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Meeting 2025 TMS Annual Meeting & Exhibition
Symposium Materials Aging and Compatibility: Experimental and Computational Approaches to Enable Lifetime Predictions
Sponsorship TMS Structural Materials Division
TMS: Mechanical Behavior of Materials Committee
TMS: Corrosion and Environmental Effects Committee
Organizer(s) Bishnu P. Khanal, Sandia National Laboratories
Michael A. Melia, Sandia National Laboratories
Coby L. Davis, Sandia National Laboratories
Kerri JM Blobaum, Lawrence Livermore National Laboratory
Anthony Van Buuren, Lawrence Livermore National Laboratory
Nan Butler, Sandia National Laboratories
Scope The interplay between a material’s fundamental aging behavior and its compatibility within a system can have significant impact on highly complex and expensive technologies found in fields such as: aerospace, satellite and space exploration, nuclear weapon programs, etc. However, the understanding of a material’s behavior over its entire service life and that material’s compatibility within its system during that time is limited and difficult to predict. Emerging advanced manufacturing industries add to the aging and compatibility knowledge gaps by introducing completely new materials or fabricating legacy materials with techniques that allow for new design capabilities causing them to age differently than their wrought counterpart (additively manufactured (AM) metals vs. wrought counterparts). Therefore, it is highly desirable to explore and discuss materials aging and compatibility by establishing their scientific basis and developing modeling/predictive tools. This symposium provides an excellent platform for scientists, researchers, and engineers to present and discuss recent research advances on experimental and computational modeling on fundamental materials behaviors and their compatibility under real and accelerated environments.

Topics of interest for abstract submission include (but not limited to):
1.Scientifically informed accelerated aging methodologies.
2.Experimental, computational, and analytical evaluation of materials degradation during accelerated aging environments with individual or some combination of stressors such as mechanical, corrosive, thermal, etc.
3.Compatibility studies for materials joining: brazing, welding and soldering.
4.Long life system compatibility of two or more different materials.
5.Discussion of simulated and experimental data similitude as a method to predict lifetimes.
6.Machine learning approaches to predict material/component lifetime.

Abstracts Due 07/15/2024
Proceedings Plan Planned:
PRESENTATIONS APPROVED FOR THIS SYMPOSIUM INCLUDE

A Mean-field Approach for High-temperature Shape Memory Alloys
Accelerated Aging and Lifetime Performance Predictions of Silicone Cushions Under Compression
Accelerated aging of aluminum alloys for long-term predictions of corrosion under atmospheric conditions of temperature and relative humidity
Accelerated oxidation of epoxy thermosets with increased O2 pressure
Accelerating Compatibility Assessments through Adoption of Selected-Ion Flow-Tube Mass Spectrometry (SIFT-MS)
Accelerating Computational Calculations of Galvanic Corrosion using Machine Learning
Bimodal Microstructure Modeling due to Non-Isothermal Loading in Ni-based Single-crystal Superalloys via Phase-field Method
Characterization of localized oxidation in tantalum and cracking susceptibility at high temperatures using Auger Electron Spectroscopy
Characterization of Long Term Service Effect on Turbine Blade Alloy
Environmentally assisted corrosion testing of 7xxx series aluminum to create an SCC susceptibility profile for temperature, humidity, and stress through accelerated testing.
High-throughput Creep Characterization for Use in Accelerated Aging Prediction
Impacts of aging additively manufactured silicone polymers in the presence of organic solvents
Kinetic assessments of TATB formulations after mild thermal aging
Materials Compatibility Testing and Assessment for Materials Reliability
Mechanical Performance, Aging, and Compatibility of Additive Manufactured Silicone Elastomers
Modeling Corrosion: Efficient Models and Validation for Long Term Degradation
Predicting compatibility and aging at the system-level with a Reaction, Sorption, Transport, and chemo-mechanics (ReSorT-M) model
Predicting Electrochemical Responses Using Machine Learning
Predicting Photo-Oxidative Embrittlement of a Semicrystalline Thermoplastic from Micromechanical Damage
Probing Bulk Mechanical Properties of Silicones Over the Course of Long-term Compressive Strain
Research on Shape Optimization of Work Roll in Hot Rolling
Strain-Controlled High-Cycle Fatigue of Aged Solder Joints for High-Reliability Environments
Towards High Throughput Materials Advancement: Thinking About Database Management in Our Studying-Polymers-on-a-Chip (SPOC) Platform


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