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Meeting MS&T21: Materials Science & Technology
Symposium Computation Assisted Materials Development for Improved Corrosion Resistance
Organizer(s) Rishi Pillai, Oak Ridge National Laboratory
Laurence D. Marks, Northwestern University
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

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

Abstracts Due 04/15/2021
Proceedings Plan Undecided

Back to the Basics: Revisiting Copper to Build Thermodynamic Corrosion Models
Computational Modeling of Corrosion and Mechanical Failure in Magnesium-Aluminum Vehicle Joints
Development of a Damage Function for Galvanic Corrosion Degradation of Coated Al Alloy Systems
Factors That Influence Materials Corrosion and How Modeling May Predict These Effects
First Steps Towards a Coupled Thermodynamic-kinetic Model to Predict Sulfate Deposit Induced Hot Corrosion of Aluminized Ni-based Superalloys
Hydrothermal Corrosion of Silicon Carbide
Modeling of High-temperature Corrosion of Zirconium Alloys Using the eXtended Finite Element Method (X-FEM)
Modelling Alkoxide Corrosion Initiation of Pure-aluminum in Ethanol with Integrated Simulation-based Experimental Methods
Modelling Microstructural Evolution of Aluminide Coatings on Ni-based Superalloys
Morphological Stability of Electrostrictive Thin Films
P2-17: Development of Rhenium Free Heat-resistant Nickel Alloy for the Cast Blades Production by the Method of Directional Crystallization
Predictive Modeling of Microstructure Induced Variations in the Sensitization Response of 5XXX Aluminum Alloys
Solubility Based Prediction of Corrosion in Molten Chloride Salts
Understanding and Reducing Bias in Machine Learning to Enhance Its Predictive and Extrapolative Capabilities: Application to the Oxidation Kinetics and Spallation Behavior of High-temperature NiCr-based Alloys

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