Construction of ground-state preserving sparse lattice models for predictive materials simulations

doi:10.1038/s41524-017-0032-0

	Construction of ground-state preserving sparse lattice models for predictive materials simulations
	Huang, Wenxuan 1; Urban, Alexander 2; Rong, Ziqin 1; Ding, Zhiwei 1; Luo, Chuan 3; Ceder, Gerbrand 1,2,4
	2017-08-07
发表期刊	NPJ COMPUTATIONAL MATERIALS
ISSN	2057-3960
卷号	3 页码:9
摘要	First-principles based cluster expansion models are the dominant approach in ab initio thermodynamics of crystalline mixtures enabling the prediction of phase diagrams and novel ground states. However, despite recent advances, the construction of accurate models still requires a careful and time-consuming manual parameter tuning process for ground-state preservation, since this property is not guaranteed by default. In this paper, we present a systematic and mathematically sound method to obtain cluster expansion models that are guaranteed to preserve the ground states of their reference data. The method builds on the recently introduced compressive sensing paradigm for cluster expansion and employs quadratic programming to impose constraints on the model parameters. The robustness of our methodology is illustrated for two lithium transition metal oxides with relevance for Li-ion battery cathodes, i.e., Li2xFe2(1-x)O2 and Li2xTi2(1-x)O2, for which the construction of cluster expansion models with compressive sensing alone has proven to be challenging. We demonstrate that our method not only guarantees ground-state preservation on the set of reference structures used for the model construction, but also show that out-of-sample ground-state preservation up to relatively large supercell size is achievable through a rapidly converging iterative refinement. This method provides a general tool for building robust, compressed and constrained physical models with predictive power.
DOI	10.1038/s41524-017-0032-0
收录类别	SCI
语种	英语
资助项目	US Department of Energy (DOE)[DE-FG02-96ER45571]
WOS研究方向	Chemistry ; Materials Science
WOS类目	Chemistry, Physical ; Materials Science, Multidisciplinary
WOS记录号	WOS:000426833600001
出版者	NATURE PUBLISHING GROUP
引用统计	被引频次：16[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/5665
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Ceder, Gerbrand
作者单位	1.MIT, Dept Mat Sci & Engn, Cambridge, MA 02139 USA 2.Univ Calif Berkeley, Dept Mat Sci & Engn, Berkeley, CA 94720 USA 3.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 4.Lawrence Berkeley Natl Lab, Mat Sci Div, Berkeley, CA 94720 USA
推荐引用方式 GB/T 7714	Huang, Wenxuan,Urban, Alexander,Rong, Ziqin,et al. Construction of ground-state preserving sparse lattice models for predictive materials simulations[J]. NPJ COMPUTATIONAL MATERIALS,2017,3:9.
APA	Huang, Wenxuan,Urban, Alexander,Rong, Ziqin,Ding, Zhiwei,Luo, Chuan,&Ceder, Gerbrand.(2017).Construction of ground-state preserving sparse lattice models for predictive materials simulations.NPJ COMPUTATIONAL MATERIALS,3,9.
MLA	Huang, Wenxuan,et al."Construction of ground-state preserving sparse lattice models for predictive materials simulations".NPJ COMPUTATIONAL MATERIALS 3(2017):9.