Discovery of new microscopic structures in surface water on graphene using data science

Koichiro Kato, Yuki Maekawa, Naoki Watanabe, Kenji Sasaoka, Takahiro Yamamoto

研究成果: Contribution to journalArticle査読


We present the first-ever application of a statistical data analysis technique based on a persistent homology method combined with molecular dynamics simulations to determine the microscopic structure of water on graphene. This work assessed the rapid transition in the water structure on going from surface water to free water with increasing distance from the graphene surface, which is one of the most fundamental issues to be resolved in the field of water research. The crossover distance was unexpectedly short at approximately 1 nm, equivalent to three water layers. Within this 1 nm thick layer of surface water, the rotational freedom of tetrahedral water clusters was almost zero due to the presence of the graphene surface. Thus, water on hydrophobic surfaces such as graphene was found to contain a newly-discovered type of water cluster.

ジャーナルJapanese journal of applied physics
出版ステータス出版済み - 2020

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Physics and Astronomy(all)

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