||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
5. Predictive modelling of materials degradation and lifetime in corrosive environments