machine learning – Science and Technology of Advanced Materials 日本語版

Machine learning approaches for predicting and validating mechanical properties of Mg rare earth alloys for light weight applications

Engineering and Structural materials
2025.02.03
Acquiring and transferring comprehensive catalyst knowledge through integrated high-throughput experimentation and automatic feature engineering

Materials Informatics
2025.02.03
Integrating machine learning with advanced processing and characterization for polycrystalline materials: a methodology review and application to iron-based superconductors

Focus on New Methodology for Developing Innovative Materials
2025.01.21
Systematic searches for new inorganic materials assisted by materials informatics

Focus on New Methodology for Developing Innovative Materials
2024.12.20
Theoretical and data-driven approaches to semiconductors and dielectrics: from prediction to experiment

Focus on New Methodology for Developing Innovative Materials
2024.12.13
Emerging computational and machine learning methodologies for proton-conducting oxides: materials discovery and fundamental understanding

Focus on New Methodology for Developing Innovative Materials
2024.11.15
Exploring new useful phosphors by combining experiments with machine learning

Focus on New Methodology for Developing Innovative Materials
2024.11.07
Multicrystalline informatics: a methodology to advance materials science by unraveling complex phenomena

Focus on New Methodology for Developing Innovative Materials
2024.09.19
Machine learning prediction of the mechanical properties of injection-molded polypropylene through X-ray diffraction analysis

Focus on Dr. Ariga 60th Anniversary: From Nanotechnology to Nanoarchitectonics
2024.08.15
Aging heat treatment design for Haynes 282 made by wire-feed additive manufacturing using high-throughput experiments and interpretable machine learning

Engineering and Structural materials
2024.05.29
Machine learning strategy to improve impact strength for PP/cellulose composites via selection of biomass fillers

Focus on Dr. Ariga 60th Anniversary: From Nanotechnology to Nanoarchitectonics Select: 60 Materials Informatics
2024.05.29
Prediction of martensite start temperature of steel combined with expert experience and machine learning

Materials Informatics
2024.05.29