Dirk,
You had forgot to list the other following steps in the wish list: ..., drafting a paper, choosing the right journal for biggest impact, and dealing with intelligent-differently reviewers.
Jokes away, I as human being with decade of experience run often into trouble of identifying with 100% certainty the new to me minerals from only the chemical composition. It often needs additional external information by other method to get closer to what the thing could actually be. Yes, ML will help you and can increase throughput if You know what minerals you have in the sample, You need first to train ML to recognize those. I.e. If You know that your samples have only Quartz, Plagioclase, biotite, amphibole and pyroxene and nothing else, and train the ML to recognize those - that will work exceptionally well. But throw something what ML was not trained to recognize and this will derail spectacularly. But wait - actually in some cases ML will have problem to distinguish pyroxene from amphibole when amphibole is K-poor and Fe rich. There is such enormous compositional overlap between some groups, that slight miss-calibration in measurement would result in wrong classification.