Predicting material properties by integrating high-throughput experiments, high-throughput ab-initio calculations, and machine learning
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DOI: 10.1080/14686996.2019.1707111
Abstract: ABSTRACT High-throughput experiments (HTEs) have been powerful tools to obtain many materials data. However, HTEs often require expensive equipment. Although high-throughput ab-initio calculation (HTC) has the potential to make materials big data easier to collect,… read more here.
Keywords: machine learning; throughput; throughput initio; material properties ... See more keywords