Random forest machine learning models for interpretable X-ray absorption near-edge structure spectru...
Random forest machine learning models for interpretable X-ray absorption near-edge structure spectrum-property relationships
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London: Nature Publishing Group UK
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English
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London: Nature Publishing Group UK
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X-ray absorption spectroscopy (XAS) produces a wealth of information about the local structure of materials, but interpretation of spectra often relies on easily accessible trends and prior assumptions about the structure. Recently, researchers have demonstrated that machine learning models can automate this process to predict the coordinating envi...
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Random forest machine learning models for interpretable X-ray absorption near-edge structure spectrum-property relationships
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TN_cdi_osti_scitechconnect_1643957
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_osti_scitechconnect_1643957
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ISSN
2057-3960
E-ISSN
2057-3960
DOI
10.1038/s41524-020-00376-6
