Month: December 2021

What’s New in APEX 2.2 for EDS

Dr. Shangshang Mu, Applications Specialist, EDAX

Last year we released APEX 2.0 software, which had grown considerably into a more complete microanalysis package to offer both Energy Dispersive Spectroscopy (EDS) and Electron Backscatter Diffraction (EBSD) characterization capability. APEX 2.1 was delivered earlier this year to include support for dual EDS detectors on the EDS side. Towards the end of this year, we added another major feature, Full Standards Quant, and multiple other new functionalities with the release of APEX 2.2. APEX 2.2 has been out for more than a month, and many users have enjoyed the higher-level features and enhancements brought by the latest release. In this blog post, I will go over what is new in APEX 2.2 for EDS.

Spectrum and Image Annotation

With the new floating Annotation Toolbar, the user can easily add text and shapes in images and spectra. A ruler option is available to measure any feature in the image, and the measurement is saved with the image. All of the annotations can be edited or deleted after creation. Annotations are saved with HDF5 files and included in the report. Spectra can be saved as images with annotations.

Figure 1. left) Floating toolbar and annotations in the spectrum. right) Annotations in the SEM image.

Spectrum Normalization

Previously, multiple spectra were normalized with respect to the highest energy peak by default. The new Spectrum Normalization feature gives the user more flexibility. The spectra can be normalized based on any peak by selecting the region or element or drawing in the spectrum overlay. The ratio information is shown on the overlay, and the normalized energy range is displayed in the report.

Figure 2. Spectra normalized with respect to the Si K alpha peak. The ratio information is shown at the top-right corner.

Quant Montage Maps

In APEX 2.0, Montage mapping was released as a key feature that allows precise large-area imaging and EDS and EBSD mapping. It uses stage movements to collect individual high-resolution images and maps through a grid pattern over a large sample surface and stitches them into montages. In APEX 2.2, we took one more step forward, and now the user can rebuild Montage maps as NET and ZAF (Wt% and At%) maps. The workflow is the same as rebuilding single-field EDS maps for ease of use.

Full Standards Quant

The most exciting new functionality in this release is Full Standards Quant. We calculate a unique reference value from a single element standard spectrum to determine the product of the beam current and detector solid angle. The reference value will be burned with every subsequent spectrum collected at the given parameters. It normalizes out any differences in beam current and detector geometry. As long as the standard and unknown spectra were collected at the same accelerating voltage, the standard can be applied to quantify the unknown sample. There are three modes available in Full Standards Quant. The Standard mode is suitable for those users who want to take complete control of the standard selection. The MultiStandards mode uses the mean values of the loaded standards. The SmartStandards mode is an intelligent approach that automatically picks the best fitting standards using an iterative internal assessment algorithm. The Full Standards Quant chart (Figure 3) gives a visual representation of how close your standards are to your unknown. It also generates a curve to show the calculated element concentration versus net counts based on the loaded standards.

Figure 3. Full Standards Quant chart of Si K. The yellow diamonds show standards, and the “X” indicates the unknown sample. The calculated curve gives the element concentration versus net counts based on the loaded standards.

APEX 2.5 with new features and productivity enhancers for EDS and EBSD is on the horizon in 2022, followed by more integrations in the APEX platform. As always, minor version upgrades of APEX are free, so experience the power of APEX 2.2 now and prepare for the benefits of APEX 2.5 soon. It will be an exciting year for APEX!


Dr. René de Kloe, Applications Specialist, EDAX

After finishing my Ph.D. in structural geology at Utrecht University, I joined EDAX in 2001 to become an EBSD Application Specialist. At the time, I expected that my experience with investigating microstructures of rocks would be equally applicable to metals and ceramics. After all, grains are grains, and deformation structures in rocks and ceramics are not all that different. At least, that was my impression when I visited the International Microscopy Conference (IMC14) in Cancun, Mexico, in 1998. My poster on melt and deformation microstructures in partially molten olivine-orthopyroxene rocks was the only geological contribution in a metallurgical section. At first glance, nobody even noticed that my TEM images were not on metal, and I had many interesting discussions on potential deformation mechanisms and how metallurgists and geologists could work together and learn from each other.

Quickly after joining EDAX, I recognized that there is a fundamental difference between the work of a material scientist and that of a geologist. To generalize, a material scientist works on developing materials like metal alloys or ceramics for a specific application and typically has a pretty good idea of what kind of processing has been applied to a material. As a geologist working with natural rocks, you have to work with the material and try to unpick its formation history that may span millions of years by observations alone. This turned out to be a helpful skill in looking at customer samples that have come my way over the years. In many cases, I only have very limited information on the background of a sample. Then, I have to rely on my observations to unravel the sequence of events and select the analytical options for the successful characterization of the microstructure. Observing materials without assuming that you know what happened allows you to catch unexpected events in production processes, and that makes a very useful connection between characterizing materials in geology and materials science.

For example, during a recent training course, we worked on a stud welded sample. This was a new technique for me, and a first-practice EBSD map showed a very interesting microstructure. We used that map during the training, but since then, I have taken the time to do a complete characterization to see if I could identify what really happens during these short milliseconds that it takes to weld a stud to a substrate.

Online, I found a general description of the welding technique (Figure 1). In the stud welding process, an electrical arc is generated between the tip of the stud and the substrate so that a small melt pool forms at the contact. The stud is then plunged into the melt pool, which solidifies within milliseconds, creating a strong bond. Can we use EBSD to tell us what really happens?

Figure 1. Stud welding procedure, 1) The stud is placed close to the substrate. 2) An electric arc is created to melt the contact area on both sides. 3) The stud is pushed into the melt pool. 4) After a few ms of cooling time, the weld is complete.

And I start just like I would when looking at a rock outcrop. First, take a step back and look at the entire structure. Once we have seen that, we can zoom in on key areas to investigate what has happened.

The SEM image (Figure 2) does not clearly show how large the area affected by the welding process is in the cross-section. The expected microstructural changes can be illustrated using an EBSD Image Quality (IQ) map. An IQ map shows the contrast of the bands in the diffraction patterns where recrystallized areas with good quality patterns are bright. In contrast, deformed areas producing poor quality patterns appear dark. Therefore, any changes in the crystalline microstructure are likely to be clearly visible in the EBSD results.

Figure 2. a) The polished sample in 3 cm resin mount. b) An SEM secondary electron montage image of the stud weld contact. (1806 fields, 15.7 x 10.7 mm)

Before we look at the weld structure itself, we need to check the starting microstructure of the base materials to recognize what changes during welding. The threaded stud on top consists of deformed austenitic steel. At the top of the IQ map (Figure 3a), individual grains can be seen along the stud’s center axis. With increasing deformation towards the threads, the grains become smaller and EBSD patterns degrade, resulting in very dark IQ values at the stud surface.

Figure 3. a) An IQ map and b) a phase map of a montage EBSD scan with 221 fields, 45 million points @ 1.5 µm steps. Red is ferrite and green is austenite. c) An IPF map on IQ showing the crystal directions parallel to the sample normal direction. The scalebar is 4 mm.

This structure is related to the wire drawing of the stud and the shaping of the threads.
The ferrite substrate appears homogeneous with an equiaxed grain structure and consistently good quality patterns. However, the change in color from green to purple in the IPF map (Figure 3c) shows a gradient in the dominant grain orientation distribution towards the interface. This does not appear to be related to the welding process and is probably introduced during the production of the ferritic steel sheet. The welding process dramatically changes the IQ appearance of both the stud and the substrate (Figure 3a). In the welding zone, the austenitic material becomes bright while the ferrite goes very dark. Between these two areas, a band of material is present that has been melted and then quickly solidified. In this solidified material, there are swirls of darker IQ values that appear indicative of the melt’s movement during the plunge phase when the stud gets pushed into the melt pool. The EBSD phase map in Figure 3b indicates that these darker bands in the melted zone consist of ferrite grains. The main components of the weld zone are shown in Figure 4.

Figure 4. A weld structure IQ map with the main structures indicated.

To see what causes these changes in the IQ map, we have to look more closely at the EBSD results. The bright IQ band in the austenite stud consists of small equiaxed grains that are fully recrystallized and produce good quality patterns (Figure 5, 6a).

Figure 5. An EBSD montage map of the entire weld zone, IPF on IQ map, 133 fields and 91M points @ 750 nm steps. The scalebar is 4 mm.

Figure 6. a) A detailed IPF on PRIAS center map of the recrystallized austenite layer. b) An IPF on PRIAS center map showing the columnar austenite grains crystallized from the former melt pool.

This structure suggests that the temperature in this band has been high enough to allow recrystallization of the deformed structure. Still, the metal remained solid and cooled down too fast to enable significant grain growth.

The fine-grained austenite microstructure is in stark contrast to the area that has been melted. Atomic movements in the melt were so fast that upon cooling, very large columnar grains could form in two bands with a seam in the middle (Figure 6b). This double band structure indicates solidification that started on both sides of the melt pool on the solid metal surfaces until the grains met in the middle.

The structure on the ferrite side is more complex. In the middle of the weld contact, a triangular area of apparent columnar grains has formed with a void at the bottom tip (Figure 7). Underneath these larger grains is a fine-grained band over the full width of the weld. In both zones, the EBSD patterns have deteriorated compared to the original ferrite matrix structure.

Figure 7. An IPF on PRIAS center map showing only the ferrite phase.

The substrate’s ferrite structure has a complicating factor when compared to the austenitic steel stud. When ferrite is heated close to the melting temperature, the crystal structure changes into that of austenite. This means that the columnar grains in the ferrite’s center area actually crystallized from the melt pool as large austenite grains, similar to those shown in Figure 6b. However, in this case, the austenitic crystal structure is not stable at room temperature, and upon cooling, these grains changed back into ferrite. This back transformation does not simply change the structure of the entire grain into the ferrite structure. Instead, it creates organized clusters of ferrite grains with different “child” orientations inside each original austenite grain. At low magnifications, these clusters give the impression of columnar grains with a single orientation. In reality, each column may contain many small grains with up to 12 different orientations (Figure 8).

Figure 8. A close up of the columnar grains in the ferrite area.

Below the melt pool, the original small ferrite grains also transform into austenite during the welding process, but the temperature does not get high enough to enable significant grain growth while the metal remains solid (Figure 9). When these small austenite grains transform back into ferrite during cooling, the original grains also get split up into many small ferrite children, which are a little deformed. That is what causes the dark appearance of this zone in the IQ map in Figure 3a.

Figure 9. An IPF on PRIAS center map of the fine-grained ferrite zone below the melt pool.

The latest version of OIM Analysis™ contains a new tool to investigate this phase transformation from high-temperature austenite into the low-temperature ferrite phase. The clusters of child ferrite grains can now be fit together into the original high-temperature austenite structure that was present during (weld) processing. This is extremely helpful in understanding the contact between the ferrite substrate and the crystallized melt pool.

The EBSD map in Figure 10a shows the compound columnar grains in the ferrite substrate with the two bands of columnar grains that were formed from the melt on top. There is no obvious microstructural correlation between the ferrite and the first layer of columnar grains from the melt in this image. However, when the high-temperature austenite microstructure is reconstructed, the columns in the ferrite substrate coalesce into single austenite grains that match the bottom layer’s orientation perfectly.

Figure 10. An IPF map of the ferrite-melt contact zone. a) The microstructure as measured and b) the microstructure after reconstruction of the high-temperature austenitic microstructure. The scalebar is 1 mm.

This means that these columnar grains grew continuously from the melt at high temperature when the weld was formed then separated into the fragmented ferrite structure and intact austenite structure upon cooling. The exact location of this boundary between the final ferrite and austenite phases is determined by the chemical composition, especially the Ni content (Figure 11). The ferrite substrate has little Ni, which causes the austenite to transform back into ferrite upon cooling.

Figure 11. A simultaneously collected EDS map for Ni. The scalebar is 1 mm.

Figure 12. An IQ detail map of the left melt pool, 2.5M points @ 1.5 µm steps. The scalebar is 900 µm.

Finally, the Ni distribution in the melt pool also explains the occurrence of the dark bands or swirls in the IQ map in Figure 12. When the stud was pushed into the melt pool, the melt fractions from the stud and ferrite substrate mixed, but not thoroughly. On the left side, an area that is somewhat depleted in Ni can be recognized in the melt pool, and where the Ni content drops below a threshold, these portions of the austenite grains that grew from the melt are not stable and transform into ferrite (Figure 13).

Figure 13. a) A phase map of the left melt pool area. Green is austenite and red is ferrite. b) An IPF on PRIAS center map of the left melt pool as measured. The scalebar is 900 µm.

The parent grain reconstruction (Figure 14) confirms that all the small ferrite grains exhibit orientations derived from the coarse austenite grain structure.

Figure 14. An IPF on PRIAS center map after parent grain reconstruction.

Just like the investigation of natural rocks, a detailed analysis of the microstructure of a metallurgical sample like this weld contact can provide a comprehensive image of the active microstructural processes with only minimal prior knowledge. Starting with an overview of the entire sample, followed by targeted scans of distinct parts of the microstructure using EBSD and EDS, a timeline of events can be reconstructed that produced a strong bond between two materials.

And what does it matter if the creation of a structure takes milliseconds or perhaps many millions of years? In the end, everything is connected.