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Figure 1
Distinction between the conventional approach and an automatic deep-learning-based analysis for powder XRD scans. Based on pulverized samples of crystalline materials, one-dimensional diffraction patterns are measured using the Bragg–Brentano focusing geometry (left). Typically, the scan is analyzed manually by matching the measured intensity peaks with crystallite properties of reference phases from a database (middle top). Alternatively, a neural-network model is applied to identify the comprised phases in the measured material (middle bottom). Both approaches come to a binary prediction of the comprised phases, while the conventional approach requires the manual intervention of an expert user (right).

Volume 8| Part 3| May 2021| Pages 408-420
ISSN: 2052-2525