September 30, 2024 article Dynamic data-driven multiscale modeling for predicting the degradation of a 316L stainless steel nuclear cladding material Journal of Nuclear Materials DOI: 10.1016/j.jnucmat.2024.155429 OpenAlex Authors 0 Author list not loaded yet. Cited by 0 stored of 3 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 An artificial neural network for surrogate modeling of stress fields in viscoplastic polycrystalline materials 2023 npj Computational Materials article Materials Science Machine Learning in Materials Science Open access 97 citations Machine-learning-based surrogate modeling of microstructure evolution using phase-field 2022 Computational Materials Science article Materials Science Machine Learning in Materials Science 62 citations Minimizing thickness variation in monolithic U-10Mo fuel foil and Zr interlayer during hot rolling: A microstructure-based finite element method analysis 2022 Materials Today Communications article Materials Science Nuclear Materials and Properties Open access 6 citations 3 results