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An open service to classify diffraction patterns
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SCIInstitute/DiffractionClassification
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README.txt ####Welcome to the DeepdiveCrystallography diffraction classification web service ###Quickstart Guide: prerequisites: python 3.6 and an internet connection To predict the crystal structure simply start the Diffraction Classifier by running the command: python DiffractionClassifier.py Then follow the series of prompts. Advanced usage: You can specify the data you'd like to load by adding --filepath FILEPATH_TO_YOUR_DATA to the function call. Similarly you specify the calibration by modifying the calibration.json file and adding --calibration calibration.json to the function call. ### Acknowledgements Work supported through the INL Laboratory Directed Research& Development (LDRD) Program under DOE Idaho Operations Office Contract DE-AC07-05ID145142. Thanks to Ian Harvey for many useful discussions and contributions to this work. ### Citations - J. A. Aguiar, M. L. Gong, R. R. Unocic, T. Tasdizen, & B. D. Miller. Decoding Crystallography from High-Resolution Electron Imaging and Diffraction Datasets with Deep Learning. Sci. Adv. aaw1949 (2019). - J. A. Aguiar, M. L. Gong & T. Tasdizen. Crystallographic prediction from diffraction and chemistry data for higher throughput classification using machine learning. Comput. Mater. Sci. 173, 109409 (2020).
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