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Meeting Materials Science & Technology 2020
Symposium Computation Assisted Materials Development for Improved Corrosion Resistance
Organizer(s) Rishi Pillai, Oak Ridge National Laboratory
Christopher David Taylor, Dnv Gl
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:

1. Modeling and simulation of aqueous and/or high temperature corrosion processes
2. Modeling of microstructural evolution (oxide scale morphology, alloy microstructure)
3. Modeling and simulation of oxide scale cracking and spallation
4. Multiscale/multiphysics modeling strategies to predict influence of alloy composition and exposure conditions on high temperature oxidation behavior
5. Machine learning and/or ICME for design of corrosion resistant materials
6. Predictive modelling of materials degradation and lifetime in corrosive environments

Abstracts Due 05/31/2020
Proceedings Plan Planned: At-meeting proceedings

Applying Machine Learning to Determine the Corrosion Resistance of Alloys
Assessing High Temperature Durability for Long-term Applications
Development of a Multiscale Corrosion Model for Valve Steels in a Gasoline Engine Environment
High Temperature Oxidation Lifetime Modeling of FeCr and NiCr Foils in Water Vapor
Introductory Comments: Computation Assisted Materials Development for Improved Corrosion Resistance
Machine Learning to Predict Cyclic Oxidation of NiCr-based alloys
Metal-Oxide Bond-energy Models for Bond Energies of Alloy Oxides in Corrosion
Simulation of Dissolution of \Gamma\Prime Precipitates in Ni-base Superalloys during Oxidation
Tailoring the Microstructure of Eutectoid Steels during Annealing for Improved Corrosion Resistance: Insights from Phase-field Simulations

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