Automated Generation and Ensemble-Learned Matching of X-ray Absorption Spectra

Kavli Affiliate: Kristin Persson

| First 5 Authors: Chen Zheng, Kiran Mathew, Chi Chen, Yiming Chen, Hanmei Tang

| Summary:

We report the development of XASdb, a large database of computed reference
X-ray absorption spectra (XAS), and a novel Ensemble-Learned Spectra
IdEntification (ELSIE) algorithm for the matching of spectra. XASdb currently
hosts more than 300,000 K-edge X-ray absorption near-edge spectra (XANES) for
over 30,000 materials from the open-science Materials Project database. We
discuss a high-throughput automation framework for FEFF calculations, built on
robust, rigorously benchmarked parameters. We will demonstrate that the ELSIE
algorithm, which combines 33 weak "learners" comprising a set of preprocessing
steps and a similarity metric, can achieve up to 84.2% accuracy in identifying
the correct oxidation state and coordination environment of a test set of 19
K-edge XANES spectra encompassing a diverse range of chemistries and crystal
structures. The XASdb with the ELSIE algorithm has been integrated into a web
application in the Materials Project, providing an important new public
resource for the analysis of XAS to all materials researchers. Finally, the
ELSIE algorithm itself has been made available as part of Veidt, an open source
machine learning library for materials science.

| Search Query: ArXiv Query: search_query=au:”Kristin Persson”&id_list=&start=0&max_results=10

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