刘淼
简介：
2023- 中国科学院物理研究所研究员
2018-2023年 中国科学院物理研究所特聘研究员
2013-2018年 劳伦斯伯克利国家实验室 博士后
2007-2012年 犹他大学材料科学工程系 博士
2006-2007年 犹他大学物理系 读研
2004-2006年 中国科学技术大学物理系 读研
1999-2004年 中国科学技术大学物理系 本科
主要研究方向：
原子尺度探索物质原理 | 第一性原理计算（聚焦能源材料、电化学、表面科学)
数据驱动的材料科学方法 | 世界级材料科学数据平台、材料基因工程
人工智能+材料科学 | 高精度、强泛化性的人工智能材料物性预测模型
机器人材料科学家 | 基于工业协作机器人的自动化无机功能材料合成表征实验室
过去的主要工作及获得的成果：
适用于一切无机化合物的人工智能原子间势函数GPTFF
创立了atomly.net材料科学数据库及相关软件体系。atomly 是世界最先进的材料数据库之一。借助材料数据及人工智能算法，我们可快速筛选、设计新材料，事半功倍。
培养了适合当前时代知识体系的学生，深受业界头部企业和科学界青睐。
代表性论文及专利：
2024
1. Coexistence of Superconductivity and Topological phase in Kagome metals ANb3Bi5 (A=K, Rb, Cs)
J Si, L-T Shi, B-Z Chen, H-H Yang, Jiyu Xu, Miao Liu, Sheng Meng
npj Computational Materials in press
2. Record-High Tc and Dome-Shaped Superconductivity in a Medium-Entropy Alloy TaNbHfZr under Pressure up to 160 GPa
L Wu, J Si, S Guan, H Zhang, J Dou, J Luo, J Yang, H Yu, J Zhang, X Ma, P Yang, R Zhou, Miao Liu*, Fang Hong*, Xiaohui Yu*
Phys. Rev. Lett. 132, 166002 (2024) Editors's suggestion 松山湖材料实验室科研进展
3. GPTFF: A high-accuracy out-of-the-box universal AI force field for arbitrary inorganic materials
Fankai Xie, Tenglong Lu, Sheng Meng, Miao Liu*
arXiv:2402.19327 (2024)
4. Electrochemically and chemically stable electrolyte–electrode interfaces for lithium iron phosphate all-solid-state batteries with sulfide electrolytes.
Tenglong Lu, Sheng Meng, Miao Liu*
J. Mater. Chem. A 2024,12, 3954 (2024) JMCA HOT Papers
5. Predicting structure-dependent Hubbard U parameters via machine learning.
Z Cao, G Cai, F Xie, H Jia, W Liu, Y Wang, F Liu, X Ren, Sheng Meng, Miao Liu*
Materials Futures 3(1) 025601 (2024)
2023
1. MatChat: A Large Language Model and Application Service Platform for Materials Science.
ZY Chen, FK Xie, M Wan, Y Yuan, Miao Liu*, ZG Wang, S Meng, YG Wang
Chinese Physics B, 32, 118104 (2023) 物理所主页报道 科学网报道 Physics World
2. Collective Behavior of Single-Atom Catalysts: a Synergistic Effect between Strain and Site Configuration.
Yanan Wang, Sheng Meng, Miao Liu*
J. Phys. Chem. Lett. 14, 44, 9918–9925 (2023) 松山湖材料实验室科研进展
3. Energy landscape and phase competition of CsV3Sb5-, CsV6Sb6-, and TbMn6Sn6-type Kagome materials.
Guanghui Cai, Yutao Jiang, Hui Zhou, Ze Yu, Kun Jiang, Youguo Shi, Sheng Meng, Miao Liu*
Chinese Physics Letters. 40 117101 (2023)
4. Percolation-induced resistivity drop in lutetium dihydride with controllable electrical conductivity over six orders of magnitude.
N Wang, J Hou, Z Liu, T Lu, P Shan, C Chai, S Jin, L Ma, L Shi, X Wang, L Y. W., Y Liu, H Zhang, X Dong, S Meng, Miao Liu* , JinGuang Cheng*
Science China Phys Mech. 66, 297412 (2023)
5. Lu-H-N phase diagram from first-principles calculations
F Xie, T Lu, Z Yu, Y Wang, Z Wang, Sheng Meng, Miao Liu*
Chinese Physics Letters 40, 057401 (2023) Express Letter
6. Atomly.net数据平台及其在无机化学中的应用
Miao Liu*, Sheng Meng
中国科学：化学 (SCIENTIA SINICA Chimica) 53(1) 19 (2023)
7. Synthesizability of transition-metal dichalcogenides: a systematic first-principles evaluation.
T Lu, Y Wang, G Cai, H Jia, X Liu, C Zhang, Sheng Meng, Miao Liu*
Materials Futures 2 015001 (2023)
8. A universal model for accurately predicting formation energy of inorganic compounds.
Y Liang, M Chen, Y Wang, H Jia, T Lu, F Xie, G Cai, Z Wang, Sheng Meng*, Miao Liu*
Science China Materials 66, 343 (2023)
2022
1. Persona of transition metal ions in solids.
H Jia, M Horton, Y Wang, S Zhang, Kristin A. Persson*, Sheng Meng*, Miao Liu*
Advanced Science 10.1002/advs.202202756 (2022)
2. Orbital dependence in single atom electrocatalytic reactions.
Y Wang, Y Liang, T Bo, Sheng Meng*, Miao Liu*
J. Phys. Chem. Lett. 2022, 13, 25, 5969 (2022)
3. Superconductive materials with MgB2-like structures from data-driven screening.
Z Yu, T Bo, B Liu, Z Fu, H Wang, S Xu, T Xia, S Li, Sheng Meng*, Miao Liu*
Phys. Rev. B 105, 214517 (2022)
4. Screening promising CsV3Sb5-like kagome materials from systematic first-principles evaluation.
Y Jiang, Z Yu, Y Wang, T Lu, S Meng*, K Jiang*, Miao Liu*
Chinese Physics Letters 39(4), 047402 (2022) Express letter
5. Unconventional materials: the mismatch between electronic charge centers and atomic positions.
J Gao, Y Qian, H Jia, Z Guo, Z Fang, Miao Liu*, H Weng*, Z Wang*
Science Bulletin 67 (6), 598-608 (2022)
2021
1. Viable substrates for the honeycomb-borophene growth.
Z Yu, S Meng*, Miao Liu*
Phys. Rev. Materials 5 (10), 104003 (2021)
2. High-Throughput Screening of Element-Doped Carbon Nanotubes Toward an Optimal One-Dimensional Superconductor
T Bo, Y Wang, Y Liang, X Liu, J Ren, H Weng, Miao Liu*, S Meng*
J. Phys. Chem. Lett. 12 (28), 6667-6675 (2021)
3. Dual carbon-hosted Co-N3 enabling unusual reaction pathway for efficient oxygen reduction reaction.
H Xu, H Jia, H Li, J Liu, X Gao, J Zhang, Miao Liu*, D Sun, S Chou, F Fang, R Wu*
Applied Catalysis B: Environmental 297,120390 (2021)
2020
1. Using strain to alter the energy bands of the monolayer MoSe2: A systematic study covering both tensile and compressive states.
X Cheng, L Jiang, Y Li, H Zhang, C Hu, S Xie, Miao Liu*, Z Qi*
Applied Surface Science 521, 146398 (2020)
2. Simplifying and accelerating kinetics enabling fast-charge Al batteries.
M Mao, Z Yu, Z Lin, YS Hu, H Li, X Huang, L Chen, Miao Liu*, L Suo*
Journal of Materials Chemistry A 8 (45), 23834-23843 (2020)
2019
1. High-throughput prediction of the ground-state collinear magnetic order of inorganic materials using density functional theory.
MK Horton, JH Montoya, Miao Liu, KA Persson
NPJ Computational Materials 5 (1), 1-11 (2019)
2. Flat AgTe honeycomb monolayer on Ag (111)
B Liu, J Liu, G Miao, S Xue, S Zhang, L Liu, X Huang, X Zhu, S Meng, J Guo, Miao Liu*, W Wang*
J. Phys. Chem. Lett. 10, 8, 1866-1871 (2019)
2019之前
Energy & Environmental Science 9, 3201 (2016)
Energy & Environmental Science 9, 2273 (2016)
Energy & Environmental Science 8, 964 (2015)
Nanotechnology 25, 135706 (2014)
Phys. Rev. Lett. 109, 055501 (2012)
Phys. Rev. B 86, 125427 (2012)
Phys. Rev. Lett. 103, 076102 (2009)
Phys. Rev. Lett. 102, 166404 (2009）
专利 United States Patent Application 20170069498
目前的研究课题及展望：
1. 开发高通量材料计算方法及材料数据库。（atomly.net）
2. 基于人工智能方法开发高精度的材料计算方法，用于非晶、无序等体系的模拟。（HAAIFF程序包，将于近期发布）
3. 基于材料大料数据的新材料研发，例如新型能源材料，包括多价态离子电池、Li-S电池、催化剂。
4. 机器人实验室
培养研究生情况：
每年招收硕博连读研究生2名。课题组提供世界一流的科研资源和国际合作机会。毕业生有机会进入业界头部企业工作。
其他联系方式：
电话：
010-82649407
Email：