期刊
COMPUTATIONAL MATERIALS SCIENCE
卷 158, 期 -, 页码 42-48出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.commatsci.2018.11.001
关键词
Data-driven ICME; Digital-twin intelligent manufacturing; Database; Standards; Toolkits
资金
- National Key Research and Development Program of China [2018YFB0703801, 2016YFB0701304]
- National Natural Science Foundation of China [51690163]
After developing the simulation-based design approach of materials for decades, computational materials science/engineering present the power in accelerating the discoveries and the applications of novel advanced materials through a digital-twin design paradigm of integrated computational materials engineering (ICME). While the short goals of ICME are almost accomplished, those long goals are on the right way, highlighting the concept/strategy of materials by design. In this brief review, the recent frameworks of data-driven ICME in the last two years are discussed, presenting key aspects of principles, benchmarks, standards, databases, platforms and toolkits via various case studies. The author and his collaborators display a routine of data-driven ICME utilized in the investigations of Mg alloys through integrating the high-throughput first-principles calculations and the CALPHAD approach. It is highlighted that the bonding charge density could not only provide an atomic and electronic insight into the physical nature of chemical bond of pure elements, alloys, metal melts, oxides and semiconductors, surface and interfaces, but also reveal the fundamental solid-solution strengthening/embrittlement mechanism and the grain refinement mechanism, paving a path in accelerating the development of advanced materials. It is believed that the combinations of high-throughput multi-scale computations and fast experiments/manufacturing will build the advanced algorithms in the development of a promising digital fabricating approach to overcome the present and future challenges, illuminating the way toward the digital-twin intelligent manufacturing era.
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