4 papers
Composition-agnostic prediction of self-assembly in multicomponent amphiphile mixtures from molecular structure
Yuuki Ishiwatari, Takahiro Yokoyama, Tomoya Kojima +2
Predicting self-assembly in multi-component amphiphilic systems is challenging due to the complexity of intercomponent interactions and the combinatorial growth of possible formula…
Machine learning-enabled exploration of mesoscale architectures in amphiphilic-molecule self-assembly
Takeo Sudo, Satoki Ishiai, Yuuki Ishiwatari +3
Amphiphilic molecules spontaneously form self-assembled structures of various shapes depending on their molecular structures, the temperature, and other physical conditions. The fu…
Machine learning prediction of self-assembly and analysis of molecular structure dependence on the critical packing parameter
Yuuki Ishiwatari, Takahiro Yokoyama, Tomoya Kojima +2
Amphiphilic molecules spontaneously form self-assembly structures based on physical conditions such as molecular structure, concentration, and temperature. These structures exhibit…
Structure Formation of Amphiphilic Nanocubes at Rest and Under Shear
Takahiro Yokoyama, Yusei Kobayashi, Noriyoshi Arai +1
We investigate the self-assembly of amphiphilic nanocubes under rest and shear using molecular dynamics (MD) simulations and kinetic Monte Carlo (KMC) calculations. These particles…