Bridging Scale Gaps in Multiscale Materials Modeling in the Age of Artificial Intelligence
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Manuscript Submission Deadline:
May 01, 2025
Co-Guest Editors: Yue Fan
Publication Date: November 2025
Keywords: Computational Materials Science & Engineering, Computer Applications and Process Control, Cyber Infrastructure, ICME, Modeling and Simulation, Multiscale Materials Modeling, Artificial Intelligence
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 interest 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 materials science and AI, highlighting their applications in bridging different-scale models, towards a better explanation/prediction of relevant experimental observations.
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