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Meeting 2025 TMS Annual Meeting & Exhibition
Symposium Algorithms Development in Materials Science and Engineering
Sponsorship TMS Materials Processing and Manufacturing Division
TMS: Computational Materials Science and Engineering Committee
TMS: Integrated Computational Materials Engineering Committee
TMS: Phase Transformations Committee
TMS: Process Technology and Modeling Committee
TMS: Alloy Phases Committee
Organizer(s) Remi Dingreville, Sandia National Laboratories
Saaketh Desai, Sandia National Laboratories
Hojun Lim, Sandia National Laboratories
Jeremy K. Mason, University of California, Davis
Vimal Ramanuj, Oak Ridge National Laboratory
Sam Reeve, Oak Ridge National Laboratory
Douglas E. Spearot, University of Florida
Scope A foundational aspect of Materials Science is to understand, characterize, and predict the underlying mechanisms and behaviors of materials. Computational modeling and simulation provide many critical insights in these efforts, but also require constant development, validation, and application of numerical techniques.

This symposium invites abstracts on the development and application of novel algorithms for materials science and engineering. This year’s symposium will especially focus on (but is not limited to) the following topical areas:

  • Novel methodologies for data mining, machine learning, image processing, microstructure generation, high-throughput databases and experiments.
  • Surrogate and reduced-order modeling, and extracting useful insights from large data sets of numerical and experimental results.
  • Algorithm development to enhance or accelerate classical computational materials science tools including density functional theory, molecular dynamics, Monte Carlo simulation, dislocation dynamics, phase-field modeling, CALPHAD, crystal plasticity, and finite element analysis.
  • Development of novel physics-based, multiscale, multi-physics materials modeling.
  • Algorithm development for fusing and evaluating the quality of multimodal data and their incorporation into computational materials workflows.
  • Uncertainty quantification, statistical metrics from image-based synthetic microstructure generation, model comparisons, and validation studies related to novel algorithms and/or methods in computational material science.
  • Development of novel methodologies for the analysis and management of data, including best practices for `FAIRization’ of data (FAIR: Findable, Accessible, Interpretable, Reproducible), as well as best practices for research software development and dissemination.

Selected presentations will be invited to submit full papers for a IMMI issue (5-10 papers).
Abstracts Due 07/01/2024
Proceedings Plan Planned: TMS Journal: Integrating Materials and Manufacturing Innovation
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