Quantitative X-Ray Microanalysis with Monte Carlo Simulations and Deep Learning************

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Convolutional neural networks (CNN) are currently implemented in a variety of image processing techniques. However, in order for them to be applied to digital signal processing, specifically X-ray spectra analysis, large and diverse training sets must be generated to cover a wide range of possible characteristics. To reach a diversity of materials science applications, training sets tailored to each specific problem must be appropriately compiled. The overall objective of the research project is to implement Monte Carlo X-ray simulations as training sets for CNNs in the ORS Dragonfly c software in order to provide a tool for X-ray spectra analysis that is efficient and accurate, and can cover a large variety of material science research based problems.