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Things That Change The Way We Use EDS

Dr. Shangshang Mu, Applications Engineer, EDAX

I got into the EDS world about 10 years ago, when I started my PhD study at Boston University. In my first project, I needed to quantify the elemental composition of my experimental samples. My advisor told me that ideally, we should use an electron microprobe and that the nearest one was at MIT, which is literally on the other side of the Charles River. But after we heard of the hourly fee and estimated the number of samples I would need to analyze, we started to plan an alternative. We found out that there was a field emission SEM equipped with an EDS detector in our own Photonics Center, just across the street and most importantly it was free of charge. At that time, I knew neither microprobe nor EDS and decided to give EDS a try first. Even if it did not work, I had nothing to lose except wasting some time. Graduate students have plenty of time to waste. So finally, I didn’t cross the beautiful Charles River but Commonwealth Avenue for the EDS.

As a result, I was introduced to the EDS world by the EDAX Apollo 40 SDD detector and EDAX was the only EDS manufacturer I knew as a beginner. It is such a good brand name standing for Energy Dispersive Analysis of X-rays so in the first couple of years I was under the impression that it was the term of this technique. For quantitative analysis, I used known standards that were close to my experimental samples in composition to standardize and got pretty good results fast and easy. In the subsequent projects, I collected a lot of EDS maps and the Apollo 40 never disappointed me. Since the EDS detector worked well for my PhD projects, I no longer considered other techniques. By the way, although I missed the opportunity to learn how to use the microprobe across the river due to the budget issue, my first full-time job in the states was to manage a much fancier microprobe acquired by a former user of the MIT’s microprobe. He received his PhD in geochemistry from MIT and I got most of my microprobe skills from him.

As an entry level EDAX user in graduate school, I had no way to imagine that I turned myself into an EDAX applications engineer and right now I am celebrating my one-year anniversary. After I joined EDAX, I got to know that the Apollo was the first generation SDD detector series of EDAX and our current EDS detectors have much better all-around performance. At the beginning of my second year with EDAX, I looked back into the EDS data I collected in graduate school and noticed that they were collected at a much slower amp time (the time the detector processes one X-ray count) compared to current ones and the EDS maps looked kind of noisy in comparison to my current perspective. Prompted by these findings, I wanted to initiate the discussion with how advancements in detector technology shaped the way we use EDS.

Apollo 40 SDD at Boston University
EDAX Octane Elite SDD in Draper, UT
Figure 1. The EDAX Apollo 40 SDD attached to the SEM I used at Boston University (left) and the EDAX Octane Elite SDD I am currently using (right).

 

I believe all EDS users have heard of this rule of thumb: keep the dead time between 20% and 40%, or something like this. At least I was taught to keep the percentage within this range and as far as I know a lot of EDS users are following this rule. This is a traditional perspective that came out in the past when detector amp times were much slower. The dead time is all about throughput and affected by the amp time. Historically, if the dead time is below 20%, it means the detector either doesn’t receive enough X-ray counts per second to ensure high data quality or the amp time is too fast to maintain an optimal detector resolution. On the other hand, if the dead time is over 40%, the Input Counts Per Second (ICPS) is too high to be handled optimally by the current amp time and may lead to excessive summed peaks. We can get the dead time back in the range by either decreasing the beam current to lower the count rate or choosing a faster amp time.

In the past, we usually did not consider the second option since it would sacrifice the detector resolution a lot for throughput. However, the current generation of EDAX EDS detectors is equipped with CMOS based pre-amplifiers that allow much faster amp times ranging from 0.12 μs to 7.68 μs, while keeping very good resolution and high throughput. For example, if I have the EDAX Octane Elite detector in my lab, I can run eight times faster by moving the amp time from the slowest 7.68 μs to the intermediate 0.96 μs, the resolution is only decreased by roughly 4 eV (from 124 eV to 128 eV). This intermediate amp time can handle at least 80% of the job, however under this condition it is hard to make the dead time go over 20% unless the detector is receiving over 100K ICPS. Even if I use the fastest amp time at 0.12 μs, the resolution is still below 150 eV, which is not a significant decrease in resolution if you know that the detector resolution for those equipped with traditional JFET pre-amplifiers is about 250 eV at this fastest amp time. Since resolution is no longer a limiting factor, feel free to open your aperture to increase the count rate and choose a faster amp time to lower the dead time. In return, you will get a higher throughput, which means more statistics and higher quality of data. Although we can go below 20% dead time to have a throughput improvement, it still makes sense to apply the 40% upper bound since the detector will not convert X-rays efficiently once the dead time is beyond this maximum percentage.

When do we want to hit hundreds of thousands of ICPS and take advantage of the fast amp time and high throughput brought by current EDS detectors? While I was using the Apollo 40 at Boston University to collect EDS maps, I stuck to 12.8 μs amp time believing the higher the detector resolution, the better the map quality. Now, I have realized that the major limitation to the quality of EDS maps is not the detector resolution but the limited statistics at the pixel level. Not to mention for our current detectors, the degradation in resolution when running fast is very little. The quality of peak deconvolution is primarily determined by the level of statistics, even when dealing with tricky peak overlaps.

I did a quick study on a piece of floor tile in my lab that contains both calcium phosphate and zirconium silicate, so P and Zr are in distinct phases. P K and Zr L peaks are heavily overlapped with only 29 eV of energy difference. I used the Octane Elite detector to do a quick five-minute net intensity map on this floor tile at 26 nA beam current and 0.96 μs amp time. This combination gave me 160K ICPS and 28% dead time. For the purpose of comparison, I used the slowest amp time at 7.68 μs to yield the highest detector resolution and recollected the maps for 6.5 minutes. To keep the dead time at 28% I had to lower the beam current to 3.2 nA to constrain the ICPS at 20K. Obviously, in the first run Zr and P were separated out nicely in the sharp images (Figure 2 left), as it built up eight times more statistics than the second run in roughly the same amount of time. In the second run at the highest detector resolution, the separation was not quite as good (Figure 2 right). As we can see, the images are kind of pixelated and the coral pixels are mixed within the green in the overlay, so the slightly better detector resolution did not help at all. If I were able to know this trick as a rookie, I would be able to get higher quality maps in the same amount of time or get the same quality of maps faster.

Net intensity maps of P/Zr overlay and P collected at 0.96 μs amp time (left) and 7.68 μs amp time (right) for roughly 5 minutes.
Figure 2. Net intensity maps of P/Zr overlay and P collected at 0.96 μs amp time (left) and 7.68 μs amp time (right) for roughly 5 minutes.

From my point of view, the advancements in detector technology, the experience we gain, or a combination of the two change the way we use EDS.

Texture on the Greens

Matt Nowell, EBSD Product Manager, EDAX

For better or worse, I am a golfer. The story of how I became a golfer helps explain my love for EBSD, and evolution as a material scientist. While I was at the University of Utah trying to decide on a major, I enjoyed fishing. Here in Utah, we have lovely access to many rivers, streams, and lakes with great fishing potential. When I started investigating Materials Science and Engineering as a degree, I thought it would be interesting to learn about the graphite used in fishing rods, and how the different processes used improved the performance of the rods. With this interest, I enrolled in the Materials Science department. Fortunately (for the fish I like to think), two things happened that changed my recreational and professional focus.

Tate Nowell catching a Utah trout

My son catching a nice Utah trout.

First, I enrolled in Organic Chemistry. Memorizing different molecules was not something that I excelled at. This dampened my enthusiasm for all things polymer-based, like composite fishing rods. Second, I was hired to work in the Electron Microscopy lab for the Materials Science department. This gave me lots of direct exposure to SEM, TEM, EDS, and even XRD instruments. It also helped to build a strong appreciation for sample preparation, but that’s the topic for another blog. All these things pushed me in the direction of materials characterization, and when I graduated, it led me to TSL, EDAX, and EBSD.

How does all this relate to golf? Soon after I started working, I played a round of golf with some friends. I had played a few casual rounds over the years, but nothing serious. Looking back, I consider myself lucky because the parking lot for the EM characterization facility was also the parking lot for the University golf course, and if I had been bitten by the golf bug at that point, things might have occurred differently. After this round, which I greatly enjoyed, I went to the local golf store thinking about different golf clubs. I found a set where the shafts of the club were manufactured by the same company that made my favorite fishing rod. This seemed like a sign to me, so I bought the clubs and jumped right into becoming a golfer.

It was great timing. EBSD scans were slow. To collect a 20,000-point scan, which was our typical target at the time, took 5-6 hours. It was easy to fit in 9 holes during some of these scans. Today, with our new Velocity™ cameras, it takes about 5 seconds to collect this data. Sometimes there is barely enough time to hit a practice putt down the hall in the lab. Many of us in the office enjoyed playing together. We even commissioned an annual tournament called the Burrito Open, where we combined golf with Mexican food. If you examine the picture of the 2008 tournament closely, you may notice it is an International event, with participants from Europe (Rene de Kloe) and Japan (Suzuki-san).

2008 Burrito Open

2008 Burrito Open

This tournament also allowed us to indulge and combine golf with work a little bit. The first trophy was constructed from an old port cover we no longer needed. The second trophy was of course a crystal trophy. As you might imagine, there was some discussion over what crystal structure would be most appropriate.

Burrito Open Trophies

Burrito Open Trophies

There is plenty of time to think during a round of golf, and one of the things I’ve thought about is how the club heads are produced. When thinking about this, we are considering either woods (or more accurately metal woods) or irons. Irons are typically either cast or forged. Forged clubs are generally positioned for the better players, but what caught my eye is that some manufacturers started marketing the idea of microstructure and the role of grains in the material. One brand even pushes what they call Grain Flow Forged.

Grain Flow Forged Iron

Grain flow forged iron

Of course, just like the fishing rods, the processing of the club affects the properties. The key link is that the processing changes the microstructure, and the microstructure defines the properties. With that in mind, it’s a fun experiment to compare the microstructure of cast clubs versus forged clubs. Stuart Wright and I first did this experiment about 20 years ago for a conference on Materials in Sports, but given the increases in capability, it would be fun to reevaluate.

I sectioned and prepared EBSD samples from both forged and cast irons. These were both made with an unknown steel alloy and prepared with my standard metallographic preparation approach. Enough coarse-grained polishing was used to remove plating from the club surface. The resulting Image Quality + Orientation Maps (IPF relative to the surface normal direction) are shown below. These were collected from the face of the golf club. I prepared cross-sections for further analysis. I was a little surprised by both microstructures. The cast iron had a dual-component microstructure, with both generally equiaxed grains and needle shaped grain constituents. It looks a lot like a dual phase Ferrite-Martensite microstructure, but with martensite being tricky to directly identify with EBSD relative to ferrite, I indexed both regions with a BCC Ferrite material file. The local misorientations were higher in the needle shaped regions, and there were also some austenitic grains present in these regions. The forged iron microstructure has a bimodal grain size distribution, with larger equiaxed grains decorated and intermixed with smaller equiaxed grains. A second scan was collected at higher magnification and with a finer step size to better resolve these fine grains.

IQ and IPF ND Orientation Map from cast golf club

IQ and IPF ND Orientation Map from cast golf club

IQ and IPF ND Orientation Map from forged golf club

IQ and IPF ND Orientation Map from forged golf club

Higher magnification IQ and IPF ND Orientation Map from forged golf club

Higher magnification IQ and IPF ND Orientation Map from forged golf club

As expected, the microstructures of the forged and cast clubs are different. As a Materials Scientist and EBSD guy, I tend to think forging is a more interesting materials processing option. In this case though, both casting and forging have produced interesting microstructures that could use further investigation. I once bought a set of forged clubs, and it was with this set I made my only hole-in-one. I’m pretty sure there is a direct correlation, and when I buy my next set, I’ll continue my experimentations.

Celebrating Nearly 60 Years of Materials Analysis Expertise with EDAX

Arjun Dalvi, Regional Sales Manager – Southeast Asia and India, EDAX

During a recent trip to Bangkok, Thailand I visited a customer and was very happy to see that two EDAX DX-95 units were installed at his location. The units are a piece of history because EDAX hasn’t sold liquid nitrogen cooled detectors or systems anywhere in the world in quite some time.

When I asked the customer when this system was installed, he said it was installed more than 30 years ago, at a time when I was still in elementary school! EDAX was one of the first companies to produce liquid nitrogen cooled detectors for microanalysis.

EDAX DX-95 EDAX SiLi Detector
EDAX DX-95 (left) and SiLi detector (right) used over 30 years ago.

Since its origin in 1962, EDAX has provided customers with reliable, accurate microanalysis systems. The company has benefitted from its stellar reputation, as well as its, name recognition. The name EDAX almost has a generic trademark, because many people throughout the world refer to their Energy Dispersive Spectroscopy (EDS) systems as “EDAX” systems.

EDAX, a big name in microanalysis and microscopy, has a vast history in research and development of new technology and product improvements. The company has been a part of the AMETEK corporation since 2011. Since joining the well-respected organization of AMETEK, EDAX has been able to pursue new developments in the fields of EDS, EBSD and WDS analysis. After AMETEK acquired a company that produced silicon nitride windows, EDAX gained a great advantage by having an inhouse supplier for its new SDD window. This was a big revolution for EDAX’s EDS products. Now, EDAX is the only manufacturer that has a unique silicon nitride window with vacuum encapsulation technology. EDAX has become one of the top manufacturers of EBSD systems, providing solutions to various applications in the fields of microstructure and formation and deformation of new materials. The new CMOS-based Velocity™ EBSD Camera is the fastest EBSD camera on the market for high-speed EBSD mapping. In India, we have many users that have EBSD systems and are doing research in the fields of steel and metals.

Today, EDAX has a complete range of products with all the latest developments and inhouse raw materials needed to help us maintain quality and add to our customers’ confidence in our products.

I feel EDAX will come up with new developments for years to come. Maybe 30 years or more down the road, we will see the Element, Octane Elect, Octane Elite or Orbis at one of our customers sites, much like the DX-95, which is still in use today.

Saying What You Mean and Meaning What You Say!

Shawn Wallace, Applications Engineer, EDAX

A recent conversation on a list serv discussed sloppiness in the use of words and how it can cause confusion. This made me consider that in the world of microanalysis, we are not immune. We are probably sloppiest with two particular words. They are resolution and phase.

Let us start with how we use the word phase and how phases are commonly defined in microanalysis. In Energy Dispersive Spectroscopy (EDS), we use phase for everything, for example, phase mapping, phase library. In Electron Backscatter Diffraction (EBSD), the usage is a little more straightforward.

So, what is a phase? Well to me, a geologist, a phase has both a distinct chemistry and a distinct crystal structure. Why does this matter to a geologist? Two different minerals with the same chemistry, but with different structures, can behave in very different ways and this gives me useful information about each of them.
The classic example for geologists is the Al2SIO5 system (figure 1). It has three members, Kyanite, Sillimanite, and Andalusite. They each have the same chemistry but different structures. The structure of each is controlled by the pressure and temperature at which the mineral equilibrated. Simple chemistry tells me nothing. I need the structure to tease out that information.

Figure 1. Phase Diagram of the Al2SiO5 system in geological conditions. Different minerals form at different pressures and temperatures, letting geologists know how deep and/or the temperature at which the parent rock formed.**

EDS users use the term phase much more loosely. A phase is something that is chemically distinct. Our phase maps look at a spectrum pixel by pixel and see how they compare. In the end, the software goes through the entire map and groups each pixel with like pixels. The phase library does chi squared fits to compare the spectrum to the library (figure 2).

Figure 2. Our Spectrum Library Match uses as Chi-squared fit to determine the best possible matches. This phase is based on compositional data, not compositional and structural data.

While the definition of phase is relatively straight forward, the meaning of resolution gets a little murkier. If you asked someone what the EDS resolution is, you may get different answers depending on who you ask. The main way we use the term resolution when talking about EDS is spectral resolution. This defines how tight the peaks in a spectrum are (figure 3).

Figure 3. Comparison of EDS vs. WDS spectral resolution. WDS has much higher resolution (tighter peaks) than EDS, but fewer counts and more set-up are required.

The other main use of resolution, in EDS is the spatial resolution of the EDS signal itself (figure 4). There are many factors which determine this, but the main ones are the accelerating voltage and sample characteristics. This resolution can go from nanometers to microns.

Figure 4. Distribution of the electron energy deposited in an aluminum sample (top row) and a gold sample (bottom row) at 15 kV (left column) and 5 kV (right column). Note the dramatic difference in penetration given by the right hand side scale bar.

The final use of resolution for EDS is mapping resolution. This is by far the easiest to understand. It is just the step size of the beam while you are mapping.

Luckily for us, the easiest way to find out what people mean when they use the terms resolution or phase, is just to ask. Of course, the way to avoid any confusion is to be as precise as possible with your choice of words. I resolve to do my part and communicate as clearly as I can!

** Source: Wikipedia

Old and New Faces

Dr. Jens Rafaelsen, Applications Engineer, EDAX

While I haven’t been around in the microscopy and microanalysis world in a professional sense for too long, it’s hard not to notice how often the faces stay the same but the title on the name tag or the company logo changes. Just to name a few from the EDAX side, Patrick Camus (Director of Engineering) used to work in applications for Noran, John Haritos (Southwest Region Sales Manager) came from Oxford, Sophie Yan (Applications) came from Zeiss, and Dave Durham (Western Region Sales Manager) came from Bruker.

Though microanalysis is a big field, it’s a small world once you get into the commercial side of it. I guess it shows that there are not too many of us that really have the deep level of interest and dedication to stay in field and the ones that do are often in short supply. While some of the changes could be a case of the grass being greener on the other side, it often seems to be driven by the desire for a career step or for personal reasons. The interesting part is that I have very rarely seen anyone hold a grudge or perceive a move to another company in the field as something negative.

Applications Engineer, Shangshang Mu

Applications Engineer, Shangshang Mu

Every year it seems like a couple of the old faces retire (though they often still show up at M&M, often wearing their last company shirt), but you start to recognize the rest of them despite any changes in affiliation. This makes it a little easier to identify the new faces and with that, I would like to introduce the newest one at EDAX: Shangshang Mu (pronounced Shong-shong) recently joined us as an applications engineer and will be based in our Draper, Utah office. He holds a PhD in Earth Sciences from Boston University and was most recently lab manager at Southeastern North Carolina Regional Microanalytical and Imaging Consortium. At EDAX, we are excited to have him on board and look forward to the rest of you getting to know him.

There’s A Hole in Your Analysis!

Dr. René de Kloe, Applications Specialist EDAX.

EBSD analysis is all about characterizing the crystalline microstructure of materials. When we are analyzing materials using EBSD the goal is to perform a comprehensive analysis on the entire field of interest. We strive to obtain the highest possible indexing rates and when we happen to misindex points we feel compelled to replace or clean these with other “valid” measurements that we simply copy from neighbor points so we do not have to show these failures in a report or paper.

But what should we do when we don’t expect data from specific spots in the first place? For example if a sample is porous or contains non-crystalline patches, or perhaps we have phases that don’t produce patterns? Then we typically simply try to ignore that. We may perhaps state that a certain fraction of our scan field refuses to produce indexing results and show which pixels these are, but that’s about it.

Pearlitic cast iron with graphite nodules - 13.5% graphite.

Figure 1: Pearlitic cast iron with graphite nodules – 13.5% graphite.

And that is strange as such areas where we don’t expect patterns are truly an integral part of a material and as such should also be characterized for a complete microstructural description. A traditional example of such a material is a cast iron which, although not porous, contains graphite inclusions which typically do not produce indexable EBSD patterns (Figure 1). Another example is the characterization of material produced by 3D printing of different metals, where small metal particles are sintered together using localized laser heating. This process doesn’t generate a fully dense product (Figure 2) and understanding the pore structure is important in predicting its mechanical response to stressed conditions.

Figure 2: Porous 3D printed steel - Indexing success 97.2%

Figure 2: Porous 3D printed steel – Indexing success 97.2%

Analyzing the non-indexed areas creates some challenges for the data treatment, especially any cleanup that you may want to do. You need to be careful to ensure that individual misindexed points, for example along grain boundaries or inside grains are not considered as pores. For a full analysis we need to be able to treat pore spaces as a special type of grain. Not one where pixels are grouped together based on similarity in measured orientation, but just the opposite, where pixels are combined based on misfit. This poses a special challenge on cleaning your data. When a typical clean-up acts like an in-situ grain growth experiment, where grains are expanded to consume bad points, in porous materials data cleanup needs to be done carefully to prevent the real grains from growing into real non-indexed spaces.

In general, EBSD data cleanup should be done in 3 steps:
1. Identify the good points,
2. Preserve the good points
and only then
3. Replace bad points.

For steps 1 and 2 we can use the patented Confidence Index in the OIM™ Analysis software. For step 1 we setup a filter to allow only correctly indexed points (typically with CI>0.1). However, this may remove too many points along grain boundaries, for example, where patterns overlap and indexing is uncertain. In step 2 we apply a confidence index standardization to retrieve all pixels that were indexed correctly, but had a low CI value and were excluded in step 1. This step assumes that if the orientation of a pixel matches that of adjacent pixels that had a high CI value, it was correctly indexed and needs to be included. This step does not change any measured orientations.

In step 3 we must be more careful as it is easy to accidentally replace too many points and shrink the non-indexed space (Figure 3):

Figure 3: Effect of too rigorous cleanup of partially crystalline material - Cu interconnects.

Figure 3: Effect of too rigorous cleanup of partially crystalline material – Cu interconnects.

A cleanup method that verifies whether a minimum number of neighboring points belong to a single grain such as the neighbor orientation correlation, is preferred.

Now that we know where the holes in the material are, we can get serious about analyzing them. First we need to define our real grains. Grains in EBSD analysis are defined by groups of points with similar orientations and a minimum number of pixels, for example maximum point to point misorientation less than 5 degrees and minimal 3 pixels in size. When you remove these grains from your partition, the left over pixels that do not fit into the grains can now be recognized. Coherent clusters of these misfit pixels are then grouped together into what might be called antigrains (Figure 4).

Figure 4: Grain and antigrain definition.

Figure 4: Grain and antigrain definition.

But even when the pores are recognized this way, the antigrains are not characterized by their orientation and as such their boundaries will do not show up in a traditional misorientation boundary overlay, which only shows the misorientation between recognized grains (Figure 5a). In order to make the antigrains visible as well, a boundary type that does not use misorientation as a criterion, but rather the position of triple junctions, needs to be selected. Between the triple junction nodes, vectors that follow all grain and antigrain interfaces are then constructed (Figure 5b).

a) Standard grain boundary overlay on IQ map based on grain orientation recognition. Non-indexed areas are white. b) IQ map with reconstructed boundaries including the antigrain edges.

Figure 5a) Standard grain boundary overlay on IQ map based on grain orientation recognition. Non-indexed areas are white. b) IQ map with reconstructed boundaries including the antigrain edges.

Once the antigrains are fully defined, all normal grain characterization tools are also available to describe the pore properties ranging from a basic size distribution (Figure 6) to a full analysis of the pore elongation and alignment (Figure 7).

Pore size distribution with colored highlighting in 3D printed iron sample.

Figure 6: Pore size distribution with colored highlighting in 3D printed iron sample.

Figure 7: Alignment of pore elongation direction.

Figure 7: Alignment of pore elongation direction.

With non-indexed points now properly assigned into antigrains, a full microstructural description of not fully dense materials or materials containing areas that cannot be indexed, is possible.

Finally we can do a (w)hole EBSD analysis.

Working for EDAX is working in a different world

René Jansen, Regional Manager EDAX EMEA, Managing Director Ametek BV

How difficult is it to explain to your friends and relatives what you are doing during the week? Microscopes, detectors and analysis materials are not things that usually ring a bell with your family, friends and neighbors. “It is all scientific and we do not understand any of it”, is the usual response to our descriptions of what we do.

We at EDAX spend most of our time on our job and on the road. For most of us, this can only happen when our families support us by letting us travel the globe.

In an attempt to overcome this gap in understanding our “world”, I thought it would be worthwhile to organize an event where everybody at EDAX in The Netherlands could invite their family and friends to our lab and show them what we do in our world. Initially, I didn’t anticipate that there would be a lot of interest in this event, but I soon found out that close to 40 people were interested in coming.

The event took place on Sunday May 18th at the EDAX facility in Tilburg, The Netherlands, where we usually have 6 employees working.  In the afternoon people were flabbergasted by René’s and Harry’s impressive demonstrations.  In no time family heirloom jewelry moved into the chamber in order to determine if the pearls were real or not (they were!). Someone else had a silver spoon, which had turned partly yellow after several times in a dish washer. What had happened to his spoon? Within 10 minutes René explained that the oxygen traces indicated corrosion, which had pushed the silver plating off to display the brass material underneath. Harry had a challenge to determine what an onion consists of. It turned out to be quite healthy thanks to several trace elements of metal.

At the end of the afternoon everybody went home satisfied with what they had learned and they had concluded that the world of EDAX is indeed very different and also very interesting. Now when we leave for work in the morning, we see in the faces of our family that think that we are going out to do a “good job” for our world and this is nice to know.