Expediting Combinatorial Data Set Analysis by Combining Human and Algorithmic Analysis

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• 作者：Helge Sören Stein ; Sally Jiao ; Alfred Ludwig
• 刊名：ACS Combinatorial Science
• 出版年：2017
• 出版时间：January 9, 2017
• 年：2017
• 卷：19
• 期：1
• 页码：1-8
• 全文大小：562K
• ISSN：2156-8944

文摘

A challenge in combinatorial materials science remains the efficient analysis of X-ray diffraction (XRD) data and its correlation to functional properties. Rapid identification of phase-regions and proper assignment of corresponding crystal structures is necessary to keep pace with the improved methods for synthesizing and characterizing materials libraries. Therefore, a new modular software called htAx (high-throughput analysis of X-ray and functional properties data) is presented that couples human intelligence tasks used for “ground-truth” phase-region identification with subsequent unbiased verification by an algorithm to efficiently analyze which phases are present in a materials library. Identified phases and phase-regions may then be correlated to functional properties in an expedited manner. For the functionality of htAx to be proven, two previously published XRD benchmark data sets of the materials systems Al-Cr-Fe-O and Ni-Ti-Cu are analyzed by htAx. The analysis of ∼1000 XRD patterns takes less than 1 day with htAx. The proposed method reliably identifies phase-region boundaries and robustly identifies multiphase structures. The method also addresses the problem of identifying regions with previously unpublished crystal structures using a special daisy ternary plot.