Layer-by-layer phase transformation in Ti3O5 revealed by machine-learning molecular dynamics simulations
文献类型：期刊论文
| 作者 | Liu, Mingfeng1,2; Wang, Jiantao1,2; Hu, Junwei3; Liu, Peitao1; Niu, Haiyang3; Yan, Xuexi1; Li, Jiangxu1; Yan, Haile4; Yang, Bo4; Sun, Yan1 |
| 刊名 | NATURE COMMUNICATIONS
 |
| 出版日期 | 2024-04-09 |
| 卷号 | 15期号:1页码:10 |
| DOI | 10.1038/s41467-024-47422-1 |
| 通讯作者 | Liu, Peitao(ptliu@imr.ac.cn) ; Niu, Haiyang(haiyang.niu@nwpu.edu.cn) |
| 英文摘要 | Reconstructive phase transitions involving breaking and reconstruction of primary chemical bonds are ubiquitous and important for many technological applications. In contrast to displacive phase transitions, the dynamics of reconstructive phase transitions are usually slow due to the large energy barrier. Nevertheless, the reconstructive phase transformation from beta- to lambda-Ti3O5 exhibits an ultrafast and reversible behavior. Despite extensive studies, the underlying microscopic mechanism remains unclear. Here, we discover a kinetically favorable in-plane nucleated layer-by-layer transformation mechanism through metadynamics and large-scale molecular dynamics simulations. This is enabled by developing an efficient machine learning potential with near first-principles accuracy through an on-the-fly active learning method and an advanced sampling technique. Our results reveal that the beta-lambda phase transformation initiates with the formation of two-dimensional nuclei in the a b-plane and then proceeds layer-by-layer through a multistep barrier-lowering kinetic process via intermediate metastable phases. Our work not only provides important insight into the ultrafast and reversible nature of the beta-lambda transition, but also presents useful strategies and methods for tackling other complex structural phase transitions. |
| 资助项目 | The work at the Institute of Metal Research is supported by the National Natural Science Foundation of China (Grant No. 52201030 and Grant No. 52188101), the National Key RD Program of China 2021YFB3501503, Chinese Academy of Sciences (Grant No. ZDRW-CN-2[22003050] ; National Natural Science Foundation of China[2021YFB3501503] ; National Key R& D Program of China[ZDRW-CN-2021-2-5] ; Chinese Academy of Sciences[51725103] ; National Science Fund for Distinguished Young Scholars[2020-QZ-03] ; Research Fund of the State Key Laboratory of Solidification Processing (NPU), China[F 81-N] ; Austrian Science Fund (FWF) within the SFB TACO |
| WOS研究方向 | Science & Technology - Other Topics |
| 语种 | 英语 |
| WOS记录号 | WOS:001202403000026 |
| 出版者 | NATURE PORTFOLIO |
| 资助机构 | The work at the Institute of Metal Research is supported by the National Natural Science Foundation of China (Grant No. 52201030 and Grant No. 52188101), the National Key RD Program of China 2021YFB3501503, Chinese Academy of Sciences (Grant No. ZDRW-CN-2 ; National Natural Science Foundation of China ; National Key R& D Program of China ; Chinese Academy of Sciences ; National Science Fund for Distinguished Young Scholars ; Research Fund of the State Key Laboratory of Solidification Processing (NPU), China ; Austrian Science Fund (FWF) within the SFB TACO |
| 源URL |  |
| 专题 | 金属研究所_中国科学院金属研究所 |
| 通讯作者 | Liu, Peitao; Niu, Haiyang |
| 作者单位 | 1.Chinese Acad Sci, Inst Met Res, Shenyang Natl Lab Mat Sci, Shenyang 110016, Peoples R China 2.Univ Sci & Technol China, Sch Mat Sci & Engn, Shenyang 110016, Peoples R China 3.Northwestern Polytech Univ, Int Ctr Mat Discovery, Sch Mat Sci & Engn, State Key Lab Solidificat Proc, Xian 710072, Peoples R China 4.Northeastern Univ, Sch Mat Sci & Engn, Key Lab Anisotropy & Texture Mat, Minist Educ, Shenyang 110819, Peoples R China 5.Univ Vienna, Fac Phys, Ctr Computat Mat Sci, Kolingasse 14-16, A-1090 Vienna, Austria |
| 推荐引用方式 GB/T 7714 | Liu, Mingfeng,Wang, Jiantao,Hu, Junwei,et al. Layer-by-layer phase transformation in Ti3O5 revealed by machine-learning molecular dynamics simulations[J]. NATURE COMMUNICATIONS,2024,15(1):10. |
| APA | Liu, Mingfeng.,Wang, Jiantao.,Hu, Junwei.,Liu, Peitao.,Niu, Haiyang.,...&Chen, Xing-Qiu.(2024).Layer-by-layer phase transformation in Ti3O5 revealed by machine-learning molecular dynamics simulations.NATURE COMMUNICATIONS,15(1),10. |
| MLA | Liu, Mingfeng,et al."Layer-by-layer phase transformation in Ti3O5 revealed by machine-learning molecular dynamics simulations".NATURE COMMUNICATIONS 15.1(2024):10. |
入库方式： OAI收割
来源：金属研究所
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