A machine learning approach to analyze the structural formation of soft matter via image recognition
Takamichi Terao
Abstract
ABSTRACT A novel method is developed to analyze the structural formation of colloidal particles based on image recognition via a convolutional neural network (CNN). This makes it possible to analyze various complex structures that are difficult to study using a traditional bond-order parameter analysis. Molecular dynamics simulations on soft colloidal systems are performed in quasi two-dimensional and three-dimensional systems, and the efficiency of the proposed method is demonstrated.
Topics & Concepts
Computer scienceSoft matterImage (mathematics)Convolutional neural networkArtificial intelligenceColloidBiological systemArtificial neural networkMaterials sciencePattern recognition (psychology)EngineeringChemical engineeringBiologyMaterial Dynamics and PropertiesMachine Learning in Materials SciencePhase Equilibria and Thermodynamics