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Advanced Algorithm for Machine Learning Techniques
  • High-Throughput Computational Screening of Electrocatalysts by Active Machine Learning for First-principles Database

  • Multiscale Molecular Dynamics Simulations Driven by Machine Learning API
  • Development and Application of Artificial Convolutional Neural Networks for Efficient Energy Materials and Processes
Materials Simulation
  • Molecular-level Mechanism Elucidation for Reactions in Energy Materials

  • Development of Ab-initio Thermodynamic and Kinetic Theories to Predict Material Properties

  • Computational Radioactive Chemistry Applied to Spent Nuclear Fuel Management and Toxic Gas Removal

Materials Design from Scratch
  • Discovery of Cost-effective and Active Nanoparticles for Electrochemically Functional Materials

  • Design of the Next Generation Battery Materials

  • Integration of Quantum Mechanics and Machine Learning to Material Design Process

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