applications

It’s a zoo in there!

Dr. René de Kloe, Applications Specialist, EDAX

For most of us EBSD users, our day to day experience is with metals, ceramics, or perhaps rocks. For man-made materials, analysis allows us to characterise the microstructure so that we can finetune the processing or fabrication of a material for a specific application. Another common use of EBSD data is for failure analysis where the crystallographic information can be coupled to external characterisation data and deformation structures such as cracks, welds, or ductile deformation features.

Figure 1. IPF map of partially recrystallized steel (left); IQ map of quartzite rock from the Pilbara region in Australia (right).

For natural materials like rocks, the questions start to get a bit trickier as we typically do not know exactly how a rock has come to exhibit the structures that it has. In combination with other tools, EBSD can then be an invaluable tool to add crystallographic and phase information to the puzzle. This allows researchers to piece together the deformation, temperature, and pressure history of the rock. This way tiny samples can provide insight in processes on a global scale like mountain building and the motion of the continents.

A third group of materials that gets a bit less attention in EBSD analysis are biominerals, materials that are formed with a certain degree of biological control to become part of an organism. In these biomaterials, the question is not how we have produced it, or how it could be finetuned to its intended application. Here the question is how biological processes have been able to optimise a material to such a remarkable degree and the EBSD analysis is used to try to understand the biological use and control of crystallisation. Unfortunately, we rarely get to look at structures that are produced by living organisms, except possibly fossils. One of the reasons that “fresh” biomineral structures are rarely studied with EBSD is that they often contain an organic fraction that makes electron microscopy samples susceptible to beam damage. To analyse such materials, the researcher must be very careful. A single pass with the electron beam is often all you get as the structure is easily damaged. In fossilised remains of animals, the organic component has been lost or replaced by solid crystals which make its analysis somewhat easier. For example, in recent years, papers have been published on crystalline lenses in the eyes of long extinct trilobites which were formed of calcite [1] and EBSD has also been used to estimate which areas of dinosaur eggs are most likely to represent the original microstructure such that the isotope ratios from these grains can be used to estimate the crystallisation temperature of the eggs [2].

A bit closer to us is perhaps the analysis of hydroxyapatite in bones. In the SEM image this cross section of a bone consists of a fibrous framework with brighter areas containing individual hydroxyapatite grains. What is not clear from such an image is if the grain orientations in these areas are all identical or perhaps exhibit random orientation. EBSD analysis clearly shows that the apatite grains occur in small clusters with similar IPF colours or equivalent orientations, which indicates that these smaller clusters are connected in the 3rd dimension in the material.

Figure 2. BSE image cross-section of bone (left); Hydroxyapatite IPF map on a single hydroxyapatite region in bone (right).

The recent introduction of the easy recording of all EBSD patterns during a scan and performing NPAR (neighbour pattern averaging and reindexing) during EBSD post-processing have allowed dramatic improvements in the analysis of beam sensitive materials. You still have to use gentle beam currents and relatively low kV to obtain the EBSD patterns. These patterns are then very noisy and the initial maps often show poor indexing success rates, but once these have been collected you are free to find the optimum way to analyse these patterns for the best possible results. For example, beam sensitive materials like the aragonite in the nacre of shells can be successfully analysed.

Figure 3. Calcite-aragonite transition the inside of a shell: original measurement (left); after NPAR reprocessing (right).

The aragonite-calcite phase map above on the left shows the initial results of an EBSD map of the inner surface of a shell over a transition zone from the calcite “framework” on the right to the smooth nacre finish on the left of the analysis area. Directly at the interface the EBSD pattern quality is so poor that it is difficult to interpret the microstructure. The phase map on the right is after NPAR reprocessing. Now the poorly indexed zone at the transition is much narrower and the map clearly shows how the aragonite starts growing in between the calcite pillars, then forms a thin veneer on top of the calcite until it gets thick enough to create euhedral planar crystals that form the smooth nacre surface at the inside of the shell.

Figure 4. Aragonite structure from pillars to nacre: original measurement (left); after NPAR reprocessing (right).

Figure 4 shows another shell structure which is now completely composed of aragonite. In cross section the structure resembles that of the calcite pillars with the nacre platelets on top, but the initial scans do not reveal any structure in the pillars. This could be taken as evidence that the crystal structure might be damaged and cannot be characterised properly using EBSD. However, after NPAR reprocessing the crystal structure of the pillars becomes clear and a feather-like microstructure is revealed.

These fascinating biological structures don’t appear often to the average materials scientist or geologist, but if you keep an open mind for unexpected structures you can still be treated to beautiful virtual creatures in or on your samples. For example, dirt is not always just in the way. Here it poses as a micron sized ground squirrel overlooking your analysis. And this magnetite duck is just flying into view over a glassy matrix.

Figure 5. Dirt patch in the shape of a ground squirrel (left); crystal orientation map of a magnetite duck flying through glass (right).

And what to think of these creatures, a zirconia eagle that is flying over a forest of Al2O3 crystals and this micron sized dinosaur that was lurking in a granite rock from the highlands of Scotland. Perhaps we finally found an ancestor of Nessie?

Figure 6. Zirconia EDS Eagle: in zirconia -alumina ceramic (left); on PRIAS bottom image (right).

Figure 7. Ilmenite-magnetite dinosaur in a granite rock.

It is clear that “biological” EBSD can occur in many shapes and sizes. Sometimes it is literally a zoo in there!

[1] Clare Torney, Martin R. Lee and Alan W. Owen; Microstructure and growth of the lenses of schizochroal trilobite eyes. Palaeontology Volume 57, Issue 4, pages 783–799, July 2014
[2] Eagle, R. A. et al. Isotopic ordering in eggshells reflects body temperatures and suggests differing thermophysiology in two Cretaceous dinosaurs. Nat. Commun. 6:8296 doi: 10.1038/ncomms9296 (2015).

My New Lab Partner Part 2 (East Coast Edition)

Jens Rafaelsen, Applications Engineer, EDAX

During a recent trip to our Draper lab in Utah for a training class, I got a first-hand look at Matt’s new lab partner (https://edaxblog.com/2017/02/14/my-new-lab-partner/). I must admit that I am a little envious of his new microscope and how easily you get great looking images (even at low acceleration voltage or high beam current) compared to the systems we have in our Mahwah lab. However, I must also admit that he needed an upgrade a lot more than we did. While his old XL has been very reliable (and still seems to be, even after moving it to another room), it was always a bit of a worry conducting a training class with only one microscope available and one that was at end of service life at that.

Around the time when Matt got his new microscope we also had an addition to our Mahwah lab as seen in the picture below:

OK, it’s definitely not an ARM or a TITAN, it only goes to 120kV, it’s not quite as new and fancy as Matt’s microscope, and the firmware might read 1994 when you hit the ON button, but it’s still good to have a TEM in the building once again. One of the things that’s great about older scientific instruments is that they often include full vacuum and wiring diagrams, schematics, and troubleshooting directions. Not so great: pressure readings in arbitrary numbers… I did some creative plumbing and mounted extra gauges on the line of the microscope gauges so now I know that a pressure reading in the buffer tank of 26 corresponds to roughly 10-1 mbar and that the camera chamber goes down to the mid 10-5 mbar. As an added bonus, several people in the building have been around long enough to have experience with the CM12 both as users and service and have had their memories jogged for how to run and align it. This also spurred the comment: “That’s right, this is why I decided to get out of field service…”.

Having had very limited TEM experience it’s been a bit of a learning curve for me but I think it’s getting there. There’s still a lot to learn when it comes to fine tuning of the instrument, diffraction, and aligning for dark field imaging, but at least I am able to get bright field images at over 500k magnification without spending too much time. And some of the images actually have somewhat decent resolution and recognizable features at that:

Holey carbon at 660.000x magnification

Of course, a lot of what we do at EDAX doesn’t really require great resolution or the newest instruments. While it’s always nice to have pretty pictures to go along with things, the X-rays don’t really care much about your astigmatism or spot size (unless you are trying to map of course). But there’s a significant difference in what you see in your spectra whether your electrons are hitting the sample with 15 kV or 120 kV. There are also very different considerations and limitations between a SEM and a TEM when it comes to actually mounting the detector, designing collimators, and even what materials can be used. With that being said, I hope that with my “new” lab partner we will move things along so that we can show you new applications, software, and hardware specifically for the TEM in the near future.

My New Lab Partner

Matt Nowell, EBSD Product Manager, EDAX

It has been an exciting month here in our Draper Utah lab, as we have received and installed our new FEI Teneo FEG SEM. We are a small lab, focusing on EBSD development and applications, and without a loading dock, so timing is critical when scheduling the delivery. So, 3 months ago, we looked at the calendar to pick a day with sunshine and without snow. Luckily, we picked well.

Figure 1: Our new SEM coming off the truck.

Figure 1: Our new SEM coming off the truck.

Once we got the new instrument up and running, of course the next step was to start playing with it. This new SEM has a lot more imaging detectors than our older SEM, so I wanted to see what I could see with it. I chose a nickel superalloy turbine blade with a thermal barrier coating, as it had many phases for imaging and microanalysis. The first image I collected was with the Everhart-Thornley Detector (ETD). For each image shown, I relied on the auto contrast and brightness adjustment to optimize the image.

Figure 2: ETD image

Figure 2: ETD image

With imaging, contrast is information. The contrast in this image shows phase contrast. On the left, gamma/gamma prime contrast is visible in the Nickel superalloy while different distinct regions of the barrier coating are seen towards the right. The next image I collected was with the Area Backscatter Detector (ABS). This is a detector that is positioned under the pole piece for imaging. With this detector, I can use the entire detector, the inner annular portion of the detector, or any of three regions towards the outer perimeter of the detector.

Figure 3: ABS Detector image.

Figure 3: ABS Detector image.

I tried each of the different options, and I selected the inner annular ring portion of the detector. Each option provided similar contrast as seen in Figure 3, but I went with this based on personal preference. The contrast is like the ETD contrast is Figure 2. I also compared with the imaging options using the detector in Concentric Backscatter (CBS) mode, where 4 different concentric annular detectors are available.

Figure 4: T1 Detector (a-b mode).

Figure 4: T1 Detector (a-b mode).

My next image used the T1 detector, which to my understanding is an in-lens detector. In this mode, I selected the a – b mode, so the final image is obtained by subtracting the image from the b portion of the detector from the a portion of the detector. I selected this image because the resultant contrast is reversed from the first couple of images. Here phases that were bright are now dark, and detail within the phases is suppressed.

Figure 5: T2 Detector.

Figure 5: T2 Detector.

My final SEM image was collected with the T2 detector, another in-lens detector option. Here we see the same general phase contrast, but the contrast range is more limited and the detail within regions is again suppressed.

I have chosen to show this set of images to illustrate how different detectors, and their positioning, can generate different images from the area, and that the contrast/information obtained with each image can change. Now I have done a cursory interpretation of the image contrast, but a better understanding may come from reading the manual and knowing the effects of the imaging parameters used.

Figure 6: Always Read the Manual!

Figure 6: Always Read the Manual!

Of course, I’m an EBSD guy, so I also want to compare this to what I can get using our TEAM™ software with Hikari EBSD detectors. One unique feature we have in our software is PRIAS™, which uses the EBSD detector as an imaging system. With the default imaging mode, it subsets the phosphor screen image into 25 different ROI imaging detectors, and generates an image from each when the beam is scanned across the area of interest. Once these images are collected, they can be reviewed, mixed, added, subtracted, and colored to show the contrast of interest, similar to the SEM imaging approach described above.

The 3 most common contrasts we see with PRIAS™ are phase, orientation, and topographic. To capture these, we also have a mode where 3 pre-defined regional detectors are collected during EBSD mapping, and the resulting images available with the EBSD (and simultaneous EDS) data.

Figure 7: PRIAS™ Top Detector Image.

Figure 7: PRIAS™ Top Detector Image.

The first ROI is positioned at the top of the phosphor screen, and the resulting phase contrast is very similar to the contrast obtained with the ETD and ABS imaging modes on the SEM.

Figure 8: PRIAS™ Center Detector Image.

Figure 8: PRIAS™ Center Detector Image.

The second ROI is positioned at the center of the phosphor screen. This image shows more orientation contrast.

Figure 9: PRIAS™ Bottom Detector Image.

Figure 9: PRIAS™ Bottom Detector Image.

The third ROI is positioned at the bottom of the phosphor screen. This image shows more topographical contrast. All three of these images are complementary, both to each other but also to the different SEM images. They all give part of the total picture of the sample.

Figure 10: Defining Custom ROIs in PRIAS™.

Figure 10: Defining Custom ROIs in PRIAS™.

With PRIAS™ it is also possible to define custom ROIs. In Figure 10, 3 different ROIs have been drawn within the phosphor screen area. The 3 corresponding images are then generated, and these can be reviewed, mixed, and then selected. In this case, I selected an ROI that reversed the phase contrast, like the contrast seen with the T1 detector in Figure 4.

Figure 11: PRIAS™ Center Image with EDS Bland Map (Red-Ni, Blue – Al, Green-Zr)

Figure 12: PRIAS™ Center Image with Orientation Map (IPF Map Surface Normal Direction).

figure-12a

Of course, the PRIAS™ information can also be directly correlated with the EDS and EBSD information collected during the mapping. Figure 11 shows an RGB EDS map while Figure 12 shows an IPF orientation map (surface normal direction with the corresponding orientation key) blended with the PRIAS™ center image. Having this available adds more information (via contrast) to the total microstructural characterization package.

I look forward to using our new SEM, to develop new ideas into tools and features for our users. I imagine a few new blogs posts should come from it as well!

The Hough Transform – An Amazing Tool.

Shawn Wallace, Applications Engineer, EDAX

Part of my job is understanding and pushing the limits of each part of our systems. One of the most fundamental parts of the EBSD system is the Hough Transform. The Hough Transform role is finding the lines on an EBSD pattern. This is the first step in indexing a pattern (Fig. 1). If this step is not consistent, the quality of any indexing and any derivative data is questionable. A normal user does not really need to understand all the intricacies of every part of the system, but it still is worthwhile to understand how your data and data quality can be affected.

Figure 1: On the left are the overlaid lines found via the Hough Transform. On the right is the Indexed solution overlaid based on the Hough. The quality of the indexed solution is based on the quality of the Hough.

Figure 1: On the left are the overlaid lines found via the Hough Transform. On the right is the Indexed solution overlaid based on the Hough. The quality of the indexed solution is based on the quality of the Hough.

With that in mind, I ran an experiment on a steel sample to see how far the Hough could be pushed and still give consistent indexing. For this experiment, I used our Hikari Super at a series of different binnings between its native resolution of 640X480 Pixels at 1×1 binning down to 35×26 pixels at 18×18 binning. All pixel resolutions are noted in Table 1. I kept my Hough Settings and beam settings consistent. My only other variable was exposure to get the camera to be equally saturated at around 0.85 saturation.

I expected the lower binning Patterns to be consistent and they were (Fig. 2). All three Euler Angles between the 1×1, 2×2, 4×4, and 8×8, were within 0.4 degrees of each other. Pushing the camera and the Hough even further really surprised me though.

Figure 2: Indexed Pattern for the lower binning showed a remarkable consistency in indexing.

Figure 2: Indexed Pattern for the lower binning showed a remarkable consistency in indexing.

Figure 3: The indexing results still held their consistency even for highest binning settings used.

Figure 3: The indexing results still held their consistency even for highest binning settings used.

I expected some drop off with the consistency of the orientation when I dropped my binning to 10×10, 16×16, and even 18×18 and it did not fully materialize (Fig. 3). The range did broaden in the Euler Angles, specifically ᶲ₂’s range increased to 3 degrees, but that is change of <1% given the entire range for ᶲ₂ is 360 degrees. Table 1 shows the data is the raw form. Overall, the data is great, from low to high binning with minimal loss in in our indexing metrics (CI and Fit) and consistency in Euler Angles except for the 18×18 binning. That is where we have found our limit, specifically when it comes to indexing metrics. We see a sharp drop off in the CI. The pixilation of the pattern has gotten to a point where it is difficult to find a unique solution. This drop off is why we tell our customer that 16×16 is the limit of binning they should use for reliable, high quality data.

Table 1. Indexing Metrics and Euler Angles for all data points.

Table 1. Indexing Metrics and Euler Angles for all data points.

With all that said, most EBSD work is not on a single orientation, but a map. Does this hold true on a map? It does. In Figure 4 and Figure 5, we can see the mapping results for 2×2 binning and 10×10 binning. Both indexed at 99.9% with their average CI’s being 0.89 and 0.84 respectively, with very little change in orientations. This level of data quality across binnings is why EDAX uses the Hough. It is an amazing little tool.

Figure 4. This map was taken at 2x2 binning. Internal deformation of the grains is visible, with inclusions between relatively undeformed.

Figure 4. This map was taken at 2×2 binning. Internal deformation of the grains is visible, with inclusions between relatively undeformed.

Figure 5. This map was taken at 10x10 binning in approximately the same area as Figure 4. Again, internal deformation is showed in the larger grain, while the inclusions are undeformed.

Figure 5. This map was taken at 10×10 binning in approximately the same area as Figure 4. Again, internal deformation is showed in the larger grain, while the inclusions are undeformed.

Adding a New Dimension to Analysis

Dr. Oleg Lourie, Regional Manager A/P, EDAX

With every dimension, we add to the volume of data, we believe that we add a new perspective in our understanding and interpretation of the data. In microanalysis adding space or time dimensionality has led to the development of 3D compositional tomography and dynamic or in situ compositional experiments. 3D compositional tomography or 3D EDS is developing rapidly and getting wider acceptance, although it still presents challenges such as the photon absorption, associated with sample thickness and time consuming acquisition process, which requires a high level of stability, especially for TEM microscopes. After setting up a multi hour experiment in a TEM to gain a 3D compositional EDS map, one may wonder Is there any shortcut to getting a ‘quick’ glimpse into 3-dimensional elemental distribution? The good news is that there is one and compared to tilt series tomography, it can be a ‘snapshot’ type of the 3D EDS map.

3D distribution of Nd in steel.

3D distribution of Nd in steel.

To enable such 3D EDS mapping on the conceptual level we would need at least two identical 2D TEM EDS maps acquired with photons having different energy – so you can slide along the energy axis (adding a new dimension?) and use photon absorption as a natural yardstick to probe the element distribution along the X-ray path. Since the characteristic X-rays have discrete energies (K, L, M lines), it might work if you subtract the K line map from the L line or M line map to see an element distribution based on different absorption between K and L or M line maps. Ideally, one of EDS maps should be acquired with high energy X-rays, such as K lines for high atomic number elements, and another with low energy X-rays where the absorption has a significant effect, such as for example M lines. Indeed, in the case of elements with a high atomic number, the energies for K lines area ranged in tens of keV having virtually 0 absorption even in a thick TEM sample.

So, it all looks quite promising except for one important detail – current SDDs have the absorption efficiency for high energy photons close to actual 0. Even if you made your SDD sensor as large 150 mm2 it would still be 0. Increasing it to 200 mm2 would keep it steady close to 0. So, having a large silicon sensor for EDS does not seem to matter, what matters is the absorption properties of the sensor material. Here we add a material selection dimension to generate a new perspective for 3D EDS. And indeed, when we selected a CdTe EDS sensor we would able to acquire X-rays with the energies up to 100 keV or more.

To summarize, using a CdTe sensor will open an opportunity for a ‘snapshot’ 3D EDS technique, which can add more insight about elemental volume distribution, sample topography and will not be limited by a sample thickness. It would clearly be more practical for elements with high atomic numbers. Although it might be utilized for a wide yet selected range of samples, this concept could be a complementary and fast (!) alternative to 3D EDS tomography.

Rotary Engines Go “Round and Round”

Dr. Bruce Scruggs, XRF Product Manager EDAX

Growing up outside of Detroit, MI, automobiles were ingrained in the culture, particularly American muscle cars. I was never a car buff but if I said little and nodded knowingly during these car discussions, I could at least survive. Engine displacement? Transmission? Gear ratios? Yep, just nod your head and grunt a little bit. Well, it turns out working at EDAX that I’ve run into a couple of serious car restoration experts. There always seems to be a common theme with these guys: how do I get more power out of this engine?

Recently, one of these restoration experts brought in a small section of the rotor housing of a Mazda engine circa early ‘80s. Turns out, this guy likes to rebuild Mazda engines, tweak the turbocharging and race them. As we all know, Mazda was famous for commercializing the Wankel engine, aka the rotary engine, to power their cars. Rotary engines are famous for their simplicity and the power one can generate from a relatively small engine displacement. These engines are also infamous (i.e. poor fuel consumption and emissions) as well which has led Mazda to end general production in roughly 2012 with the last of the production RX-8s.

Now, one of the questions in rebuilding these engines is how to repair and resurface the oblong rotor housing. In older engines of this type, the surface of the rotor housing can suffer deep gouges. The gouges can be filled and then need to be resurfaced. Initially, we imaged the cross-section of the rotor housing block in an Orbis PC micro-XRF spectrometer to determine what was used to surface coat the rotor housing. If you read up on this engine, (it’s a 12A variant), the block is aluminum with a cast iron liner and a hard chromium plating. The internet buzz claims the liner is installed via a “sheet metal insert process”. And when I google “sheet metal insert process” all I get are links to sheet metal forming and links referring to webpages which have copied the original reference to “sheet metal insert process”.

In the following Orbis micro-XRF maps (Figures 1a and 1b), you can see the aluminum rotor housing block and the cast iron liner. Each row of the map is about 100 µm wide with the iron liner being about 1.5 mm thick. If you look carefully, you can also see the chrome coating on the surface of the iron liner. On the cross-section, which was done with a band saw cut, the chrome coating is about one map pixel across. So, it’s less than 100 µm thick. From web searches, hard chrome plating for high wear applications start at around 25 µm thick and range up to hundreds of microns thick. For very thick coatings, they are ground or polished down after the plating process to achieve more uniform application. So, what is found in the elemental map is consistent with the lower end of web-based information for a hard chrome coating, bearing in mind that the coating measured had well over 150k miles of wear and tear. If we had a rotor housing with less wear and tear, we could use XRF to make a more proper measurement of the chrome plating thickness and provide a better estimate of the original manufacturer’s specification on the hard chrome thickness.

Figure 2: Orbis PC elemental map

Figure 1a: Orbis PC elemental map

Overlay of 4 elements:
Fe: Blue (from the cast iron liner)
Al: Green (from the aluminum rotor housing block)
Cr: Yellow (coating on the cast iron liner)
Red: Zinc (use unknown)

Figure 3: Total counts map: Lighter elements such as Al generate fewer X-ray counts and appear darker than the brighter, heavy Fe containing components.

Figure 1b: Total counts map: Lighter elements such as Al generate fewer X-ray counts and appear darker than the brighter, heavy Fe containing components.

We did have a look at the chrome coating by direct measurement with both XRF, looking for alloying elements such as Ti, Ni, W and Mo, as well as SEM-EDS looking for carbides and nitrides. We found that it’s simply a nominally, pure chrome coating with no significant alloying elements. We did see some oxygen using SEM-EDS, but that would be expected on a surface that has been exposed to high heat and combustion for thousands of operating hours. Again, these findings are consistent with a hard chrome coating.

In some on-line forum discussions, there was even speculation that the chrome coating was micro-porous to hold lubricant. So, we also looked at the chrome surface under high SEM magnification (Figure 2). There are indeed some voids in the coating, but it doesn’t appear that they are there by design, but rather that they are simply voids associated with the metal grain structure of the coating or perhaps from wear. We specifically targeted a shallow scratch in the coating, looking for indications of sub-surface porosity. The trough of the scratch shows a smearing of the chrome metal grains but nothing indicating designed micro-porosity.

Figure 4: SEM image of chrome plated surface of rotor housing liner. The scratch running vertically in the image is about 120 µm thick.

Figure 2: SEM image of chrome plated surface of rotor housing liner. The scratch running vertically in the image is about 120 µm thick.

The XRF maps in Figure 1 also provides some insight into the sheet metal insert process. The cast iron liner appears to be wrapped in ribbons of aluminum alloy and iron. The composition of the iron ribbon (approximately 1 wt% Mn) is about the same as the liner. But, the aluminum alloy ribbon is higher in copper content than the housing block. This can be seen in the elemental map (Figure 1a) where the aluminum ribbon is a little darker green, lower Al signal intensity, than the housing block itself. The map also shows a thread of some zinc bearing component running through (what we speculate are) the wrappings around the liner. My best guess here is that it is some sort of joining compound. Ultimately, the sheet metal insert process involves a bit more than a simple press or shrink fit of a cylinder sleeve in a piston engine block. Nod knowingly and grunt a little.

Help!

Dr. René de Kloe, Applications Specialist EDS, EBSD, EDAX

The job of an applications engineer is to help people. Help sales people to explain to customers what a system can do. Help customers to get the most out of their system and help them to understand their materials better. Help the marketing group with nice examples. And help the development team to devise applications that have not been tried before.

One thing you need in order to be able to help is knowing the EDAX analysis systems inside-out. But the other thing you need is samples. Lots of samples. Every function or analysis tool in the software, regardless if it is for EDS, EBSD, WDS, or XRF is best shown with a specific material or combination of elements or phases. Some of these, like chemical standards with known composition, you have to make or perhaps buy. Others you have to collect yourselves, but from where? A great source for new materials are our customers. People often send me materials to evaluate our systems, or for help on how to best analyse their samples. When I then get permission to keep a bit of the material it goes directly into my collection, together with valuable information on the current analysis requirements in different scientific disciplines.

Eight phase FeSi alloy Brass with NiMnSi particles 

This goes a long way in getting good example materials, but I always keep my eyes open for new interesting things. When I see a metal strip in an anti-theft label in clothing I keep it (after buying the item of course), when a droplet of lead-tin solder falls on the floor, I stick it in the microscope to see if it looks good. I also scrutinize things that get thrown away, ranging from the lid of a vegetable jar to a damaged bellows of an EBSD system. That has given me beautiful cast aluminium samples for EDS mapping, multiphase brass alloys for ChI-Scan EDS-EBSD analysis, and recently an unexpected copper-plated zinc-aluminium-silicon alloy for EBSD phase identification from a broken belt buckle.

Grain structure of a staple Grain structure of a key ring 

Luckily I don’t always have to go dumpster diving to get my example materials. One of my favorite sample mounts contains different types of heavily deformed ferrite, duplex stainless steel, and also martensitic structures. That sounds perhaps complicated, but on the outside the same sample just looks like staples, a paperclip, a key ring, and a screw.

The screw, for example, I polished after doing some DIY work at home and because a certain type of screw kept breaking off when I tightened it, I wanted to take a close look why that happened. It turned out that there were lots of small cracks along the thread, which then also lined up with trails of carbides further inside the screw. That turned out to be a really bad combination and when you tighten the screw, the cracks propagate, connect with the carbide trails and the screw head snaps off. The replacement screws that I used instead had a much finer structure without any cracks and that is what is still holding things together in the house. This shows how microstructures literally shape our daily life. And it also provides a beautiful example to help illustrate the importance of microstructural characterization to new EBSD users.

Weak screw Strong screw

The huge variation in materials and microstructures makes the collection of demonstration samples the most important tool for an application scientist and from this place I hereby want to thank all people who have given me a piece of some material during my years at EDAX to use to help others.

By the way, I would appreciate it very much if the person who briefly “borrowed” my marble sample last year gives it back soon …