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Meeting TMS Specialty Congress 2024
Symposium Accelerating Discovery for Mechanical Behavior of Materials 2024
Organizer(s) Aeriel D. Murphy-Leonard, Ohio State University
Frank W. DelRio, Sandia National Laboratories
Brad L. Boyce, Sandia National Laboratories
Daniel S. Gianola, University of California, Santa Barbara
John J. Lewandowski, Case Western Reserve University
Erica Thea Lilleodden, Fraunhofer Insitute for Microstructure of Materials and Systems (IMWS)
Pania Newell, The University Of Utah
Corinne E. Packard, Colorado School of Mines
Scope Accelerating Discovery for Mechanical Behavior of Materials 2024, a brand new TMS event, will encompass cutting-edge research and development efforts surrounding mechanical behavior over a wide range of material types, with an emphasis on the underlying microstructural causes. This meeting will highlight the different techniques and methodologies that research groups are developing to understand the multi-scale mechanisms used in the explore mechanical behavior in microstructurally and compositionally complex alloys. This unique platform will promote deep discussions and collaborations across industry, government, and academia.

Late Breaking News Abstracts are now being collected by April 15, 2024.

Abstracts are requested under the following topics:

Student Poster Competition - Mechanical Behavior

Accelerated Approaches

• Accelerating Materials Discovery via Machine Learning (e.g., in model-experiment fusion, validation, uncertainty quantification)

• Autonomous Characterization & Property Evaluation

• High-Throughput Techniques (Including Nanoindentation, Tribology, Atomic Force Microscopy,

• Data Sharing and Multimodal Data Fusion in the Mechanical Behavior of Materials


• Multi-objective Optimization of Materials

• Co-optimization of Materials and Topology Defects by Design

• Design of Robust Materials for Hydrogen Storage and other Energy Applications

• Digital Twins/Validation

• Microstructural Optimization for Mechanical Properties (I.E., Microstructure-Properties Linkage)

Machine Learning

• Discovering Constitutive Relationships using ML

• Fusion Of Mechanical Testing & Characterization Techniques to Accelerate Materials Development

• Bayesian Design of Experiments

• Machine Learning Applications - Multiscale and Multiphysics (E.G., Model-Experiment Fusion, Validation, Uncertainty Quantification)

In-situ and In-process of Extreme Environments

• In Situ Testing and Characterization

• In-Process and Operando Control of Mechanical Properties During Processing

• Materials Behavior and Testing Under Extreme Environment: Hydrogen, Temperature, Shock, etc.

• Coupled Extremes

• Climate and long-term aging

Mechanics of Novel Materials

• Mechanical Behavior in Multifunctional Materials

• Mechanics Of Biological & Nature-inspired Systems

• Metamaterials Testing & Optimization

• Nano-Architected Materials

Abstracts Due 04/15/2024
Proceedings Plan Definite: Other
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