Publications

Preprints

  • Towards Designing Highly Conductive Polymer Electrolyte by Machine Learning Assisted Coarse-Grained Molecular Dynamics
    Yanming Wang*, Tian Xie*, Arthur France-Lanord, Arthur Berkley, Jeremiah A. Johnson, Yang Shao-Horn, Jeffrey C. Grossman (*equally contributed)
    Submitted

Journals

2019

  • The effect of chemical variations in the structure of poly (ethylene oxide)-based polymers on lithium transport in concentrated electrolytes
    Arthur France-Lanord, Yanming Wang, Tian Xie, Yang Shao-Horn, and Jeffrey C. Grossman
    Chemistry of Materials, ASAP
    [Link] [PDF]
  • Predicting charge density distribution of materials in a highly transferable approach by local-environment-based graph convolutional network
    Sheng Gong, Tian Xie, Taishan Zhu, Shuo Wang, Eric R. Fadel, Yawei Li, and Jeffrey C. Grossman
    Physical Review B, 100, 184103, 2019
    [Link] [PDF] [arXiv]
  • Graph Dynamical Networks for Unsupervised Learning of Atomic Scale Dynamics in Materials
    Tian Xie, Arthur France-Lanord, Yanming Wang, Yang Shao-Horn, Jeffrey C. Grossman
    Nature Communications, 10, 2667, 2019
    [Link] [News] [PDF] [arXiv] [Code] [Dataset]

2018

  • Hierarchical Visualization of Materials Space with Graph Convolutional Neural Networks
    Tian Xie, Jeffrey C. Grossman
    The Journal of Chemical Physics, 149, 174111, 2018
    [Link] [PDF] [arXiv]
  • Machine Learning Enabled Computational Screening of Inorganic Solid Electrolytes for Suppression of Dendrite Formation in Lithium Metal Anodes
    Zeeshan Ahmad, Tian Xie, Chinmay Maheshwari, Jeffrey C. Grossman, Venkatasubramanian Viswanathan
    ACS Central Science, 4(8), 996-1006, 2018
    [Link] [Media] [PDF] [arXiv]
  • Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties
    Tian Xie, Jeffrey C. Grossman
    Physical Review Letters, 120, 145301, 2018
    [Link] [PDF] [arXiv] [Code]

2016

  • Surpassing the Exciton Diffusion Limit in Single-Walled Carbon Nanotube Sensitized Solar Cells
    Ghada I Koleilat, Michael Vosgueritchian, Ting Lei, Yan Zhou, Debora W Lin, Franziska Lissel, Pei Lin, John WF To, Tian Xie, Kemar England, Yue Zhang, Zhenan Bao
    ACS nano, 10(12), 11258-11265, 2016
    [Link]
  • Chemically Engineered Substrates for Patternable Growth of Two-Dimensional Chalcogenide Crystals
    Mingzhan Wang, Jinxiong Wu, Li Lin, Yujing Liu, Bing Deng, Yunfan Guo, Yuanwei Lin, Tian Xie, Wenhui Dang, Yubing Zhou, Hailin Peng
    ACS nano, 10(11), 10317-10323, 2016
    [Link]

2015

  • Patterning two-dimensional chalcogenide crystals of Bi2Se3 and In2Se3 and efficient photodetectors
    Wenshan Zheng*, Tian Xie*, Yu Zhou*, YL Chen, Wei Jiang, Shuli Zhao, Jinxiong Wu, Yumei Jing, Yue Wu, Guanchu Chen, Yunfan Guo, Jianbo Yin, Shaoyun Huang, HQ Xu, Zhongfan Liu, Hailin Peng (*equally contributed)
    Nature Communications, 6, 6972, 2015
    [Link] [PDF]

Talks

2019

  • Understanding the atomic scale dynamics in materials with unsupervised learning from molecular dynamics.
    Tian Xie, Arthur France-Lanord, Yanming Wang, Yang Shao-Horn, Jeffrey Grossman
    MRS Fall Meeting, Boston, MA.
    [Link] [PDF]
  • [Invited] High Throughput, Rapid Materials Design for Energy Storage
    Tian Xie, Jeffrey Lopez
    MIT Energy Initiative Annual Research Conference, Cambridge, MA
  • [Invited] Graph neural networks as a general framework for the design and understanding of materials
    Tian Xie
    Computational Chemistry and Machine Learning Workshop, Xiamen, China
  • [Invited] Unsupervised Learning of Atomic Scale Dynamics in Materials
    Tian Xie, Arthur France-Lanord, Yanming Wang, Yang Shao-Horn, Jeffrey Grossman
    Toyota Research Institute, Mountain View, CA

2018

  • CGCNN—A Graph Representation of Materials for Property Prediction and Materials Design
    Tian Xie, Jeffrey Grossman
    MRS Fall Meeting, Boston, MA
    [Link] [PDF]
  • Continuous Representation of Chemical Environments for the Prediction of Material Properties
    Tian Xie, Arthur France-Lanord, Yanming Wang, Jeffrey Grossman
    APS March Meeting, Los Angeles, CA
    [Link]

2017

  • Graph Representation of Periodic Systems for Accurate and Explainable Prediction of Material Properties via Machine Learning
    Tian Xie, Jeffrey C. Grossman
    MRS Fall Meeting, Boston, MA
    [Link]

Posters

2018

  • CGCNN: a graph representation of materials for property prediction and materials design
    Tian Xie, Jeffrey Grossman
    MRL Materials Day, Cambridge, MA
    [Link] [PDF] [Highlight]
  • Understanding Lithium-ion Transport with Deep Neural Networks
    Tian Xie, Arthur France-Lanord, Yanming Wang, Yang Shao-Horn, Jeffrey C. Grossman
    TRI Accelerated Materials Design & Discovery workshop, Redwood City, CA
    [Link]
  • Artificial Intelligence for Accelerated Materials Design
    Tian Xie, Arthur France-Lanord, Yanming Wang, Yun Liu, Jeffrey C. Grossman
    MIT Intelligence Quest Launch, Cambridge, MA
    [Link] [PDF]