17 citations · 17 across the 2 of their papers we have counts for
4 papers · 1 filter
A Universal Machine Learning Model for Elemental Grain Boundary Energies
Weike Ye, Hui Zheng, Chi Chen +1
The grain boundary (GB) energy has a profound influence on the grain growth and properties of polycrystalline metals. Here, we show that the energy of a GB, normalized by the bulk…
Accelerating Materials Discovery with Bayesian Optimization and Graph Deep Learning
Yunxing Zuo, Mingde Qin, Chi Chen +4
Machine learning (ML) models utilizing structure-based features provide an efficient means for accurate property predictions across diverse chemical spaces. However, obtaining equi…
Learning Properties of Ordered and Disordered Materials from Multi-fidelity Data
Chi Chen, Yunxing Zuo, Weike Ye +2
Predicting the properties of a material from the arrangement of its atoms is a fundamental goal in materials science. While machine learning has emerged in recent years as a new pa…
Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals
Chi Chen, Weike Ye, Yunxing Zuo +2
Graph networks are a new machine learning (ML) paradigm that supports both relational reasoning and combinatorial generalization. Here, we develop universal MatErials Graph Network…