Predicting material properties by integrating high-throughput experiments, high-throughput ab-initio calculations, and machine learning
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, HTC does not represent the actual materials...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2020-01-01
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| Series: | Science and Technology of Advanced Materials |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/14686996.2019.1707111 |