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Science and Technology of Advanced Materials 日本語版
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machine learning

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  • 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
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