研究
AI4EC 研究动态
AI4EC 研究动态
- Toward Operando Modeling of Electrochemical Processes at Metal-Aqueous Solution InterfacesPeibin Kang, Jun Cheng*, Lingyi Meng*1/28/2026Journal of Chemical Theory and Computation, 2026, 17, 5, 1471–1478
- Machine-Learning Accelerated Computational Spectroscopy Reveals Vibrational Signature of the Oxidation Level of Graphene in Contact with WaterXianglong Du, Jun Cheng*, Fujie Tang*1/24/2026The Journal of Physical Chemistry Letters, 2026, 17, 5, 1471–1478
- Domain Oriented Universal Machine Learning Potential Enables Fast Exploration of Chemical Space of Battery ElectrolytesFeng Wang; Yu-Hang Tang; Ze-Bing Ma; Yu-Cheng Jin; Jun Cheng*12/31/2025Nature Communication, 17, 1226 (2026).
- Synergizing a knowledge graph and large language model for relay catalysis pathway recommendationFei Fu; Qing-Qing Li; Fangrong Wang; Jie Hu; Tian-Tian Wang; Yun-Pei Liu; Weihong Xu; Zhili Lin; Fu-Qiang Gong; Qi-Yuan Fan; Jeff Z Pan*; Ye Wang*; Jun Cheng*8/25/2025National Science Review, 2025, 12(8), nwaf271
- Interfaces govern the structure of angstrom-scale confined water solutionsYongkang Wang; Fujie Tang; Xiaoqing Yu; Kuo-Yang Chiang; Chun-Chieh Yu; Tatsuhiko Ohto; Yunfei Chen; Yuki Nagata* & Mischa Bonn*8/8/2025Nature Communications, 2025, 16, 7288
- Machine Learning Potential for Electrochemical Interfaces with Hybrid Representation of Dielectric ResponseJia-Xin Zhu* and Jun Cheng ⁺7/2/2025Physical Review Letters, 2025, 135(1): 018003.
- Revealing Transition State Stabilization in Organocatalytic Ring-Opening Polymerization Using Data ScienceZhang, Miaomiao; Su, Yuming; Du, Tianyi; Ding, Shihao; Dai, Jieyu; Wang, Cheng*; Liu, Yun*5/29/2025Angewandte Chemie International Edition, 2025, 64(23): e202502090.
- Decoding the Competing Effects of Dynamic Solvation Structures on Nuclear Magnetic Resonance Chemical Shifts of Battery Electrolytes via Machine LearningYou, Qi; Sun, Yan; Wang, Feng; Cheng, Jun*; Tang, Fujie*4/18/2025Journal of the American Chemical Society, 2025, 147(17): 14667–14676.
- Toward a unified benchmark and framework for deep learning-based prediction of nuclear magnetic resonance chemical shiftsXu, Fanjie; Guo, Wentao; Wang, Feng; Yao, Lin; Wang, Hongshuai; Tang, Fujie*; Gao, Zhifeng*; Zhang, Linfeng; E, Weinan; Tian, Zhong-Qun; Cheng, Jun*3/28/2025Nature Computational Science, 2025, 5(4): 292-300.
- Optical Absorption Spectroscopy Probes Water Wire and Its Ordering in a Hydrogen-Bond NetworkTang, Fujie; Qiu, Diana Y.*; Wu, Xifan3/5/2025Physical Review X, 2025, 15(1): 011048.
- Revealing the molecular structures of α-Al₂O₃(0001)–water interface by machine learning based computational vibrational spectroscopyDu, Xianglong; Shao, Weizhi; Bao, Chenglong; Zhang, Linfeng; Cheng, Jun*; Tang, Fujie*9/24/2024The Journal of Chemical Physics, 2024, 161(12): 124702.
- Step-induced double-row pattern of interfacial water on rutile TiO₂(110) at electrochemical conditionsSun, Yan; Wu, Cheng-Rong; Wang, Feng; Bi, Rui-Hao; Zhuang, Yong-Bin; Liu, Shuai; Chen, Ming-Shu; Zhang, Kelvin H. -L.*; Yan, Jia-Wei*; Mao, Bing-Wei; Tian, Zhong-Qun; Cheng, Jun*5/21/2024Chemical Science, 2024, 15(31): 12264-12269.
- Accelerating Computation of Acidity Constants and Redox Potentials for Aqueous Organic Redox Flow Batteries by Machine Learning Potential-Based Molecular DynamicsWang, Feng; Ma, Zebing; Cheng, Jun*4/24/2024Journal of the American Chemical Society, 2024, 146(21): 14566-14575.
- Machine Learning Molecular Dynamics Shows Anomalous Entropic Effect on Catalysis through Surface Pre-melting of NanoclustersGong, Fu-Qiang; Liu, Yun-Pei; Wang, Ye; E, Weinan; Tian, Zhong-Qun; Cheng, Jun*4/19/2024Angewandte Chemie International Edition, 2024, 63(27): e202405379.
- Heterodyne-Detected Sum-Frequency Generation Vibrational Spectroscopy Reveals Aqueous Molecular Structure at the Suspended Graphene/Water InterfaceWang, Yongkang; Tang, Fujie; Yu, Xiaoqing; Ohto, Tatsuhiko; Nagata, Yuki*; Bonn, Mischa*3/13/2024Angewandte Chemie International Edition, 2024, 63(20): e202319503.
- Exploring new generation of characterization approaches for energy electrochemistry—from operando to artificial intelligenceQiao, Yu; Hu, Ren; Gu, Yu; Tang, Fu-Jie; Luo, Si-Heng; Zhang, Hai-Tang; Tian, Jing-Hua; Cheng, Jun; Tian, Zhong-Qun*1/8/2024SCIENTIA SINICA Chimica, 2024, 54: 338-352.
- A workflow package to automatically generate machine learning potentials and phase diagrams for semiconductor alloysGuo, Yu-Xin; Zhuang, Yong-Bin; Shi, Jueli; Cheng, Jun*9/1/2023The Journal of Chemical Physics, 2023, 159(9): 094801.
- Characterizing surface-confined interfacial water at graphene surface by in situ Raman spectroscopyWang, Yao-Hui; Jin, Xin; Xue, Minmin; Cao, Mao-Feng; Xu, Fan; Lin, Gao-Xiang; Le, Jia-Bo; Yang, Wei-Min; Yang, Zhi-Lin; Cao, Yang; Zhou, Yinghui; Cai, Weiwei; Zhang, Zhuhua; Cheng, Jun*; Guo, Wanlin; Li, Jian-Feng*7/19/2023Joule, 2023, 7(7): 1652-1662.
- Deciphering the Anomalous Acidic Tendency of Terminal Water at Rutile(110)–Water InterfacesZhuang, Yong-Bin; Cheng, Jun*5/23/2023The Journal of Physical Chemistry C, 2023, 127(22): 10532-10540.
- Band Alignment of 2D Material–Water InterfacesWen, Xiaojian; Fan, Xue-Ting; Jin, Xiangfeng; Cheng, Jun*2/17/2023The Journal of Physical Chemistry C, 2023, 127(8): 4132-4143.
- Switching of Redox Levels Leads to High Reductive Stability in Water-in-Salt ElectrolytesWang, Feng; Sun, Yan; Cheng, Jun*2/9/2023Journal of the American Chemical Society, 2023, 145(7): 4056-4064.
热门标签
Coupling Electronic Effects
Multiscale Interface Model
Interfacial Structure
Computational Spectroscopy
Graphene in Contacat with Water
Electrolytes
MLMD
uMLP
relay catalysis
knowledge graph
large languuage model
generative pre-trained transformer
HD-SFG
aqueous electrolyte
Molecular Structure
Nuclear Magnetic Resonance Spectroscopy
Spectroscopy
NMR
Deep learning
Molecules
Redox reactions
Ab-initio molecular dynamics
Machine learning
Interfacial water
Molecular dynamics
Deprotonation
Free energy
Heterogeneous catalysis
Surface chemistry
Graphene
Electrochemistry
Operando measurement
Interfaces
Acidity
Electrical conductivity