I stumbled into Dondero’s Rock Shop a few weeks ago and struck up a conversation with the owner. He had been interested in geology all his life and was now operating a very nice shop in North Conway, NH with just about every type of mineral one could imagine on display. It was a great opportunity to have an expert identify a few specimens my boys had collected the previous day and he was more than happy to help. These were very large single crystals of relatively common minerals, but it was obvious that experience makes all the difference when one is trying to identify them by sight. I offered to return the favor by collecting XRD data on anything that ever managed to stump his well trained eye and he immediately brought out an interesting sedimentary formation which he’d sliced into cross to sections. He had been very curious about its composition and I brought home a sample. My technical expertise is primarily in the hardware we use at Texray while the real science is handled by other, more highly skilled hands, but this seemed like a fun little project and good practice if nothing else.
Geological samples are particularly difficult to analyze by XRD as they contain various defects which are difficult if not impossible to model based on theoretical data. Our precious Rietveld refinements roll off of this type of data like water off a ducks back all too often and we’re left wondering how on earth this mud could be mistaken for moon rocks. As wonderful as Rietveld is in well-trained hands, we tend to rely much more on comparative data when we’re working with this type of sample. We can thank Dennis Eberl of USGS in Boulder, CO for bringing RockJock into the world to solve exactly these types of problems. RockJock is relies on what’s called RIR. That is Relative Intensity Ratio analysis to provide both qualitative and quantitative results. The algorithm has been massaged into a number of commercial products in an effort to improve the user interface and add additional functionality, but the core of all that is still readily available on the internet for anyone interested to download. If you’re interested in something a little more user friendly, we offer ClaySim from MDI.
To the left you can see the data I collected after mild grinding. It’s not uncommon to spend several hours collecting data before it’s adequate for quantification or other advance analysis, but as we’re only interested in qualitative phase ID, this will more than suffice. I was quite surprised to find only two major phases present since the sample clearly shows four distinct layers with completely different coloration. The scan actually ran all the way to 120°2Θ, but the “action” is mostly concentrated at the lower angles. Hardcore geologist actually push the lower limit all the way down to 2.5°2Θ in an effort to catch a few illusive peaks. The analysis program you see here is MDI Jade 2010. It’s their flagship product and for good reason. Almost all of our users are running some form of Jade for their analysis and all have had nothing but glowing praise for it.
So it appears that the mystery rock was actually little more than Quartz and Dickite. It’s possible that there’s a bit of Kaolinite mixed in there as well, particularly because Dickite and Kaolinite share a chemical composition. The real fun started when I let Jade loose using a feature called “One Click Analysis”. This is as close to a “black box” as XRD analysis will ever get. With good data collected on a solid, well-aligned XRD, this little button can provide impressive results with no user input at all. It’s not the magic bullet for every situation, but in this case, it recommended yet another phase with the same chemical composition as Kaolinite and Dickite. Nacrite. Adding this into our phase list improved the difference pattern and allowed Jade to model nearly every bump in the pattern.