3 citations · 5 across the 3 of their papers we have counts for
3 papers
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…
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…
AI powered, automated discovery of polymer membranes for carbon capture
Ronaldo Giro, Hsianghan Hsu, Akihiro Kishimoto +6
The generation of molecules with Artificial Intelligence (AI) is poised to revolutionize materials discovery. Potential applications range from development of potent drugs to effic…