October 26, 2024 article Open access What can machine learning help with microstructure-informed materials modeling and design? MRS Bulletin DOI: 10.1557/s43577-024-00797-4 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 0 stored of 36 References 3 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access A mixed formulation for physics-informed neural networks as a potential solver for engineering problems in heterogeneous domains: comparison with finite element method 2022 arXiv (Cornell University) preprint Physics and Astronomy Model Reduction and Neural Networks Open access 216 citations Material modeling for parametric, anisotropic finite strain hyperelasticity based on machine learning with application in optimization of metamaterials 2021 International Journal for Numerical Methods in Engineering article Engineering Elasticity and Material Modeling Open access 60 citations A Machine Learning Enabled Image‐data‐driven End‐to‐end Mechanical Field Predictor For Dual‐Phase Steel 2023 PAMM article Materials Science Machine Learning in Materials Science Open access 10 citations 3 results