Machine learning prediction of self-assembly and analysis of molecular structure dependence on the critical packing parameter
Yuuki Ishiwatari, T. Yokoyama, Tomoya Kojima, Taisuke Banno, Noriyoshi Arai
Abstract
We used machine learning to predict the self-assembly structures of amphiphilic molecules and analyzed the physical factors affecting their morphologies.
Topics & Concepts
Self-assemblyAmphiphileMoleculeMaterials scienceChemical physicsNanotechnologyComputer scienceArtificial intelligenceBiological systemChemistryPolymerCopolymerComposite materialOrganic chemistryBiologyAdvanced Polymer Synthesis and CharacterizationMachine Learning in Materials ScienceSurfactants and Colloidal Systems