MicroXCT Computed Tomography Quick Reference Guide 29

Bibliography 31

3

Chapter 1

Abstract

Many of today’s industrial abrasives, blades, and cutting tools are composed of or protected by layers of a

protective thin film. Often a thin film is a diamond coating, which because of its high cost and increased oxidation

at high temperatures, can be deemed unsuitable for some industrial fields. Certain ceramics, such as metal

borides, and in the case of this study, aluminum magnesium boride (BAM), provide cost effective thin films

with adaptive qualities depending on the synthesis. In the case of the ceramic alloy BAM, qualities consistent

of high microhardness, a low coefficient of thermal expansion, and a very low coefficient of friction can be

synthesized. Research studies for stronger industrial tools that wear less over time will continue to grow and

adapt as we understand more about various material properties. The study of thin film ceramic alloys deposited

on steel tracks to model industrial equipment can allow for useful industrial upgrades without replacing working

tools entirely. To better understand how various parameters affect the characteristics of BAM stated above, the

processing parameter laser power will be adjusted to study gas and powder pore amounts within the deposited

thin films.

4

Chapter 2

Introduction

2.1 Background

Application of thin films was accomplished through a technique called direct laser deposition (DLD). After

being introduced in the early 2000s as an outcome of the additive manufacturing industry, laser deposition of

materials has provided a cost efficient and effective method to equipment repair, creation of unique parts, and

precision placement of thin films of materials. A powder alloy is fed through gas-filled tubes onto the base

object. A high powered laser strikes the surface of the base object, causing point precision fusion of the base and

clad material. Given the short amount of time that the laser is focused on a particular area, and the concentrated

area being heated, a point on the metal cools rapidly and maintains shape. This study will use a combination of

BAM, titanium diboride, and Inconel 625 nickel alloy as the powder for deposition.

Aluminum magnesium boride is unlike many ceramic alloys, in its makeup and in properties. While most

superhard alloys often consist of a simple atomic structure, BAM has a complex orthorhombic structure with 64

atoms per unit cell [1]. The true ratio of the compound is Al0.75Mg0.75B14, although for simplicity BAM is

often referred to as a stoichiometric alloy, Al1Mg1B14 [2]. Using BAM in superhard thin film coatings is a step

towards application of other complex and unlikely alloys in the DLD process, which can provide a new range of

characteristics for thin films use.

The addition of titanium diboride with AlMgB14 can promote a higher microhardness, ranging from 28 – 51

GPa [2]. TiB2 also acts an adhesive to bond the ceramic alloy BAM with the steel track [3]. This addition is

what promotes BAM to being a part of the superhard alloy classification. In proper proportions, TiB2+AlMgB14

can exhibit a coefficient of friction as low as 0.04; a “self-lubricating” nature slicker than that of Teflon [1].

BAM’s low thermal coefficient of thermal expansion and its high melting point make it a desirable coating for

many steel instruments of the manufacturing industry. In the case of this study, a combination of Inconel 625

nickel powder alloy also allows for a better formation of the BAM powder to base 1095 steel track. Because of

its high tensile strength and very strong resistance to corrosion, the nickel alloy can possibly prevent splitting

between the steel track and the deposition region [4].

5

2.2 Objective

Through application of BAM onto high carbon steel, a material typical of industrial cutting and abrasive equip-

ment, characteristics of future BAM coated tools can be predicted. Direct laser deposition will be used to

apply thin film BAM coatings to the steel tracks, with the parameter studied being laser power of the direct

laser deposition process. Parameters such as deposition speed, powder flow rate, and gas flow rate were left

constant. Parameter analysis of laser power on TiB2+AlMgB14 thin films will be performed to optimize hardness,

strength, and longevity of the applied steel tracks. These characteristics will be measured through minimizing

porosity within each samples’ deposition region. Micro-computed tomography (micro-CT), microhardness

testing, electron microscopy, spectroscopy will be performed on the samples to achieve the objectives in this study.

Through research of the laser deposition process, some hypotheses were formulated before experimentation.

The first hypothesis was that as the laser power increases, average pore size and overall porosity fraction of

each sample will decrease. This is due to the ability for gas pores to have longer times to escape the deposition

region before the melted alloy finishes its phase change back into a solid. Second, any powder porosity will

also decrease as laser power increases, due to an increase in temperature over the BAM and Inconel 625 nickel

alloy melting points. The third hypothesis was that laser power and microhardness would show a positive

relationship, given that microhardness was predicted to increase as internal and surface porosity were minimized.

The final fourth hypothesis was that a second deposition scan over the first deposition would show another level

of decreased porosity in the samples. Remelting the thin film area could provide another chance for trapped

pores to escape the melted region before hardening, as well as increasing the deposition height for a stronger

BAM thin film coating.

2.3 Broad Impact

When combined with titanium diboride, BAM becomes a superhard alloy with a microhardness of up to 51 GPA

[2]. While diamond is still harder, we see the cost of this ceramic alloy dramatically cheaper. This makes BAM

a worthwhile investment in coating of special equipment in industries that require high strength, self-lubricating

properties, and most importantly, cost efficient parts and parts repair. The thin film application of BAM can

introduce longevity and strength without completely adapting how machines run and operate. Companies will

be allowed opportunity to increase their output and processes with no more work than to have their blades and

abrasives coated with thin film such as in Figure 2.1. Optimization of the processing parameters will provide

industrial businesses the luxury of determining exactly which characteristics newly coated equipment should

have, depending on its functionality in the workplace.

Beyond the industrial impact of direct laser deposition, the ability to create rapid prototypes allows for

research such as this to occur, where many samples are needed for comparison. Through research, we are

attempting to create and identify objects with desired characteristics, such as high microhardness, low porosity,

and uniform microstructure in this case study. Additive manufacturing has allowed for adaptation in a wide

variety of processing parameters to even allow the creation of functionally graded parts, where the characteristics

of the deposited region changed with each deposition layer [5]. A question asked when starting the DLD process

was, “What parameters will have the greatest effect on the desired characteristics of our final product?” Through

studying previous research and personal hypothesis, seven major processing parameters were determined to

effect sample characteristics: laser power, laser beam diameter, powder mass flow rate, deposition speed, laser

6

Figure 2.1: VDK 3000 Direct Laser Deposition - SDSMT

beam height, gas flow rate, and deposition atmosphere [5]. Laser power will be the only processing parameter

researched as a variable in this study.

7

Chapter 3

Procedure

3.1 Materials

Table 3.1: Materials List

Material Powder Particle Size (Micron) Melting Point (C) Microhardness (GPa) Density (g/cm3̂) Powder Weight %

TiB2+AlMgB14 44 – 106 TiB2 (2970) AlMgB14 (2000) 28 - 50 3.14 80%

Inconel 625 Nickel 44 – 106 1290 - 1350 13 - 24 8.44 20%

1095 Steel N/A 1515 3.03 7.87 N/A

1095 high carbon steel is often used in blades and other cutting tools. This type of steel was chosen

because of its high hardness, toughness, and low tensile strength. To properly model abrasive instruments, the

steel track has a thin width of 650 microns, with square edges to provide a uniform melt pool during laser contact.

The powder particle size of TiB2+AlMgB14 and the Inconel 625 nickel alloy were both consistent within

a range of 44 - 106 microns in diameter. The powder has an even distribution of pore sizes found within the

entire powder mixture. This information was provided by the manufacturer, and was not tested for accuracy.

The melting point of the TiB2+AlMgB14 was unknown, given that this value depends on exactly how much

titanium diboride was added to the BAM powder. This was proprietary information, and was not available at

time of research. The percent composition of TiB2+AlMgB14 will also determine how high the microhardness

was, within a range of 28 - 51 GPa. Even while the TiB2+AlMgB14 composition percentage was proprietary, an

80% - 20% ratio of TiB2+AlMgB14 and the Inconel 625 nickel alloy were mixed to produce our final powder for

deposition. All powder mixing was completed by the laser deposition system.

The percent weight composition of Inconel 625 nickel alloy is displayed in Table 3.2 [4]. The known

elements will be traced using EDS analysis on the final thin film depositions.

8

Table 3.2: Inconel 625 Nickel Alloy Chemical % Composition [4]

Nickel 58.0 min Niobium (Plus Tantalium) 3.15 - 4.15

Carbon 0.1 max Molybdenum 8.0 - 10.0

Manganese 0.5 max Aluminum 0.4 max

Iron 5.0 max Titanium 0.4 max

Sulfur 0.015 max Phosphorous 0.015 max

Silicon 0.5 max Cobalt 1.0 max

Chromium 20.0 - 23.0 Total: 100%

3.2 Equipment

The following instruments were used to construct, prepare, and analyze thin film deposition samples. A proper

explanation of to the following will be discussed in the Procedure; VDK 3000 Direct Laser Deposition System,

XRadia MicroXCT 400 Scanner, Buehler Micromet 4 Microhardness System, and Zeiss Supra 40VP Scanning

Electron Microscopy System. Secondary equipment used included a Leco mounting press, diamond blade

precision saw, and a standard polishing station.

3.3 Procedure

The procedure listed below provides detailed instructions on the processes found in Figure 3.1.

3.3.1 Sample Preparation for Direct Laser Deposition

Preparation of the sample tracks involved first cutting two tracks of length 350mm. This was to provide 30mm

deposition area for seven samples, with 20mm spacing between each deposition. One track would be for seven

single layer deposition samples, while the other was for double layer depositions under the same processing

parameters. Tracks were then wiped down with Methyl Ethyl Ketone (MEK) to remove debris and oil, and then

blasted with an air gun.

3.3.2 VDK 3000 Direct Laser Deposition

Direct laser deposition is a form of additive manufacturing, mainly used for localized addition of alloys to current

items or repair of equipment. Figure 3.2 shows an industrial laser beam concentrated on a very small sample

area. The beam creates a melt pool on the base material. A precise amount of a powder alloy is fed onto the melt

pool via some gas to prevent oxidation of powder material. In this case, Argon gas is used as a shield for the

powder. As the powder and base material melt together, a thin layer is deposited, increasing the height of the

base material and creating a small transition region, or dilution area, between the powder and the base material.

The beam is quickly moved to the next location for deposition, and a phase change almost instantly brings the

melt pool back to a solid connection between the base material and the clad region [6].

Once a sample was placed into the DLD chamber, MatLab was used to control general alignment of the

sample and laser, as well as correctly establishing desired processing parameters. Precise alignment of the laser

beam and the sample track proved difficult, since the clamp to hold the steel track could be moved with a light

9

Figure 3.1: Procedure Flow Chart

Figure 3.2: Direct Laser Deposition Schematic [7]

tap of a hammer. A visual camera aid was used ensure deposition occurs on the tracks. Titanium diboride and

aluminum magnesium boride powder were mixed at a proprietary rate, although 20% powder concentration was

chosen to be Inconel 625 nickel alloy as a bonding agent to the base material as stated in Table 3.1. Each 30mm

section of the deposition received an increase in around 15 Watts of laser power so that the laser power ranged

from 88.0 Watts to 179.0 Watts.

10

3.3.3 Sample Preparation for Analysis

The tracks were cut using a precision diamond blade saw, leaving only the 30mm deposition areas. From these

samples, 6mm length pieces of the tracks were removed for sampling. The new 6mm samples were then mounted

in bakelite using a Leco mounting press. Samples were mounted in order to display the thin width of the samples,

showing a small deposition bead on top of the steel tracks. Mounted samples were polished to 1200 grit, and then

to 3 micron using diamond suspension pads. It should be noted that polishing was not necessary for micro-ct

analysis.

3.3.4 XRadia MicroXCT 400 Scanner

Computed tomography relies on taking single 2-Dimensional images at multiple angles around an object. Figure

3.3 shows an object placed on a rotating plate, and images were taken with an x-ray source and detector on

each side of the sample. After a desired number of angles were imaged, a reconstruction process placed all

2-Dimensional images on a single plane of reference. A computed 3-dimensional grey scale model of the sample

was created through many reconstruction algorithms. The various intensities of the x-rays travelling through

a sample provided precise visuals of what the object looks like, both externally and internally [8]. Micro-ct

scanning can achieve resolutions of under 1 micron per voxel; a cubic pixel volume. Filters were then added to

the reconstruction process to further enhance the visualization of an object, and to remove any errors occurring

in the image acquisition process.

Figure 3.3: Micro-CT Schematic [9]

Micro-computed tomography involved first updating the current user manual guide that was present. This

update can be found in Appendix B. Samples were scanned at 4X with 140kV at full power. Each micro-ct scan

was tailored to have a pixel size of 4.55 microns/ pixel. Single image acquisition for each scan was viewed best

quality at 13 seconds, resulting in a 9 hour full scan on average. Manual reconstruction of the 2-D x-ray images

11

were then performed to remove any visual artifacts created during the automatic reconstruction process.

Using a single 2-dimensional image of each sample, a vertically oriented histogram was created to display

x-ray intensity attenuation from air, bakelite mounting material, TiB2 + AlMgB14 deposition region, and through

the 1095 steel track. Normalization of the histograms were used to provide insight in uniform deposition of the

BAM by determining the deposition region density. Sample densities can be adapted into experimental porosity

percentages for each laser power used.

3.3.5 Avizo Imaging Software

Digital 3-D images of the mounted samples were transported to imaging software, Avizo. The goal with Avizo

was complete porosity separation from the full material. The general process that was found best for image

segmentation of porosity was provided in Appendix A.

3.3.6 Buehler Micromet 4 Microhardness System

Microhardness testing was useful when working with very small or thin parts of almost any material, as well

as measuring microstructures and changes in hardness of a material [10]. Vickers hardness testing (VH) was a

common method of microhardness testing, and was easily converted to other units of hardness measurement.

Figure 3.4 shows a small diamond indenter, with the opposite faces being 136 degrees, was pressed into a

mounted material by a direct load being placed above the indenter. This load can range from a few grams to many

kilograms, depending on the hardness of your sample and how large of an indentation desired. The diameter of

the diamond indenter points are measured under a microscope to provide a Vickers hardness value for a given area.

Figure 3.4: Vickers Microhardness Diamond Pyramid Indentation [11]

While microhardness testing is widely used in many research and industrial fields, the process has received

the titles of “time-consuming” and “finicky" [10]. Operator error is common when sampling, due to simply

choosing the correct widths of the diamond indenter diameters by line of eye. For lighter loads, a smaller

12

indentation is created and can lead to a greater risk of accruing error in the results. Sample preparation was key

to minimizing operator error, as a polished sample can provide easier visibility of the indenter points than a

sample covered with small scratches and debris.

Microhardness testing was performed from the edge of the deposition region down through the transition

region to the pure 1095 steel track. This way, the sample with the highest microhardness can be found, as well as

an understanding of how the transition region was affected by a change in laser power.

3.3.7 Scanning Electron Microscope

Scanning electron microscopy (SEM) shoots high energy electrons at the surface of a specified material enclosed

in a vacuum chamber, as seen in 3.5. The transfer of energy was measured for the surface material, and excited

electrons on the material surface produce information such as high resolution topography, surface element compo-

sition, and microstructure. Image magnification for SEM can range from 10X to up to 30,000X for some systems.

Scanning electron microscopy was used to see high magnification images of the deposition surface and the

surface porosity occurring. An energy dispersive spectroscopy (EDS) analysis of elements was completed to

confirm uniform mixtures of alloys, and detect any impurities found within the sample and sample pores.

Figure 3.5: SEM Schematic [12]

13

Chapter 4

Results

4.1 XRadia-400 Micro-computed Tomography

4.1.1 X-Ray Attenuation Density Analysis

Figure 4.1: Sample 7 (179.0 Watts) Normalized X-Ray Attenuation Histogram

Using normalized x-ray intensity attenuation histograms from the micro-ct such as the histogram seen in

Figure 4.1, values associated with the 1095 steel can be defined as the steel’s true density, 7.87 g/cm3, and

normalized intensities of air can be assigned as 0.0 g/cm3. The actual density of air at 3200 feet was found

to be 1.225x10−03 g/cm3, although for simplicity this was defined as 0.0 g/cm3 [13]. Assuming a linear

relationship between densities, the deposition area density can be defined as a density along the newly scaled

linear relationship made from the air and high carbon steel.

14

Table 4.1: Density Calculation of Clad Region

Laser Power (Watts) Known Density g/cm3 Experimental Density g/cm3

Air Steel TiB2+AlMgB14

88 0 7.87 3.112

103 0 7.87 3.104

118 0 7.87 3.12

133 0 7.87 3.128

149 0 7.87 3.112

164 0 7.87 3.112

179 0 7.5 3.111

Experimental density of the clad region consistently appeared lower than that of the known density of TiB2

and BAM, 3.14 g/cm3 in Table 4.1. A combination of 20 percent Inconel 625 nickel alloy, which has a density of

8.44 g/cm3, should promote a consistent value above 3.14 g/cm3 for each sample. Given that the percentages of

titanium diboride and BAM are proprietary and the density of the used powder was unavailable, the assumption

that 3.14 g/cm3, the density of BAM, was a reasonable density for the area will be used. The difference between

the known and experimental densities can contain operator error, but mainly this represents the effect of the

porosity that was now occurring inside the deposition region. the internal and surface pores allow for a lower

density to be determined through the x-ray attenuation method.

Using the equation 4.1, the porosity can be determined from a normalization of the known and experimental

densities.

Porosity = 1− ρExperimental

ρKnown(4.1)

The density calculations from micro-ct scanning now provide an experimental value for the porosity fraction

percentage within each sample, as seen in Figure 4.1.1. Found percent porosity will be compared with the

porosity fraction percentages determined through the Avizo 3-D Imaging Software.

Figure 4.1.1 may appear to have an error in the Known density of steel, where sample 7 at 179.0 Watts

displays 7.5 g/cm3. The values for density were derived directly from their x-ray intensity values. For samples

1 - 6, all steel samples received almost the exact same x-ray attenuation values. Sample 7, even after multiple

attempts to achieve the intensity that corresponds with 7.87 g/cm3, was determined to have a density of 7.5

g/cm3. While the data for sample 7 could easily be overwritten to the correct density of 1095 steel, the research

completed this summer was unable to uncover why the intensity values produced a varied density here.

We can see that in Figure 4.2, sample 4 (133.0 Watts) contains the least amount of porosity within the

deposited region, at only 0.39%. This was followed by sample 3 (118.0 Watts) by a 0.24% higher porosity of

0.63%. Other samples hold porosity percentages closer to 1%. This directs attention to a laser power of 118

15

Table 4.2: Porosity Fraction from Micro-CT Intensities

Laser Power (Watts) Experimental Porosity Fraction %

88 0.91

103 1.14

118 0.63

133 0.39

149 0.89

164 0.9

179 0.91

Figure 4.2: Porosity Percentage for Changes in Laser Power

Watts - 133 Watts as an optimum laser power for application of BAM thin films.

4.1.2 Artifacts and Manual Reconstruction

Given current settings of the XRadia 400 micro-ct scanner, the samples were automatically reconstructed with

various artifacts. Artifacts form from various errors in the reconstruction of the 3-D image. The noise found

through micro-ct normally comes from the summation of large groups of intensity values that should all resemble

the same value [14]. Throughout the imaging process, found artifacts in the deposition samples included: streaks,

rings, and a ghosting effect of mirrored samples.

Streaking artifacts were visibly distinctive straight lines in an object. Streaks can occur at various widths,

and are caused by a single inconsistency in scanning an image, such as from an area with a high change in

densities [14]. Streaks can be seen horizontally placed on the 2-D ortho slice images of Figure 4.3 B and 3-D

rendering of Figure 4.3 A.

A common artifact noticed in all scans was the occurrence of rings, forming on both the top of the sample

16

Figure 4.3: A: 3-D Render of Found Artifacts, B: Cross-section of Deposition Artifacts, C: Internal RingArtifacts

and internally within the clad region as seen in Figure 4.1.2 C. Rings generally occur from a single error in the

calibration of the detector, which was then carried through to each 2-D x-ray image [14].

A ghosting effect originally made our samples very difficult to interpret. This was the separation and mirror-

ing of an image, creating an overlap distortion. Ghosting allowed for larger sources of error, such promoting

more streaking and ring artifacts to occur. In the XMReconstructor Software, the overlapped images were moved

back together after comparing many images of a proper manual center shift value. In all samples, a center shift

around 69 microns corrected the reconstructions of the ghosting effect and removed many rings. Incorporating a

new low filter ring removal removed the rest of the occurring ring artifacts.

When x-rays are travelling through the center of an object, a larger proportion of low energy photons are

absorbed than high energy, thus creating areas of high intensity within the sample [14]. This is referred to as

beam hardening. Incorporating a beam hardening coefficient of 0.3 through 1.2 into the reconstruction algorithms

allowed for a removal of the streaks within the sample. Addition of a beam hardening coefficient also created a

clearer image along boundaries of large density change.

4.1.3 Avizo Modelling Software for Porosity Separation

Once each sample was uploaded to Avizo software, a 3-dimensional render can be produced of the reconstructed

ct scans. Using various parameters and filters established in Appendix A, areas of varying density can be

separated from the reconstruction as a whole. Separation of pores from the deposition creates an opportunity

to compare volumes of porosity to full volume of the sample. Porosity fraction was analyzed to find which

sample has the least amount of porosity. The porosity percent values found can be compared to the previous

experimental porosity fraction found through equation 4.1.

Pores were relatively close to surface, and maintain similar size; powder porosity was greatest here. Figure

17

Figure 4.4: Left: Sample 1 Porosity Separation, Right: Sample 6 Porosity Separation

4.4 Left had the largest pores, but also appeared to contain the least number amount of pores within the deposition

region. Figure 4.4 Right shows an increase in pore counts throughout the deposition region. Surface roughness

can be seen to visibly increase as laser power increases, given the noticed increase in surface porosity.

Table 4.3: Avizo Porosity Fraction Analysis*

*Sample Analysis may not be accurate due to curvature in steel tracks before depositionDLD Laser Power (Watts) Porosity Volume (mm3) Total Volume (mm3) Total Porosity % Porosity % From Calculated Density Mean Pore Radius (Microns)

88.0 1.06E+07 1.11E+09 0.957 0.91 37.84

103.0* 1.25E+07 1.47E+09 0.85 1.14 18.82

118.0 7.59E+06 1.25E+09 0.605 0.63 30.45

133.0 1.26E+07 1.35E+09 0.928 0.39 25.85

149.0 1.81E+07 1.37E+09 1.326 0.89 27.53

164.0 1.26E+07 1.17E+09 1.077 0.9 30.81

179.0* 7.61E+06 2.04E+09 0.374 0.91 21.14

Table 4.3 provides a comparison of the porosity percentages for both Avizo calculated porosity fraction

and the experimental x-ray attenuation calculation. While the agreement is generally acceptable, a noticed

discrepancy was seen on sample 4 of 133.0 Watts. This was originally predicted as the optimal laser power for

minimal porosity, although through the Avizo analysis, a 0.538% increase in porosity was noticed.

4.2 Microhardness Testing

Microhardness testing was completed from a starting point at the deposition edge, and analyzed vertically

at increments of 20 microns. This was done in order to find both the microhardness occurring at the edge

of the sample, and to also uncover how transition regions affect microhardness for the entire sample. Each

microhardness test was given space between tests in order to ensure that a micro-indentation does not affect the

indentation to follow [10]. In Figure 4.5, we see the deposition edge of the TiB2+AlMgB14 and Inconel 625

nickel alloy. This small region was followed by a larger V–shaped region, the melt zone produced by the laser

18

beam. The laser melt zone was a gradient, where the deposited alloys lose concentration the farther from the

deposition edge. This transition period was followed by martensite formation as a heat affected zone with no

phase change occurs in the steel during this region. The martensite region was absent any deposition material.

Figure 4.5: Sample 4 Optical Microscopy

Figure 4.6 displays the changes in microhardness from the deposition edge, melt pool, martensite region,

and to the 1095 steel track. For the seven samples of varied laser power, the highest microhardness was seen in

the following samples: 4, 3, followed by sample 5. Following hypothesis 2 that the highest microhardness will

also contain the least porosity, sample 4 was justified by the previous study with porosity fraction calculations

from the x-ray density analysis. Sample 1 shows a large drop in microhardness around 50 microns below the

deposition sample. This follows belief that the deposition height and transition region were smaller for lower

laser power settings. Sample 7 was seen to have the longest transition region, lasting around 110 microns.

Research should be completed on why the martensite region was not viewed as a transitionary period, but instead

was noticed as a direct cutoff line for each sample.

Any inconsistencies in the microhardness testing can be viewed in two ways. It can be noticed as an error in

data collection, as discussed previously in this report. Inconsistencies within the data can also be attributed to the

offset of the melt pool from the center of the steel track, noticed in Figure 4.2. A measurement could reach the

martensite region before the melt pool was finished, and produce lower vickers hardness values. Etching was com-

pleted before microhardness testing was accomplished. This could result in lower hardness values for all samples.

4.3 Scanning Electron Microscopy

SEM allowed for high resolution images at high magnification of the material surface. While debris was found

on the samples, powder and gas porosity were clearly visible throughout the melt region. A region along the

edge of the deposition samples in Figure 4.7 Right produces a smooth region, consisting of almost only the

deposited powder material. This region was directly followed by a surface texture that occurred for unknown

19

Figure 4.6: Microhardness Through Deposition Sample

reasons on the transition region. In Figure 4.7 Left, a circular area on the surface has attracted an additional

layer of material that was experiencing some cracking. This was most likely dried organic material, and will be

discussed further with Energy Dispersive Spectroscopy in the following section.

Figure 4.7: Left: 103.0 Watt SEM 110X, Right: 103.0 Watt SEM 1.04K X

Microscopy analysis was not performed on all samples due to time constraints. The same trends as in

Figure 4.7 were expected to be seen on all samples. Just as discovered from microhardness testing and micro-

ct imaging, the deposition layer and the transition region were believed to increase with an increase in laser power.

20

Figure 4.8: EDS Spectrum Analysis, 104.4K X

4.3.1 Energy Dispersive Spectroscopy

EDS analysis was completed on five separate regions within the deposition area (Figure 4.8). Spectrum 1 was an

area referenced in Figure 4.7 as an area with a cracked organic coating on the surface. The coating was covering

an area of powder porosity. On Table 4.4 Spectrum 1 consists of mainly 52.22% oxygen, 20.48% aluminum,

and 7.44% titanium. This leads to the belief that an organic coating was attracted to an area of gas porosity that

surrounds TiB2+AlMgB14 powder trapped within the melt pool.

Spectrum 2 represents the general composition of the clad region. 50.75% of the area, classified as the light

green region of Figure 4.8, consists of iron; the main ingredient of steel. Uniformity was exactly what was

expected for the melt pool area.

Spectrum 3 represented the bakelite region, and although trace amounts of powder residue were discovered,

spectrum 3 was not applicable to this research.

Table 4.4 displays an inconsistency with Spectrum 4. Boron, an element both within the titanium diboride

alloy and within BAM powder, was found localized along the surface only. This may be assumed an error with

spectroscopy analysis, considering Boron was very low on the periodic table and hard to pick up when of discreet

amounts [15]. This similar error exists with Carbon, which was noticed in large amounts within all samples [15].

Spectrum 5 was chosen to uncover compositions of what is shown as "red dots" throughout Figure 4.8. Iron

21

Table 4.4: EDS Spectrum Atomic Composition

Spectrum 1 Atomic % Spectrum 2 Atomic % Spectrum 3 Atomic % Spectrum 4 Atomic % Spectrum 5 Atomic %

O 52.22 Fe 50.75 Ti 41.57 B** 51.62 C** 48.08

Al 20.48 C** 24.01 C** 32.56 C** 24.3 Fe 31.87

C** 13.67 Ni 9.25 O 21.98 Ti 23.13 Ti 8.64

Ti 7.44 Ti 7.12 Al 2.11 Cr 0.09 Ni 5.11

Mg 4.91 Cr 3.83 Fe 0.81 Fe 0.57 Cr 2.8

Fe 0.9 Nb 2.2 Na 0.26 W* 0.3 Nb 1.63

Ca 0.22 Mo 2.04 Ca 0.23 Total 100 Mo 1.46

Cr 0.14 Si 0.79 Cl 0.13 W* 0.2

Total 100 Total 100 Si 0.12 Si 0.08

K 0.12 Ta 0.08

S 0.11 P 0.04

Total 100 Cu 0.01

Total 100

represents most of these points in the melt pool region. Small amounts of many elements found within Table 3.2

were what compose the rest of these areas, which tells us that the makeup was the Inconel 625 nickel alloy being

evenly dispersed within our sample.

Starred on Table 4.4, tungsten was found within the Inconel 625 nickel alloyed area. This was an inconsis-

tency in the EDS analysis, given that tungsten was not an element found in any of the original powder samples.

This can be explained by the consistent use of the Direct Laser Deposition machine by many students working in

various areas of research. The powder used for deposition in this research, TiB2+AlMgB14 and Inconel 625

nickel alloy, were both recollected from the bottom of the deposition chamber and reused for future research.

Previous research could have left trace amounts of tungsten, as well as elements expected within my sample

analysis, in the deposition bed to be later combined with my powder samples.

22

Chapter 5

Discussion

Given the current level of analysis performed on the deposition samples, corrections and conclusions can be

made of the original hypotheses.

The first hypothesis was that porosity will decrease with an increase in laser power. This proved to be true

until a threshold was reached, and then porosity started to increase again. After a certain point, the depth of the

melt region was large enough to trap gas in lower regions before hardening. Given that only one variable, laser

power, was adjusted, effects of changing multiple variables was still unknown. Previous research has concluded

that a lower laser power, complimented by a slow deposition speed and a high feed rate, was preferable to

overcome pores and discrepancies within the deposition areas [3].

The second hypothesis stated that porosity will originate more from gas pores, rather than from trapped

sections of powder alloy. This was consistently true for all samples due to lack of vacuum sealing the deposition

chamber. Powder porosity only occurred in samples 1 and 2, and appeared to disappear when wattage increased

above 108 watts. Still, an increase in the laser power showed a larger amount of porous behavior on the surface of

the material. The increased surface roughness for the tracks can lead to a faster wear rate[3]. Surface roughness

also produces a dramatic increase in the previously low coefficient of friction, a characteristic that was greatly

desired for this specific thin film.

For the third hypothesis, porosity was assumed to decrease with an increase in microhardness in the clad

region. We noticed that the hardest samples were 4, 3, and 5, in that order. This matches the x-ray porosity

fraction analysis completed with linearly related density calculations.

The fourth hypothesis was not applicable, as the double layer deposition scans were unable to be analyzed

given time restrictions.

When looking at microhardness testing, it was known that samples of steel coated TiB2+AlMgB14 can

achieve vickers hardness values of around 3800 HVN, or 37 GPa [3]. It should be noted that the achieved values

in this research did not surpass 1000 HVN. While the referenced study used percentages of 60% BAM and 40%

23

TiB2, the proportions in this research were unknown and are still considered proprietary information. The BAM

powder alloy mixture received at SDSMT was a tailored proportion to promote highest microhardness, although

was reused powder leftover from previous depositions. This leaves an open discussion on why the seven studied

samples received Vickers hardness values below expectation. Possible reasons for the wide range of researched

results are discussed more below.

In this research, the porosity found within the samples all existed below 2% porosity for each sample.

When comparing results to previous work, 70% - 30% AlMgB14 - TiB2 ratio of revealed porosity percentages

of 1% - 4%, which was determined to have a large effect on desired mechanical properties [15]. Given the

large difference in microhardness obtained in this work, compared to the literature work, further micro- and

nano-hardness testing needs to be performed to understand the contributions from the different materials and

porosity.

Calculating porosity percentages from x-ray density method proved to be an accurate and unique way to

determine porosity percentages. Study of other research, though, shows densities of AlMgB14 + 30 wt% TiB2 to

be 3.22 g/cm3, and AlMgB14 + 70 wt% TiB2 to be 3.82 g/cm3 [15]. Although the BAM and TiB2 powder ratio

for this experiment remains unknown, a comparison of two available densities shows that the chosen Known

density in Equation 4.1 of 3.14 g/cm3 could possibly be an underestimate. An addition of Inconel 625 nickel

alloy also would increase the actual density value. Access to the true density of the powder deposition material

would provide cleaner data to be analyzed when determining an optimum wattage for the direct laser deposition

system.

After removal of all pores within a material, the Avizo software provided information on porosity fraction

for a given sample, where the found pore volume are related to the full object. Discussion should be conducted

on whether the Avizo software determines the full object in a reference frame as the 3-D render volume of the

object, or as the entire volume of the ROI Region of Interest box that outlines the 3-D rendered model. The

assumption that the algorithm used the 3-D render volume was used. If the ROI was used as the full volume of

the object, the porosity percentages would be lower than the actual amount.

24

Chapter 6

Conclusion

Increases in laser power of direct laser deposition demonstrate various changes in levels of porosity and micro-

hardness within the deposited region. For the studied range (88.0 – 179.0 Watts) when looking at the Avizo

software analysis, a laser power of 118.0 Watts proved most effective in minimizing gas and powder porosity

within the deposited BAM region. This power setting proved to have the second highest microhardness from the

surface through the martensite region.

Porosity percentages calculated in Section 4.1.1 point to Sample 4 (133.0 Watts) as the optimum laser power

to minimize sample porosity. Hardness testing also suggested that this was the sample with the highest Vickers

hardness value.

Powder porosity occurred in the first two samples of low laser power, although gas pores dominated all clad

regions of the studied samples. Sample 2 (103.0 Watts) may not have received a uniform deposition layer, and

hence provides inaccurate data.

More research should be completed in order to completely determine porosity fractions of various laser

power settings. Even with discrepancies in the analyzed data, the optimum laser power can be narrowed to a

shorter range, between 118.0 and 133.0 Watts.

6.1 Recommendations

In recreation of this research, or if adaptations and additions occur, the following are recommendations believed

to produce more accurate data.

In order to further minimize porosity, the laser deposition chamber should be vacuum sealed. This will

remove external oxygen that was being trapped in the melt region during deposition.

If one refers to Figures 4.2 or 4.3 Left, the ‘V’ transition region of the laser beam can be seen. This beam

25

appears off centered by around 25 microns. The alignment of the direct laser deposition occurred with a hammer

and a large amount of patience, while referring to a blurry screen for “close up accuracy”. Computerized

alignment of the DLD can allow for an even coating of BAM onto the steel tracks. This will create cleaner

comparisons between samples, and could remove error occurring between the Avizo porosity densities and the

calculated x-ray intensity densities of sample 4 and sample 7.

The received 1095 steel tracks arrived in a large coil. Completing linear laser deposition on a curved track can

lead to some samples having a smaller melt region than others. The parameters that were left constant were then

out of sync along areas of curvature. Possible curvature could have produced inaccurate data with samples 2 and 7.

The samples, all of which were cut at 6mm widths, should be mounted in the same volume of bakelite. Pucks

for the researched samples varied in size. Consistency with puck depth would simplify the experimental density

and porosity fraction analysis calculated from x-ray attenuation.

Once above adjustments are made, and sample analysis of laser power was completed, adjust other processing

parameters, such as deposition speed, powder flow rate, and powder application angle.

Double layer deposition could provide another method towards a decrease in porosity fraction within samples.

By remelting the clad region, a larger amount of BAM will be deposited on the surface, as well as providing any

currently trapped pores a chance to escape the melt pool before solidifying again.

Grain boundaries were not clearly visible in any of the deposition samples. A study of the changes in grain

boundaries could provide insight on microstructure and its relationship to a change in laser power, as well as

other future adjusted parameters.

26

Chapter 7

Acknowledgments

I would like to gratefully thank the following individuals and organizations for support throughout this experience:

My personal advisor, Dr. William M. Cross, and Back to the Future site director, Dr. Michael West, for their

guidance and support on the research process, development, and for encouraging growth in research-based and

personal character.

Dr. Alfred Boysen, for his support in time management and the creation of a portfolio to showcase my

undergraduate learning experience of Summer 2016.

Graduate student Jimmy Tomich, for instruction and advising the Direct Laser Deposition process to create

the researched samples.

My fellow REU students, who provided continuous support during the research process. Thank you for the

long term personal and professional friendships built over the summer research experience.

Thank you to the National Science Foundation for providing opportunity for excellent research at SDSMT

through Grant NSF DMR-1460912.

27

Appendix A

Steps for Porosity Analysis

1. Volume Render Image

a. Establish correct threshold

2. Ortho Slice Image

a. Find lowest layer with porosity

b. Go down one more layer

3. Click on Original File Name

a. Crop image found on top right bar of popup

b. Crop out all layers below the porosity

4. Repeat 2 and 3 with upper limit

5. AutoCrop

6. Porosity Analysis Wizard

a. Apply Noise Reduction

b. Filter Width 3

c. Detect Main Voids

d. Click on IThreshold Point

e. Select Data Name with no Mask

f. Apply, then click on IThreshold label, then click Move On

g. Detect Adaptively Small Porosity

h. Size: 7 voxels

i. Repeat from part d for small porosity

j. Do not separate voids

k. So we first outline the object, then on small porosities we highlight the pores

l. Adjust maximum volume of defects DOWN until outer massive bubbles disappear.

m. Click on porosities analysis volume render

n. Hide 3-D image by adjusting threshold to just see porosity

7. Remove Small Spots

8. Volume Fraction (No Mask)

28

Appendix B

XRadia MicroXCT Computed TomographyQuick Reference Guide

Detailed Steps

(Assumes no sample or filter currently in the system)

1. Open XMController

2. Position Source at -100 and Detector at +50 (safe zone for typical sized samples) Found on Motion Controller,

Joystick image.

3. Set Stage to X = 0, Y = 0 , Z = 0, and Theta = 0.

4. Switch Objective to low resolution (Macro, 1X, or 4X to match sample size) Magnifying Glass image.

5. Remove any previous sample stand and screen on x-ray source.

6. Load Sample and position roughly with visual light camera (VLC) and joystick.

7. Close door.

8. Turn on x-ray. Set kV to 80 kV (Organic Samples) or 140 kV (Inorganic Samples) and power to max. This

will take 10 – 15 minutes to warm up to desired kV. (Click Light bulb Image)

9. Begin continuous imaging at 1 second, binning 4. (Click Two Gears image)

10. Turn on cross-hairs (Highlight center Field of View FOV) Found under the View tab.

11. At Theta = 0, use double clicking to position region of interest to the center of the cross-hairs.

12. Rotate sample +90 and -90 degrees by using the tab at the bottom right of the x-ray image.

13. At Theta = +90/-90, use double clicking to position region of interest to the center of the cross-hairs to center

the Z-Axis.

14. Press STOP sign to turn off continuous imaging. Switch to desired magnification.

15. Repeat steps 9 – 14 as needed.

16. Move Detector towards sample to increase Field of View, if needed.

17. Determine correct filter and kV.

a. Write down Y-Value location of sample in external notepad.

b. Move Sample out of FOV, and perform single acquisition of air space.

c. Paste in Y-Value from external notepad, and perform single acquisition of sample FOV.

d. Click ‘Process’ tab, and choose image calculator.

29

e. B/A = Image/Air = Normalized Intensity

f. See filter selection quick guide before proceeding to step 18.

g. Add proper filter, and adjust kV range until 0.22 – 0.35 is seen after Image Calculator is completed again.

18. Determine single acquisition time. Best image quality is obtained with counts >5000 on sample.

19. Acquire tomography points using the Tomography Location tool.

a. Highlight Center FOV (Found under ‘View’ tab)

b. Click ‘Image Control’ (Two Tools image)

c. Click on Annotation Recipe (Crosshairs image, bottom right)

d. Clear Existing

e. Set as current Tomography Points

20. Set up Recipe. (Four Gears image)

a. Click on Check Tomography Location (Make sure the X, Y, Z values are the same as the current position

on Motion Controller).

b. -180 degrees to 180 degrees

c. Adjust Exposure Time to desired time (Determined during single acquisition, step 18)

d. Set number of images to 1600, with 400 frames between images

e. Set minimal number of reference frames to 10

f. Estimate center shifting, unless ring artifacts occur

g. Browse file storage directory for a place to save file, and provide a clear name.

h. Run Current Recipe

30

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