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Meeting 2026 TMS Annual Meeting & Exhibition
Symposium Local Chemical Ordering and Its Impact on Mechanical Behaviors, Radiation Damage, and Corrosion
Sponsorship
Organizer(s) Yang Yang, Pennsylvania State University
Matthew Daly, University of Illinois-Chicago
Wenqing Wang, Lawrence Berkeley National Lab
Charles A. Hirst, University of Wisconsin-Madison
Penghui Cao, University of California, Irvine
Irene J. Beyerlein, University of California, Santa Barbara
Scope Recent developments in the field of compositionally complex materials have sparked thought-provoking speculations regarding the role of local chemical ordering (LCO) in various chemistry–microstructure relationships. The practical motivation is clear: LCO could present a new dimension for tuning and designing the behavior of structural and functional materials. Meanwhile, from a fundamental perspective, the ubiquity of LCO suggests that it might become an indispensable component towards predictive physical modeling of compositionally complex materials.

A comprehensive thermodynamic and kinetic framework of LCO and its connections to microstructural evolution and phase stability are still lacking. This absence demonstrates the considerable challenge in working with the staggering chemical complexity of LCO, which lies just beyond the capability of current experimental and computational approaches. In this symposium we will explore emerging trends on computational and experimental efforts in understanding LCO and its impact on materials properties. Our goal is to deepen our understanding of novel concepts and highlight methodological challenges hindering the quantitative characterization of LCO.

Specific topics include:
- LCO impact on defects and microstructural evolution, from the atomistic to the mesoscale.
- Non-equilibrium dynamics and kinetics under extreme driving conditions, including high/cryogenic temperature, radiation, and corrosion
- Experimental characterizations and in-situ techniques, including S/TEM, 4D STEM, SEM, in situ TEM, X-Ray
- Simulation and modeling approaches, including first-principles methods, atomistic simulations, thermodynamic modeling, machine learning, and data-science approaches.

Abstracts Due 07/01/2025
Proceedings Plan Undecided
PRESENTATIONS APPROVED FOR THIS SYMPOSIUM INCLUDE
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