8 citations · 8 across the 2 of their papers we have counts for
3 papers
cs.LG2022
MGCVAE: Multi-objective Inverse Design via Molecular Graph Conditional Variational Autoencoder
Myeonghun Lee, Kyoungmin Min
The ultimate goal of various fields is to directly generate molecules with desired properties, such as finding water-soluble molecules in drug development and finding molecules sui…
cond-mat.mtrl-sci2022★ 8 cited
Machine Learning-Aided Discovery of Superionic Solid-State Electrolyte for Li-Ion Batteries
Seungpyo Kang, Minseon Kim, Kyoungmin Min
Li-Ion Solid-State Electrolytes (Li-SSEs) are a promising solution that resolves the critical issues of conventional Li-Ion Batteries (LIBs) such as poor ionic conductivity, interf…
cond-mat.mtrl-sci2021
Machine learning aided materials design platform for predicting the mechanical properties of Na-ion solid-state electrolytes
Junho Jo, Eunseong Choi, Minseon Kim +1
Na-ion solid-state electrolytes (Na-SSE) exhibit high potential for electrical energy storage owing to their high energy densities and low manufacturing cost. However, their mechan…