Bridging Scale Gaps in Multiscale Materials Modeling in the Age of AI
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Manuscript Submission Deadline:
April 01, 2024
Co-Guest Editors: Liang Qi
Publication Date: October 2024
Keywords: Advanced Materials, Advanced Processing, Computational Materials Science & Engineering, Modeling and Simulation, Physical Properties
Scope: Multiscale Materials Modeling has seen decades of efforts and progress, but challenges remain in bridging different length/time scales across models. Lower-scale simulation results are difficult to construct into physics-based constitutive equations, hampering their transferability to higher-scale models. These challenges intensify with growing interests in chemically complex materials and extreme conditions in advanced materials processing. The emergence of data-driven techniques – particularly artificial intelligence (AI) – offers new possibilities to overcome these obstacles. This special topic focuses on the integration of computational material science and AI, highlighting their applications in bridging different-scales models, towards a better explainability/prediction of relevant experimental observations.
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