[Hirotoshi Mori] Cooperation of molecular simulation and machine learning for exploring novel functional materials realized with specific mixing rates

Research Director

Hirotoshi Mori

Hirotoshi Mori

Faculty of Core Research, Ochanomizu University
Associate Professor

Outline

In mixtures, intermolecular interaction shows nonlinearity to mixing rates. Using the nonlinearity, we can create novel functional materials such as mixed refrigerants. However, physicochemical properties of mixtures have been explained by experimental results, i.e., “activities”, which can be defined as a difference from linear summation for properties of components in mixtures. There has been no theory to predict activities. This means that huge number of experimental trial had been mandatory to search for novel functions realized with specific mixing rates. In this project, I develop theoretical techniques to predict activities by cooperation of ab initio molecular simulation and machine learning.

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Program

  • CREST
  • PRESTO
  • ACT-I
  • ERATO
  • ACT-C
  • ACCEL
  • ALCA
  • RISTEX
Finish programs
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  • OS_Policy-EN
  • Question-E