Error estimation in high-throughput density functional theory calculation for material property: elastic constants of cubic binary alloy case
文献类型：期刊论文
| 作者 | Wang, Juan1,2; Yang, Xiaoyu1,2; Wang, Guisheng3; Ren, Jie1,2; Wang, Zongguo1; Zhao, Xushan1; Pan, Yue4 |
| 刊名 | Computational materials science
 |
| 出版日期 | 2017-06-15 |
| 卷号 | 134页码:190-200 |
| 关键词 | High-throughput dft calculation Error estimation Neural network Cross validation Support vector regression |
| ISSN号 | 0927-0256 |
| DOI | 10.1016/j.commatsci.2017.03.035 |
| 通讯作者 | Yang, xiaoyu(kxy@cnic.cn) |
| 英文摘要 | Estimating density functional theory (dft) calculation error is an important while challenging task in computational material science. the calculation contains inherent errors due to improper input parameters and approximated exchange-correlation functional. in this paper, we present a data-driven approach of using machine learning techniques to estimate the error of dft calculation. we prepare the data by high-throughput first principle dft simulation and experimental data collection. the single-hidden layer back propagation feedforward neural network (slbpfn) constructed based on the proposed cross validation algorithm, and support vector machine for regression (svr) techniques are employed to build regression models to predict the dft calculation error. as a demonstration, the developed regression models are used to predict errors in calculating elastic constants of cubic binary alloys. it has been demonstrated that the machine learning techniques can predict dft calculation error of elastic constants with an acceptable accuracy. it also shows the bp neural network built by our proposed cross validation algorithm can provide a better prediction. our study is a first-invasive work of using machine learning techniques to estimate the errors in calculating elastic constants of binary alloys. (c) 2017 elsevier b.v. all rights reserved. |
| WOS关键词 | TOTAL-ENERGY CALCULATIONS ; WAVE BASIS-SET ; MATERIALS DESIGN ; NEURAL-NETWORKS ; PREDICTIONS ; SN |
| WOS研究方向 | Materials Science |
| WOS类目 | Materials Science, Multidisciplinary |
| 语种 | 英语 |
| WOS记录号 | WOS:000401043200024 |
| 出版者 | ELSEVIER SCIENCE BV |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2374223 |
| 专题 | 计算机网络信息中心 |
| 通讯作者 | Yang, Xiaoyu |
| 作者单位 | 1.Chinese Acad Sci, Comp Network Informat Ctr, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Beijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China 4.Sun Yat Sen Univ, Sch Math, Guangzhou 510275, Guangdong, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Juan,Yang, Xiaoyu,Wang, Guisheng,et al. Error estimation in high-throughput density functional theory calculation for material property: elastic constants of cubic binary alloy case[J]. Computational materials science,2017,134:190-200. |
| APA | Wang, Juan.,Yang, Xiaoyu.,Wang, Guisheng.,Ren, Jie.,Wang, Zongguo.,...&Pan, Yue.(2017).Error estimation in high-throughput density functional theory calculation for material property: elastic constants of cubic binary alloy case.Computational materials science,134,190-200. |
| MLA | Wang, Juan,et al."Error estimation in high-throughput density functional theory calculation for material property: elastic constants of cubic binary alloy case".Computational materials science 134(2017):190-200. |
入库方式： iSwitch采集
来源：计算机网络信息中心
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。