期刊
COMPUTING IN SCIENCE & ENGINEERING
卷 15, 期 5, 页码 22-31出版社
IEEE COMPUTER SOC
DOI: 10.1109/MCSE.2013.76
关键词
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资金
- US National Science Foundation [DMS-11-25909, DMR-13-07811]
- Air Force Office of Scientific Research [FA9550-12-1-0456]
- Wilkinson Professorship of Interdisciplinary Engineering
- Division Of Materials Research
- Direct For Mathematical & Physical Scien [1307811] Funding Source: National Science Foundation
This work presents a new perspective on alloy thermodynamics computation using data-driven analysis and machine learning for the design and discovery of materials. The focus is on an integrated machine-learning framework, coupling different genres of supervised and unsupervised informatics techniques and bridging two distinct viewpoints: continuum representations based on solid solution thermodynamics, and discrete high-dimensional elemental descriptions.
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