Journal
JOURNAL OF MATERIALS RESEARCH
Volume 35, Issue 8, Pages 872-889Publisher
CAMBRIDGE UNIV PRESS
DOI: 10.1557/jmr.2020.43
Keywords
defects; electronic structures; simulation
Categories
Funding
- National Key Research and Development Program of China [2016YFB0701304, 2016YFB0701303, 2018YFB0703801, 2018YFB0703802]
- National Natural Science Foundation of China [51690163]
- National Science and Technology Major Project [2017-VI-0014-0086]
- CRRC Tangshan Co., Ltd. [201750463031]
- Science Challenge Project [TZZT2019-D1.5]
- project of SKL-AMM-USTB [2016-Z07]
- Fundamental Research Funds for the Central Universities in China [G2016KY0302]
- Seed Foundation of Innovation and Creation for Graduate Students at Northwestern Polytechnical University [ZZ2019081]
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This article presents a brief review of our case studies of data-driven Integrated Computational Materials Engineering (ICME) for intelligently discovering advanced structural metal materials, including light-weight materials (Ti, Mg, and Al alloys), refractory high-entropy alloys, and superalloys. The basic bonding in terms of topology and electronic structures is recommended to be considered as the building blocks/units constructing the microstructures of advanced materials. 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 materials but also reveal the fundamental strengthening/embrittlement mechanisms and the local phase transformations of planar defects, paving a path in accelerating the development of advanced metal materials via interfacial engineering. Perspectives on the knowledge-based modeling/simulations, machine-learning knowledge base, platform, and next-generation workforce for sustainable ecosystem of ICME are highlighted, thus to call for more duty on the developments of advanced structural metal materials and enhancement of research productivity and collaboration.
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