At QMA-2019, John Donovan said "the only thing we measure is k-ratios. Everything else we pull out of our ass." He has a point. We measure k-ratios and then apply a set of correction factors that have some empirical basis to estimate the composition. k-ratios are the fundamental characteristic of our business. For a given beam energy and take-off angle, your instrument should produce the same k-ratios (to within statistics) as mine for the same material. If they don't then there is cause to investigate. In fact, if we measure a set of k-ratios and we are able to match them up with k-ratios from a known material, there is no need to apply matrix corrections, we know that we are measuring that material. This is becoming particularly important as we start to move into domains in which our traditional matrix correction algorithms don't work (like L lines in transition metals...) We may never be able to develop matrix correction algorithms that work in this domain however, by database lookup we could identify the material if anyone anywhere has entered it into the database.
So I'm going to propose a (significant, long-term) microanalysis community project:
1. Create an online repository / database of empirical k-ratios
2. Encourage the community to submit k-ratios and maintain an online record of all the submissions
3. Make the database available to all (through a web form and through a web application programming interface)
Uses:
1. Evaluate matrix correction algorithms against a community consensus database
2. You can make all measurements against the best similar (matched) standard in the database without actually having that material in you lab!! (See below)
With community consensus, a day could come in which all a lab would need to do standards-based quant against any material would be one standard per element. (All your standards on one or two blocks that never need come out of your instrument..)
3. We can accurately measure the composition of materials for which matrix correction algorithms don't work (if they are in the database)
4. QC your instrument by comparing the k-ratios you measure to community consensus k-ratios
5. Reduce our dependence on matrix correction algorithms (all measurements could be against similar standards)
6. k-ratios never go out of stock or become degraded (like NIST /

standards)
7. The range of compositional variation of inhomogeneous standards could be characterized.
Questions:
1. Is this a good idea? (Am I overlooking something?)
2. Is the community interested in participating? (It will only work if many people contribute)
3. How do we design such a database?
How do we curate data? Do we curate data? (Is community consensus better than curation? Do we implement outlier detection?)
Do we attribute data to labs/individuals?
What data needs to be included? (What is the minimum required, what else would be helpful, what would be icing?)
4. Where is it hosted? (MAS? NIST? FIGMAS?)
5. Who develops and maintains it? (One person, a group (FIGMAS?, MAS working group?, research group???))
6. What materials would we suggest measuring the k-ratio against? (Pure elements? What about surface oxidization? What is the most stable?)
7. Do we need a separate WDS and EDS databases? (For EDS, should we just archive spectra (unknown and standards?))
Similar (matched) standards -
The idea here is to "share k-ratios not materials." Any standard that anyone anywhere had measured an entered into the database could be used in your measurement without having that material in your lab.
Historically, if we want to make a measurement against Kakanui hornblende (KH), we need a chip or two in our lab. But this isn't necessary. If we have a database of k-ratios of KH against Si, Al, Fe, Mg, CaF2, Albite, etc and we make measurements in our lab using Si, Al, Fe, ... We can use the consensus k-ratios to convert our simple Si, Al, Fe... k-ratios into k-ratios relative to KH and then use these to measure our unknown against KH. (Furthermore, the spread of the k-ratios in the database could provide information about the standard's heterogeneity.)