Construction of ground-state preserving sparse lattice models for predictive materials simulations
文献类型：期刊论文
| 作者 | Huang, Wenxuan4; Urban, Alexander3; Rong, Ziqin4; Ding, Zhiwei4; Luo, Chuan2; Ceder, Gerbrand1,3,4 |
| 刊名 | NPJ COMPUTATIONAL MATERIALS
 |
| 出版日期 | 2017-08-07 |
| 卷号 | 3页码:9 |
| ISSN号 | 2057-3960 |
| DOI | 10.1038/s41524-017-0032-0 |
| 英文摘要 | 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. |
| 资助项目 | US Department of Energy (DOE)[DE-FG02-96ER45571] |
| WOS研究方向 | Chemistry ; Materials Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000426833600001 |
| 出版者 | NATURE PUBLISHING GROUP |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/5664]  |
| 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.Lawrence Berkeley Natl Lab, Mat Sci Div, Berkeley, CA 94720 USA 2.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 3.Univ Calif Berkeley, Dept Mat Sci & Engn, Berkeley, CA 94720 USA 4.MIT, Dept Mat Sci & Engn, Cambridge, MA 02139 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. |
入库方式： OAI收割
来源：计算技术研究所
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