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| Conference Tools for MS&T24: Materials Science & Technology |
About this Symposium |
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| Meeting | MS&T24: Materials Science & Technology |
| Symposium | Computation Assisted Materials Development for Improved Corrosion Resistance |
| Sponsorship | TMS: Corrosion and Environmental Effects Committee |
| Organizer(s) | Rishi Pillai, Oak Ridge National Laboratory Brian Gleeson, University of Pittsburgh Mathias C. Galetz, DECHEMA-Forschungsinstitut Tianle Cheng, National Energy Technology Laboratory |
| Scope | This symposium will showcase the latest developments in computational assisted design of materials for improved corrosion resistance. Computational modeling studies are sought that (a) provide insights into the mechanisms of corrosion, (b) allow for advanced prediction of corrosion induced degradation, and (c) provide the basis for the development of corrosion resistant materials. Predictive modeling of both aqueous and high temperature corrosion is challenging due to the complexity of the underlying mechanisms, their dependence on scale morphology, alloy microstructure, surface preparation, and lack of thermodynamic-kinetic data. Advances in computing power have provided the impetus for application of modeling methods that utilize one or more approaches such as machine learning, molecular dynamics, density functional theory and phase field to develop new materials and to better understand materials factors that confer or control corrosion resistance.
The symposium encourages, but is not limited to, the following areas of interest: |
| Abstracts Due | 05/15/2024 |
PRESENTATIONS APPROVED FOR THIS SYMPOSIUM INCLUDE |
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