108 citations · 342 across the 19 of their papers we have counts for
6 papers · 1 filter
AI-guided inverse design and discovery of recyclable vitrimeric polymers
Yiwen Zheng, Prakash Thakolkaran, Agni K. Biswal +6
Vitrimer is a new, exciting class of sustainable polymers with the ability to heal due to their dynamic covalent adaptive network that can go through associative rearrangement reac…
Accurate battery lifetime prediction across diverse aging conditions with deep learning
Han Zhang, Yuqi Li, Shun Zheng +4
Accurately predicting the lifetime of battery cells in early cycles holds tremendous value for battery research and development as well as numerous downstream applications. This ta…
Overcoming the Size Limit of First Principles Molecular Dynamics Simulations with an In-Distribution Substructure Embedding Active Learner
Lingyu Kong, Jielan Li, Lixin Sun +7
Large-scale first principles molecular dynamics are crucial for simulating complex processes in chemical, biomedical, and materials sciences. However, the unfavorable time complexi…
BatteryML:An Open-source platform for Machine Learning on Battery Degradation
Han Zhang, Xiaofan Gui, Shun Zheng +3
Battery degradation remains a pivotal concern in the energy storage domain, with machine learning emerging as a potent tool to drive forward insights and solutions. However, this i…
Overcoming the Barrier of Orbital-Free Density Functional Theory for Molecular Systems Using Deep Learning
He Zhang, Siyuan Liu, Jiacheng You +6
Orbital-free density functional theory (OFDFT) is a quantum chemistry formulation that has a lower cost scaling than the prevailing Kohn-Sham DFT, which is increasingly desired for…
Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning
Shuxin Zheng, Jiyan He, Chang Liu +15
Advances in deep learning have greatly improved structure prediction of molecules. However, many macroscopic observations that are important for real-world applications are not fun…