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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...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Taylor & Francis
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7006745/ https://www.ncbi.nlm.nih.gov/pubmed/32082441 http://dx.doi.org/10.1080/14686996.2019.1707111 |