145 citations · 149 across the 2 of their papers we have counts for
5 papers
Charting Lattice Thermal Conductivity of Inorganic Crystals
Taishan Zhu, Sheng Gong, Tian Xie +2
Thermal conductivity is a fundamental material property but challenging to predict, with less than 5% out of about synthesized inorganic materials being documented. In this…
Predicting charge density distribution of materials using a local-environment-based graph convolutional network
Sheng Gong, Tian Xie, Taishan Zhu +4
Electron charge density distribution of materials is one of the key quantities in computational materials science as theoretically it determines the ground state energy and practic…
Graph Dynamical Networks for Unsupervised Learning of Atomic Scale Dynamics in Materials
Tian Xie, Arthur France-Lanord, Yanming Wang +2
Understanding the dynamical processes that govern the performance of functional materials is essential for the design of next generation materials to tackle global energy and envir…
Hierarchical Visualization of Materials Space with Graph Convolutional Neural Networks
Tian Xie, Jeffrey C. Grossman
The combination of high throughput computation and machine learning has led to a new paradigm in materials design by allowing for the direct screening of vast portions of structura…
Machine Learning Enabled Computational Screening of Inorganic Solid Electrolytes for Dendrite Suppression with Li Metal Anode
Zeeshan Ahmad, Tian Xie, Chinmay Maheshwari +2
Next generation batteries based on lithium (Li) metal anodes have been plagued by the dendritic electrodeposition of Li metal on the anode during cycling, resulting in short circui…