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cs.LG2024★ 3 cited
Improving Performance Prediction of Electrolyte Formulations with Transformer-based Molecular Representation Model
Indra Priyadarsini, Vidushi Sharma, Seiji Takeda +3
Development of efficient and high-performing electrolytes is crucial for advancing energy storage technologies, particularly in batteries. Predicting the performance of battery ele…
cs.LG2023★ 2 cited
MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural Network
Akihiro Kishimoto, Hiroshi Kajino, Masataka Hirose +6
Property prediction plays an important role in material discovery. As an initial step to eventually develop a foundation model for material science, we introduce a new autoencoder…