EDS Detectors

Caveat Emptor – Especially with Microanalysis Samples

Matt Nowell – EBSD Product Manager, EDAX

My wife tells me I’m a bit of a hoarder. As we have done our spring cleaning, I’ve found coasters of places I’ve dined around the world, shirts a size (or more) smaller that I haven’t worn in years, and 2 Lego minifigures I bought and forgot to give to the kids. I’ve been forced to admit I didn’t need to keep all this any longer. Of course, as someone who develops and demonstrates EDS and EBSD microanalysis tools, the one thing you can never have too much of is interesting samples. I have drawers full of samples I’ve analyzed, or hope to analyze, and they come in handy when someone wants an interesting example for a customer or presentation.

With that in mind, I’d like to describe my adventures with a new sample I obtained this year. I found a bracelet online that claimed to have 62 elements. To me, that seemed wonderful, and potentially a great sample for EDS and EBSD analysis. I ordered one, and anxiously awaited its delivery.

When it arrived, and I opened it, I immediately became a bit suspicious. For the size and volume of material, it felt very light. I have a set of metal coupons that are all the same size but different alloys and materials, and there is a significant different in feel between different alloys. I guessed it was aluminum, but would use EDS and EBSD to determine the composition.

It was an interesting characterization problem though – potentially it contained 62 elements, but I didn’t know the concentration or spatial distribution of these elements. I started with EDS, and used my Octane Elite EDS detector. Initially I set up the SEM for 20kV analysis, with ≈15kcps output through the detector with ≈ 30% deadtime. Under these conditions, the resolution of the EDS detector was 122.8eV. I imaged a 600µm x 800µm area of the bracelet, and collected EDS spectra for 1, 10, 100, 1000, and 10,000 seconds. The signal to background increases as the square of the time collected, so for each 10X increase, I expected to improve the detection by about a factor of 3.

Figure 1. EDS Spectra collected for 10,000 Live Seconds

Figure 1 shows the EDS spectra collected for 10,000 live seconds. With careful review and analysis, I was able to identify 22 of the possible 62 claimed elements. Aluminum had the largest peak, and had the highest concentration. Of course, I knew I was only sampling the surface, and made no attempt to section into the sample. There was also a strong oxygen peak, which I would attribute to an oxidation layer. Most other detectable elements were present in smaller concentrations. Figures 2 and 3 show an energy range between 7.75eV – 9.00 eV, where the k-line peaks for nickel, zinc, and copper are present, for 10 and 10,000 live seconds of collection. These elements were selected because they were present in low concentrations. At 10 live seconds, these peaks are very noisy but present, and additional collection time significantly improves their distribution shape and counting statistics.

Figure 2. EDS Spectra collected for 10 Live seconds with 15kcsp output

Figure 3. EDS Spectra collected for 10,000 Live Seconds with 15kcsp output

Knowing that better counting improves lower limits of detection, I increased the beam current on the SEM to obtain ≈215kcps output counts, and then collected spectra over the same time intervals.* Figure 4 shows the collection under these conditions after 10,000 live seconds. I should note that while I analyzed the same size area, I did not analyze the exact same area, so it is possible any variations could be due to this approach.

Figure 4. EDS Spectra collected for 10,000 Live Seconds with 215kcps output

At this point, I had a lot of data, but increasing the count rate did not reveal any more elements than were initially detected. To evaluate performance, I quantified each spectra, and focused my analysis on the nickel, zinc, and copper elements. The weight percentage of each of these elements is shown in Figure 5 for each collection time and count rate. Each element has the same color (blue for Nickel, red for Zinc, and black for Copper), the lower count rate lines have a marker, while the higher count rate lines do not.

Figure 5. Weight percentage of selected elements as a function of acquisition time and output count rate

To me, this data was very impressive. Except for the 1 and 10 live second collections at the lower output count rate, the consistency of the data was good, even with concentrations of less than 1 weight percentage. The quantification output does give an error percentage value, and rule-of-thumb acceptance criteria was met after 100 live seconds collection at the lower count rate and 10 live seconds collection at the higher count rate. The fact that I continued to collect data for significantly longer times past this point would suggest that the remaining elements are either not-present, not at the surface where I am analyzing, or are present at concentrations lower than my detection limits.

I also wanted to look at this sample structurally, hoping for an interesting multiphase sample with pretty microstructures I could hang in the hall. I sectioned the sample, and polished a portion for EBSD analysis. The PRIAS + IPF Orientation map is shown in figure 6. I was able to index 99.7% of the collected points with high confidence using the aluminum FCC material file. It has a very large grain structure. I did see a number of smaller Fe precipitates, but I have not examined at higher magnification yet.

Figure 6. PRIAS + IPF Orientation map .

All in all, it didn’t turn out to be the sample I had hoped for, but was good to help think about collecting EDS data for both accuracy and sensitivity. I’ll have to share the sample with other colleagues for WDS and µXRF analysis to see if we can find more of these missing elements.

For more information on quantative analysis with EDS, join our upcoming webinar, ‘Practical Quantitative Analysis – How to optimize the accuracy of your data’. Please click here to register.

Considerations for your New Year’s Resolutions from Dr. Pat

Dr. Patrick Camus, Director of Research and Innovation, EDAX

The beginning of the new calendar year is a time to reflect and evaluate important items in your life. At work, it might also be a time to evaluate the age and capabilities of the technical equipment in your lab. If you are a lucky employee, you may work in a newly refurbished lab where most of your equipment is less than 3 years old. If you are such a fortunate worker, the other colleagues in the field will be envious. They usually have equipment that is much more than 5 years old, some of it possibly dating from the last century!

Old Jalopy circa 1970 EDAX windowless Si(Li) detector circa early 70’s

In my case, at home my phone is 3 years old and my 3 vehicles are 18, 16, and 3 years old. We are definitely evaluating the household budget this year to upgrade the oldest automobile. We need to decide what are the highest priority items and which are not so important for our usage. It’s often important to sort through the different features offered and decide what’s most relevant … whether that’s at home or in the lab.

Octane Elite Silicon Drift Detector 2017 Dr. Pat’s Possible New Vehicle 2017

If your lab equipment is older than your vehicles, you need to determine whether the latest generation of equipment will improve either your throughput or the quality of your work. The latest generations of EDAX equipment can enormously speed up throughput and the improve quality of your analysis over that of previous generations – it’s just a matter of convincing your boss that this has value for the company. There is no time like the present for you to gather your arguments into a proposal to get the budget for the new generation of equipment that will benefit both you and the company.
Best of luck in the new year!

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.

“It’s not the size of the dog in the fight, it’s the size of the fight in the dog.” (Mark Twain)

Dr. Oleg Lourie, Senior Product Manager, EDAX

San Javier, Spain, October 18, 2015: Airbus A400M airlifter escorted by Sains Patulla Aguila squad on their 30th anniversary celebration event.

Many of us like to travel and some people are fascinated by the view of gigantic A380’ planes slowly navigating on tarmac with projected gracious and powerful determination. I too could not overcome a feel of fascination every time I observed these magnificent planes, they are really – literally big..  The airline industry however seems to have a more practical perspective on this matter – the volume of the A380s purchase is on decline and according to the recent reports Airbus is considering reducing their production based on growing preference towards smaller and faster airplanes. Although the connection may seem slightly tenuous,  in my mind I see a fairly close analogy to this situation in EDS market, when the discussion comes to the size of EDS sensors.

In modern microanalysis where the studies of a compositional structure rapidly become dependent on a time scale, the use of the large sensors can no longer be a single solution to optimize the signal. The energy resolution of an EDS spectrometer can be related to its signal detection capability, which determines the signal to noise ratio and as a result the energy resolution of the detector. Fundamentally, to increase signal to noise ratio one may choose to increase signal, or number of counts, or as alternative to reduce the noise of the detector electronics and improve its sensitivity. The first methodology, based on larger number of counts, is directly related to the amount of input X-rays determined by a solid angle of the detector, and/or the acquisition time. A good example for this approach would be a large SDD sensor operating at long shaping times. A conceptually alternative methodology, would be to employ a sensor with a) reduced electronics noise; and b) having higher efficiency in X-ray transmission, which implies less X-ray losses in transit from sample to the recorded signal in the spectra.

Using this methodology signal to noise ratio can be increased with a smaller sensor having higher transmissivity and operating at higher count rates vs larger sensor operating at lower count rates.

To understand the advantage of using a small sensor at higher count rates we can review a simple operation model for SDD.  A time for a drift of the charge generated by X-ray in Si body of the sensor can be modeled either based on a simple linear trajectory or a random walk model. In both cases, we would arrive to approximate l~√t dependence, where l is the distance traveled by charge from cathode to anode and t is the drift time. In regard to the sensor size this means that a time to collect charge from a single X-ray event is proportional to the sensor area. As an example, a simple calculation with assumed electron mobility of 1500 cm2/V-1s and bias 200 V results in 1 µs drift time estimate for 100 mm2 and 100 ns drift time for 10 mm2 sensors. This implies that in order to collect a full charge in a large sensor the rise time for preamplifier needs to be in the range of 1 µs vs 100 ns rise time that can be used with 10 mm2 sensor.  With 10 times higher readout frequency for 10 mm2 sensor it will collect equivalent signal to a 100 mm2 sensor.

What will happen if we run a large sensor at the high count rates? Let’s assume that a 100mm2 sensor in this example can utilize the 100 ns rise time. In this case, since the rise time is much shorter than the charge drift time (~1 µs), not all electrons, produced by an X-ray event, will be collected. This shortage will result in an incomplete charge collection effect (ICC), which will be introducing artifacts and deteriorating the energy resolution. A single characteristic X-ray for Cu (L) and Cu Kα will generate around 245 and 2115 electrons respectively in Si, which will drift to anode, forced by applied bias, in quite large electron packets.  Such large electron packets are rapidly expanding during the drift with ultimately linear expansion rate vs drift time. If the rise time used to collect the electron packet is too short, some of the electrons in the packet will be ‘left out’ which will result in less accurate charge counting and consequently less accurate readout of the X-ray energy. This artifact, called a ‘ballistic deficit’ (BD), will be negatively affecting the energy resolution at high count rates. It is important to note that both ICC and BD effects for the large sensors are getting more enhanced with increasing energy of the characteristic X-rays, which means the resolution stability will deteriorate even more rapidly for higher Z elements compare to the low energy/light elements range.

Figure 1: Comparative Resolution at MnKa (eV).

Figure 1: Comparative Resolution at MnKα (eV) *

As the factual illustration to this topic, the actual SDD performance for sensors with different areas is shown in the Fig. 1. It displays the effect of the acquisition rates on the energy resolution for the EDS detectors having different sensors size and electronics design. Two clear trends can be observed – a rapid energy resolution deterioration with increase of the sensor size for the traditional electronics design; and much more stable resolution performance at high count rates for the sensor with new CMOS based electronics. In particular, the data for Elite Plus with 30 mm2 sensor shows stable resolution below 0.96 µs shaping time, which corresponds to >200 kcps OCR.

In conclusion, conceptually, employing a smaller sensor with optimized signal collection efficiency at higher count rates does offer an attractive alternative to acquiring the X-ray signal matching the one from large area sensors, yet combined with high throughput and improved energy resolution. Ultimately, the ideal solution for low flux applications will be a combination of several smaller sensors arranged in an array, which will combine all the benefits of smaller geometry, higher count rates, higher transmissivity and maximized solid angle.

* SDD performance data courtesy of the EDAX Applications Team.

Return Ticket from the East Coast to East Asia

Dr. Jens Rafaelsen, Applications Engineer, EDAX

Figure 1

As I write this I am on my way back to the US after having spent the past week in Singapore with my schedule filled with meetings and training sessions with both local microscope vendors and for customers, and discussions with the EDAX sales and applications people from China, India and Singapore. A good amount of time was spent discussing detector specifics and how to really make the advantages of our silicon nitride window and Elite detectors shine, but there was also general knowledge transfer and comparison between the challenges that we see in the different regions.

Singapore is definitely a change from the east coast of the United States, with the tropical climate and architecture including a sky-rise hotel with a ship parked on top, buildings with the exterior designed to look like the shell of the Durian fruit, or giant steel tree structures in the middle of the city park. But it is also a central hub where we have one of our regional offices and a state that invests heavily in the knowledge industry.
Figure 2
While the primary reason for my trip was the training of our local team and introduction of new and up-coming projects and software features, I also wanted to gather input and knowledge to bring back to our main office in Mahwah. Often we get so used to what we see every day that we forget that there’s a whole world out there. What we in the US think should be the major focus can be of less interest in other regions and vice versa. One of the things I learned was that the Asia/Pacific region sees a larger proportion of operators being technicians with limited insight into the advantages and limitations of the technique, than we usually do in the US and Europe. At the same time the microscope vendors were impressed with the level of analysis and how powerful the TEAM™ software is. These are things that we will have to take into consideration for future development, making it easier for novice users to apply the flexibility and power of the software but still allowing our advanced users access to all the bells and whistles that we have to offer.

Although we have conference systems, phone meetings and e-mail, there’s definitely something to be said for meeting face to face. The discussions and interactions flow much more easily when we can actually point to the same thing on the screen, draw on a piece of paper or just chat over coffee. Of course it can be a little overwhelming to come back to the hotel after a long day and find an overflowing inbox when you open the computer (not to mention getting calls at 3 AM from people who aren’t aware that you are travelling), but this is easily compensated by the experience of the culture, local food, and the chance to catch up with colleagues. Who knew that fried fish skin with salted egg goes so well with a cold beer?

With my Singapore trip over, I am making my way through the 24-hour travel back to the US and I have time to contemplate the experiences and discussions that I have had during the past week. There’s plenty of data to analyze, ideas for new software features, and input from microscope vendors to consider, but all that will have to wait. For now, it’s time to catch some sleep, try to get back on east coast time and maybe not worry about the line at immigration and New York traffic till I actually have to deal with it!

The origin of ideas

Dr. Patrick Camus, Director of Research and Innovation, EDAX

iStock_000035437584XLarge__teamwork

Stimulation for new research approaches and topics can come from odd origins and at the most unexpected times.

We recently held a Sales Meeting at the factory in Mahwah. During a presentation by Dr. Jens Rafaelsen, an Applications Scientist, he mentioned an unexpected EDS result. He found that a brand new EDS Elite detector was collecting more x-rays than a larger older Octane detector for the same geometry and SEM conditions. This result is quite unexpected and seems to violate physics and our typical ideas about x-ray detection. If confirmed, this result has far reaching implications for Sales and Marketing and would be exploited in the coming months. But the science behind the result is unknown at the time.

spectrum20160219090857870

EDS spectrum and modelling of Mg-Calcite.

A further discussion with Jens after his presentation inspired me to draft some notes on the scrap of paper that I had on hand. From these notes, I drafted an approach to an x-ray detection modelling experiment that would require input from Jens and another Scientist within the company. The experiment is to go beyond the simple description of associating detector detection performance with simply solid angle. That method may work when much of the sub-assemblies of the detection system are similar. However, for the latest generation of EDS detection systems, the use of modern materials requires a more complete system analysis.

Together, we will refine the model, compare the results to empirical results, and hope to publish both internal and external publications.

All of this work was sparked by a subtle but original observation by a coworker. Inspiration can come from unexpected sources and at unexpected times. Where have your inspirations come from?

Click here to watch Global Applications Manager, Tara Nylese presenting an overview of the Octane Elite at M&M 2015.

BLOG UPDATE FROM PAT – March 23, 2016
A new result has been found while modelling different detector configurations. The thickness of the Silicon support grid for the windows is significantly different for the traditional polymer (>300 um) and the new Si-N (<50 um) windows. This creates a different absorption of x-rays as a function of x-ray energy. This is illustrated in the following figure.

The predicted increase of the transparency of the Si-N window grid at intermediate x-ray energies has the potential to increase the total count rates of the detection system by a significant amount. More details to follow.

It’s All About Speed!

Dr. Oleg Lourie, Senior Product Manager EDS, EDAX

Different perceptions of speed can be measured differently, and yet in my opinion speed is one of those few fascinating concepts, which you are always aware of regardless of your activity. The world of speed is enriched with various emotional flavors which generate a multitude of reactions:  curiosity, when I observed the 690m/h cruising speed during my recent flight with KLM (‘are we getting close to 1Mach and when?’), or a contemplative focus when you accelerate to 170m/h on the German Autobahn near Düsseldorf.

In all circumstances speed inevitably arrests your attention, just as blazing fast EDS mapping did for me recently, when I saw a literally staggering acquisition speed below 200 us/pixel, which translated into a 512×400 pixel, fully quantifiable elemental map, which was collected in less than 1 min.

The ‘Octane’ EDS power, that ‘fueled’ this racing performance is equally remarkable – holding above 2Mcps in X-ray input counts without a single complaint  and exploding with 860Kcps for a single channel at about 50% dead time. I should admit I simply enjoyed it. It is inspiring to push the ‘limits’. The new electronics for this system will move things even further by leveling the throughput up to 1.8Mcps for a single channel – literally doubling the processing speed of the system.

1. Phase map of mineral clearly showing separation of zirconium silicate and calcium phosphate phases. 2. Spectrum of zirconium silicate

While astounded at the extreme throughput, a casual observer may wonder where this power can be applied in a ‘daily commute’ for elemental information. The answer is everywhere! It affects all your materials analysis when there are no boundaries imposed by your spectrometer on the scope of your experiment. It is indispensable for setting automated runs where sudden changes in sample composition, geometry or topography can impact acquisition. It aids in the formulation of statistics, where you need the fastest screening to acquire reliable statistical data. It is essential in ‘in situ’ studies where you rapidly change the sample compositional structure during the observation. It is useful in observing live Direct Phase Mapping and showing various phase distributions immediately after the scanned image is acquired. With more than 860 kcps ‘under the hood’, low noise CUBE electronics design and pulse processing times geared from 7.8 us to 120 ns, you can focus on driving your experiment at any speed you can imagine to achieve superior results in less time.

3. Spectrum of calcium phosphate 4. Superimposed spectra of 2 and 3 showing an complete overlap of the P and Zr peaks, which makes them undistinguishable in the RGB elemental map.

With all this ‘Octane’ power to keep your acquisition limits tunable on demand, there are many more exciting experiments further ‘down the road’. And yes, the roads can be icy and slippery in December. It is more fun to race with your fast EDS, collecting powerful, streamlined data and aiming towards the holidays with new observations, and possibly new discoveries.