Research Summary

Selected Publications

• 1. Terayama, K., Sumita, M., Tamura, R., Payne, D.T., Chahal, M.K., Ishihara, S. and Tsuda, K.:
  "Pushing property limits in materials discovery via boundless objective-free exploration"
  Chemical Science, 11, 5959-5968 (2020)
• 2. Homma, K., Liu, Y., Sumita, M., Tamura, R., Fushimi, N., Iwata, J., Tsuda, K. and Kaneta, C.:
  "Optimization of heterogeneous ternary Li3PO4-Li3BO3-Li2SO4 mixture for Li-ion conductivity by machine learning"
  The Journal of Physical Chemistry C, 124, 12865-12870 (2020)
• 3. Mehrabi, P., Di Pietrantonio, C., Kim, T.H., Sljoka, A., Taverner, K., Ing, C., Kruglyak, N., Pomès, R., Pai, E.F. and Prosser, R.S.:
  "Substrate-based allosteric regulation of a homodimeric enzyme"
  Journal of the American Chemical Society, 141, 11540-11556 (2019)
• 4. Saito, Y., Shin, K., Terayama, K., Desai, S., Onga, M., Nakagawa, Y., Itahashi, Y.M., Iwasa, Y., Yamada, M. and Tsuda, K.:
  "Deep-learning-based quality filtering of mechanically exfoliated 2D crystals"
  npj Computational Materials, 5, 124 (2019)
• 5. Sakurai, A., Yada, K., Simomura, T., Ju, S., Kashiwagi, M., Okada, H., Nagao, T., Tsuda, K. and Shiomi, J.:
  "Ultranarrow-band wavelength-selective thermal emission with aperiodic multilayered metamaterials designed by Bayesian optimization"
  ACS Central Science, 5, 319-326 (2019)
• 6. Sumita, M., Tamura, R., Homma, K., Kaneta, C. and Tsuda, K.:
  "Li-Ion Conductive Li3PO4-Li3BO3-Li2SO4 Mixture: Prevision through Density Functional Molecular Dynamics and Machine Learning"
  Bulletin of the Chemical Society of Japan, 92, 1100-1106 (2019)
• 7. Sumita, M., Yang, X., Ishihara, S., Tamura, R. and Tsuda, K.:
  "Hunting for organic molecules with artificial intelligence: molecules optimized for desired excitation energies"
  ACS Central Science, 4, 1126-1133 (2018)
• 8. Saito, Y., Oikawa, M., Nakazawa, H., Niide, T., Kameda, T., Tsuda, K. and Umetsu, M.:
  "Machine-learning-guided mutagenesis for directed evolution of fluorescent proteins"
  ACS Synthetic Biology, 7, 2014-2022 (2018)
• 9. Yang, X., Zhang, J., Yoshizoe, K., Terayama, K. and Tsuda, K.:
  "ChemTS: an efficient python library for de novo molecular generation"
  Science and Technology of Advanced Materials, 18, 972-976 (2017)
• 10. Ju, S., Shiga, T., Feng, L., Hou, Z., Tsuda, K. and Shiomi, J.:
  "Designing nanostructures for phonon transport via Bayesian optimization"
  Physical Review X, 7, 021024 (2017)

Recent Research Results

• 

  Jun. 7, 2022
  Fluorescent molecules revealed by quantum chemistry and machine learning

• 

  Aug. 7, 2020
  Machine learning helps find materials that buck the trend

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