Review of the Synergies Between Computational Modeling and Experimental Characterization of Materials Across Length Scales
R\'emi Dingreville, Richard A. Karnesky, Guillaume Puel, Jean-Hubert, Schmitt

TL;DR
This review explores the integration of computational modeling and experimental characterization across multiple length scales in materials science, highlighting recent advances, applications, and open challenges in multiscale materials research.
Contribution
It provides a comprehensive overview of recent trends in combining predictive modeling with experiments to understand structure-property relationships in materials.
Findings
Computational models are increasingly used as discovery tools in materials engineering.
Experimental data significantly enhance multiscale modeling accuracy.
Several application areas demonstrate successful integration of experiments and modeling.
Abstract
With the increasing interplay between experimental and computational approaches at multiple length scales, new research directions are emerging in materials science and computational mechanics. Such cooperative interactions find many applications in the development, characterization and design of complex material systems. This manuscript provides a broad and comprehensive overview of recent trends where predictive modeling capabilities are developed in conjunction with experiments and advanced characterization to gain a greater insight into structure-properties relationships and study various physical phenomena and mechanisms. The focus of this review is on the intersections of multiscale materials experiments and modeling relevant to the materials mechanics community. After a general discussion on the perspective from various communities, the article focuses on the latest experimental…
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