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About this Symposium

Meeting MS&T25: Materials Science & Technology
Symposium Integrated Computational Materials Engineering for Physics-Based Machine Learning Models
Sponsorship TMS: Integrated Computational Materials Engineering Committee
Organizer(s) William E. Frazier, Pacific Northwest National Laboratory
Zhengtao Gan, Arizona State University
Lei Li, Pacific Northwest National Laboratory
Yucheng Fu, Pacific Northwest National Laboratory
Philip E. Goins, US Army Research Laboratory
Scope This symposium will include topics pertaining to the improvement and deployment of computational materials approaches through linkages with experimental data, simulations at other length scales, and surrogate models. Applications related to microstructural evolution, mechanical behavior, degradation during processing and in-service are of particular interest. Topics may include:

- Integrated models of material deformation and microstructural evolution in metallic and non-metallic materials.
- Integrated models of microstructural evolution and material degradation.
- Integrated models of material process-structure-property relationship.
- Approaches for the simulation of grain growth, recrystallization, twinning, phase transformations, or related phenomena coupling multiple scale modeling approaches.
- Verification/validation of machine learning models [e.g., physics-informed or data-driven methods] of microstructural evolution and/or response to deformation, aging, and irradiation.
- Novel couplings of experimental methods and data with mesoscale modeling approaches.
- Models using physics-informed or generative machine learning approaches to model the formation of microstructures or microstructural evolution processes.

Abstracts Due 05/15/2025

PRESENTATIONS APPROVED FOR THIS SYMPOSIUM INCLUDE


Understanding and design of metallic alloys guided by integrated phase-field simulations
A GNN based Finite Element Simulations Emulator: Application to Parameter Identification for Aluminum Alloy 6DR1
Ab initio prediction of the magnetic thermodynamics of LaCoO3 pervoskite based on the zentropy theory
Accelerated Nuclear Materials Thermochemistry in MOOSE through Surrogate Modeling
Atomistic and AI-Driven Insights into Ferroelectric Switching in Hybrid Improper Double Perovskite Oxides
Bayesian Optimization of KWN Precipitation Model Parameters for Improved Predictive Performance
Effects of Temperature and Strain Rate on Dynamic Recrystallization and Recovery of Aluminum Alloy 2618
Fe-based alloy design via Graph DNN training and inversion
Machine Learning Model for Estimating the Number of Grains in Ti–6Al–4V XRD Patterns
Physics-Based Machine Learning Framework for Fatigue-Life Estimation in Wrought Mg Alloys
The Study of Iron Strontium through Experiment, Simulation, and Data Science
Thermal response of stochastically modeled mesoscale metal foam


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