Random Forest Models for Accurate Identification of Coordination Environments from X-Ray Absorption Near-Edge Structure

Random Forest Models for Accurate Identification of Coordination Environments from X-Ray Absorption Near-Edge Structure

Summary: Analyzing coordination environments using X-ray absorption spectroscopy has broad applications in solid-state physics and material chemistry. Here, we show that random forest models trained on 190,000 K-edge X-ray absorption near-edge structure (XANES) spectra can identify the main atomic c...

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Bibliographic Details
Main Authors: Chen Zheng, Chi Chen, Yiming Chen, Shyue Ping Ong
Format: Article
Language:English
Published: Elsevier 2020-05-01
Series:Patterns
Subjects:
machine learning
X-ray absorption spectroscopy
random forest
feature importance
XANES
coordination environment
Online Access:http://www.sciencedirect.com/science/article/pii/S2666389920300131

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http://www.sciencedirect.com/science/article/pii/S2666389920300131

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