Materials researchers are generating data in ever-increasing volumes, and these data are, in turn, fueling the discovery and design of new materials. These changes are enabled by advances in data capture via laboratory information management systems (LIMS), high-throughput experiment and computation, improved data collection capabilities, automated experiment selection and execution, and new analytical methods based on artificial intelligence (AI) and machine learning (ML) approaches. Data infrastructure is being developed with increasing numbers of repositories as well as data-sharing and standardization efforts.

中文翻译：

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材料数据可用性和应用的进展：回顾


材料研究人员正在生成越来越多的数据，而这些数据反过来又推动了新材料的发现和设计。这些变化是通过实验室信息管理系统（LIMS）数据采集、高通量实验和计算、改进的数据收集能力、自动化实验选择和执行以及基于人工智能（AI）和机器学习的新分析方法的进步实现的（ML）方法。随着存储库数量的增加以及数据共享和标准化的努力，数据基础设施正在不断发展。