microstructural analysis

How to Increase Your Materials Characterization Knowledge with EDAX

Sue Arnell, Marketing Communications Manager, EDAX

The EDAX Applications and Product Management teams have been very busy offering free ‘continuing education’ workshops in September and October – with a great global response from our partners and customers.

At the end of September, Applications Specialist Shawn Wallace and Electron Backscatter Diffraction (EBSD) Product Manager Matt Nowell joined 6 additional speakers at a ‘Short Lecture Workshop for EBSD’, sponsored by EDAX at the Center for Electron Microscopy and Analysis (CEMAS) at The Ohio State University. The participants attended sessions ranging from ‘EBSD Introduction and Optimization of Collection Parameters for Advanced Application’ to ‘The Dictionary Approach to EBSD: Advances in Highly-Deformed and Fine-Grained Materials’.

Feedback on this workshop included the following comments, “This was a great learning opportunity after working with my lab’s EDAX systems for a couple of months”; “I like the diversity in the public and the talks.  I was very pleased with the overall structure and outcome”; and “Great! Very helpful.”

Matt Nowell presents at the ‘Short Lecture Workshop for EBSD’ at CEMAS, OSU.

In mid-October, EBSD Applications Specialist, Dr. Rene de Kloe traveled to India for a series of workshops on EBSD at the Indian Institute of Science (Bangalore), the International Advanced Research Center (Hyderabad), and the Indian Institute of Technology (Mumbai). Topics discussed at the sessions included:

• Effects of measurement and processing parameters on EBSD
• The application of EBSD to routine material characterization
• Defining resolution in EBSD analysis
• Three Dimensional EBSD analysis – temporal and spatial
• Advanced data averaging tools for improved EDS and EBSD mapping – NPAR™
• Microstructural Imaging using an Electron Backscatter Diffraction Detector – PRIAS™
• Transmission EBSD from low to high resolution

Dr. René de Kloe presents at one of three recent workshops in India.

According to our National Sales Manager in India, Arjun Dalvi, “We conducted this seminar at different sites and I would like to share that the response from all our attendees was very good. They were all eager to get the training from Dr. René and to take part in very interactive Q and A sessions, in which many analysis issues were solved.”

Global Applications Manager Tara Nylese was at the Robert A. Pritzker Science Center in Chicago, IL last week to give a presentation on “Materials Characterization with Microscopy and Microanalysis” for the Illinois Institute of Technology. “In this lecture, we started with a basic introduction to electron microscopy, and then dived deeper into the fundamentals of X-ray microanalysis. We explored both the basics of X-ray excitation, and how to evaluate peaks in an X-ray spectrum. From there, we looked at applied examples such as composition variation in alloys, chemical mapping of components of pharmaceutical tablets, and some fascinating underlying elemental surprises in biological materials.”

Finally, today we have 50 participants at the Geological Museum in Cambridge, MA for a training workshop given by Dr. Jens Rafaelsen and sponsored by Harvard University on “Taking TEAM™ EDS Software to the Next Level” * Presentation topics include:

• Basic operation of the TEAM™ EDS Analysis package
• How to get the most out of TEAM™ EDS Analysis
• Advanced training
• Tips and Tricks using TEAM™ EDS Analysis

Dr. Jens Rafaelsen presents at the Harvard workshop.

Here at EDAX, we are keen to provide our customers, potential customers, and partners with opportunities to improve their knowledge and polish their skills using the techniques, which are central to the EDAX product portfolio.  Our EDS, EBSD, WDS and XRF experts are keen to help with regular training sessions, webinars, and workshops. If you would like to be included, please check for upcoming webinarsworkshops, and training sessions at www.edax.com.

*A video of these workshop sessions will be available from EDAX in the coming weeks.

A Bit of Background Information

Dr. Jens Rafaelsen, Applications Engineer, EDAX

Any EDS spectrum will have two distinct components; the characteristic peaks that originate from transitions between the states of the atoms in the sample and the background (Bremsstrahlung) which comes from continuum radiation emitted from electrons being slowed down as they move through the sample. The figure below shows a carbon coated galena sample (PbS) where the background is below the dark blue line while the characteristic peaks are above.

Carbon coated galena sample (PbS) where the bacground is below the dark blue line while the characteristic peaks are above.

Some people consider the background an artefact and something to be removed from the spectrum (either through electronics filtering or by subtracting it) but in the TEAM™ software we apply a model based on Kramer’s law that looks as follows:Formulawhere E is the photon energy, N(E) the number of photons, ε(E) the detector efficiency, A(E) the sample self-absorption, E0 the incident beam energy, and a, b, c are fit parameters¹.

This means that the background is tied to the sample composition and detector characteristic and that you can actually use the background shape and fit/misfit as a troubleshooting tool. Often if you have a bad background, it’s because the sample doesn’t meet the model requirements or the data fed to the model is incorrect. The example below shows the galena spectrum where the model has been fed two different tilt conditions and an overshoot of the background can easily be seen with the incorrect 45 degrees tilt. So, if the background is off in the low energy range, it could be an indication that the surface the spectrum came from was tilted, in which case the quant model will lose accuracy (unless it’s fed the correct tilt value).


This of course means that if your background is off, you can easily spend a long time figuring out what went wrong and why, although it often doesn’t matter too much. To get rid of this complexity we have included a different approach in our APEX™ software that is meant for the entry level user. Instead of doing a full model calculation we apply a Statistics-sensitive Non-linear Iterative Peak-clipping (SNIP) routine². This means that you will always get a good background fit though you lose some of the additional information you get from the Bremsstrahlung model. The images below show part of the difference where the full model includes the steps in the background caused by sample self-absorption while the SNIP filter returns a flat background.

So, which one is better? Well, it depends on where the question is coming from. As a scientist, I would always choose a model where the individual components can be addressed individually and if something looks strange, there will be a physical reason for it. But I also understand that a lot of people are not interested in the details and “just want something that works”. Both the Bremsstrahlung model and the SNIP filter will produce good results as shown in the table below that compares the quantification numbers from the galena sample.

Table

While there’s a slight difference between the two models, the variation is well within what is expected based on statistics and especially considering that the sample is a bit oxidized (as can be seen from the oxygen peak in the spectrum). But the complexity of the SNIP background is significantly reduced relative to the full model and there’s no user input, making it the better choice for the novice analyst of infrequent user.

¹ F. Eggert, Microchim Acta 155, 129–136 (2006), DOI 10.1007/s00604-006-0530-0
² C.G. RYAN et al, Nuclear Instruments and Methods in Physics Research 934 (1988) 396-402

What an Eclipse can teach us about our EDS Detectors

Shawn Wallace, Applications Engineer, EDAX

A large portion of the US today saw a real-world teaching moment about something microanalysts think about every day.

Figure 1. Total solar eclipse - image from nasa.gov

Figure 1. Total solar eclipse.                                  Image credit-nasa.gov

With today’s Solar Eclipse, you could see two objects that have the same solid angle in the sky, assuming you are in the path of totality. Which is bigger, the Sun or the Moon? We all know that the Sun is bigger, its radius is nearly 400x that of the moon.

Figure 2. How it works.                                             Image credit – nasa.gov

Luckily for us nerds, it is also 400x further away from the Earth than the moon is. This is what makes the solid angle of both objects the same, so that from the perspective of viewers from the Earth, they take up the same area in the sphere of the sky.

The EDAX team observes the solar eclipse in NJ, without looking at the sun!

Why does all this matter for a microanalyst? We always want to get the most out of our detectors and that means maximizing the solid angle. To maximize it, you really have two parameters to play with: how big the detector is and how close the detector is to the sample. ‘How big is the detector’ is easy to play with. Bigger is better, right? Not always, as the bigger it gets, the more you start running in to challenges with pushing charge around that can lead to issues like incomplete charge collection, ballistic deficits, and other problems that many people never think about.

All these factors tend to lead to lower resolution spectra and worse performance at fast pulse processing times.
What about getting closer? Often, we aim for a take-off angle of 350 and want to ensure that the detector does not protrude below the pole piece to avoid hitting the sample. On different microscopes, this can put severe restrictions on how and where the detector can be mounted and we can end up with the situation where we need to move a large detector further back to make it fit within the constraining parameters. So, getting closer isn’t always an option and sometimes going bigger means moving further back.

Figure 3. Schematic showing different detector sizes with the same solid angle. The detector size can govern the distance from the sample.

In the end, bigger is not always better. When looking at EDS systems, you have to compare the geometry just as much as anything else. The events happening today remind of us that. Sure the Sun is bigger than Moon, but the latter does just as good a job of making a part of the sky dark as the Sun does making it bright.

For more information on optimizing your analysis with EDS and EBSD, see our webinar, ‘Why Microanalysis Performance Matters’.

Celebrating the 50th Birthday of Microanalysis

Sia Afshari, Global Marketing Manager, EDAX

The Microscopy & Microanalysis (M&M) Conference is celebrating 50 years of microanalysis at this year’s meeting in St. Louis next week. There is an entire session (A18.3) dedicated to the 50-year anniversary and the historical background of microanalysis from several different perspectives.

My colleague, Dr. Patrick Camus will be presenting the history of EDAX in his presentation, “More than 50 Years of Influence on Microanalysis” at this session and this is a must see for everyone who is at all interested in the historical development and advances in microanalysis!

Looking back at some of the images in the field of microscopy and seeing how far we have come from static spectrum collection to the standardless quantification of complex materials makes me wonder (in a good way!), about the future and especially about the technical possibilities in microanalysis.

Figure 1. Nuclear Diodes EDAX System Interfaced to Cambridge Stereoscan Scanning Electron Microscope – circa 1968

Pat will be describing the evolution of the company from Nuclear Diodes (1962) through EDAX International (1972) and purchase by Philips (1974) to acquisition by Ametek in 2001. Many accomplished microanalysts have been part of the EDAX team along the journey and have contributed enormously to the technical development of microanalysis. The advancements which have been made to date and those which will continue in the future would have not been possible without the dedication and hard work of all these pioneers in this field.

Figure 2. EDAX Element Silicon Drift Detector on a Scanning Electron Microscope – 2017.

At EDAX, which happens to be older than 50 years, I have been honored to meet some of the pioneers of microanalysis. I extend my gratitude to all those whose work has made it possible for us to enjoy the level of sophistication achieved today and we hope to continue their innovative tradition!

Please click here for more information on EDAX at M&M 2017.

XRF: Old Tech Adapting to New Times

Andrew Lee, Senior Applications Engineer, EDAX

X-rays were only discovered by Wilhelm Roentgen in 1895, but by the early 1900’s, research into X-rays was so prolific that half the Nobel Prizes in physics between 1914 to 1924 were awarded in this relatively new field. These discoveries set the stage for 1925, when the first sample was irradiated with X-rays. We’ve immortalized these early founders by naming formulas and coefficients after them. Names like Roentgen and Moseley seem to harken back to a completely different era of science. But here we are today a century later, still using and teaching those very same principles and formulas when we talk about XRF. This is because the underlying physics has not really changed much, and yet, XRF remains as relevant today as it ever was. You can’t say that for something like telephone technology.

XRF has traditionally been used for bulk elemental analysis, associated with large collimators, and pressed pellet samples. For many decades, these commercial units were not the most sophisticated instruments (although Apollo 15 and 16 in 1971 and 1972 included bulk XRF units). Modern hardware and software innovations to the core technique have allowed XRF to adapt to its surroundings in a way, becoming a useful instrument in many applications where XRF previously had little to offer. Micro-XRF was born this way, combining the original principles with newer hardware and software advancements. In fact, micro-XRF is included on the new NASA rover, scheduled for launch to Mars in 2020.

Biological/life sciences is one of those fields where possibilities are now opening as XRF technology progresses. A great example that comes to mind for both professional and personal reasons is the study of neurodegenerative diseases. Many such diseases, such as Parkinson’s, Alzheimer’s, and amyotrophic lateral sclerosis (ALS), exhibit an imbalance in metal ions such as Cu, Fe, and Zn in the human body. While healthy cells maintain “metal homeostasis”, individuals with these neurodegenerative diseases cannot properly regulate, which leads to toxic reactive oxygen species. For example, reduced Fe and Cu levels can catalyze the production of hydroxyl radicals which lead to damaged DNA and cell death. Imaging the distribution of biological metals in non-homogenized tissue samples is critical in understanding the role of these metals, and hopefully finding a cure. The common language between the people who studied physics versus the people who studied brain diseases? Trace metal distribution!

A few years ago, I had the opportunity to analyze a few slices of diseased human tissue in the EDAX Orbis micro-XRF (Figure 1 and 2), working towards proving this concept. Although the results were not conclusive either way, it was still very interesting to be able to detect and see the distribution of trace Cu near the bottom edge of the tissue sample. XRF provided unique advantages to the analysis process, and provided the necessary elemental sensitivity while maintaining high spatial resolution. This potential has since been recognized by other life science applications, such as mapping nutrient intake in plant leaves or seed coatings.

Figure 1. Stitched montage video image of the diseased human tissue slice, with mapped area highlighted in red. Total sample width ~25 mm.

Figure 1. Stitched montage video image of the diseased human tissue slice, with mapped area highlighted in red. Total sample width ~25 mm.

Figure 2. Overlaid element maps: Potassium{K(K) in green} and Copper {Cu(K) in yellow} from mapped area in Figure 1, showing a clear area of higher Cu concentration. Total mapped width ~7.6 mm.

Figure 2. Overlaid element maps: Potassium{K(K) in green} and Copper {Cu(K) in yellow} from mapped area in Figure 1, showing a clear area of higher Cu concentration. Total mapped width ~7.6 mm.

Sometimes, the application may not be obvious, or it may seem completely unrelated. But with a little digging, common ground can be found between the analysis goal and what the instrument can do. And if the technology continues to develop, there seems to be no limit to where XRF can be applied, whether it be outwards into space, or inwards into the human biology.

Journey of Learning: Teaching Yourself the Power of EBSD

Shawn Wallace – Applications Engineer, EDAX

The joy of learning is sadly something that many people forget about and some never really feel. One of the things I like to keep in mind when I am learning something new is that learning is usually not a eureka moment, but a process of combining concepts and ideas already known, to reach a new solution or idea. The reason I was thinking about learning as a process is because recently I found myself forgetting that. A customer sample came in that was, for EBSD, hard in every way: Difficult crystal system/orientation, sample prep issues, poor diffractor. With all those factors, the sample was putting up a fight and winning, mainly because I allowed it to. I had tried all my normal tricks and was not making much headway. I knew the sample was analyzable, but I was not treating the process as a personal learning opportunity, instead I was treating it as a fight that I had to win. I was quickly bouncing from potential solution to potential solution and trying them, without spending much time on thinking what would be best to try and how to tackle the problem as a problem, and not a challenge. I didn’t even frame it that way in my own head until a week later when I was visiting a customer site to do some training.

During the training session, a sample came up with a very different set of problems, but still ones that were stymieing us as we sat at the microscope. I found the user resorting to what I had done previously; just try this and see if it works, without thinking about what the best course of action was. As I sat there, I told them to take a step back and evaluate what the issue was and how we could use our knowledge of all the functions available to us in the TEAM™ software and/or our microscope to find a solution. We sat and talked about the issue and the user was able to come up with a game plan and try some things that would help him reach a solution or gain additional knowledge, aka LEARN. I learned that day – that I sometimes need to treat myself the way I would treat a user. There will always be cases when I don’t know the answer and I have to teach myself the solution.

That leads us to an open question. How do you learn EBSD as you go along? With that in mind, here at EDAX we are going to start a new series of blog posts to discuss the basics of EBSD, from pattern formation, the Hough Transform, and finally indexing. More importantly, I hope to touch on how to troubleshoot issues using your newfound understanding of these concepts and tie the entire processes together as they all play off each other.

My final goal is get your creative juices flowing to dive deeper into understanding the kind of questions that EBSD can answer, and how that, in the end, can provide you with an incredible understanding of your analysis challenges and ultimately a solution to the problem. EBSD is one of the most powerful analytical techniques that I know. It can answer the simple questions (what phase is my sample?) to the incredibly complex (if I squeeze my sample this way, which grains will tend to deform first?). As your knowledge grows, EBSD is one step ahead of you, egging you on to learn more and more. I hope to be your guide on this Journey of Learning. I think I will learn quite a bit too.

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).