About this Abstract |
Meeting |
2023 TMS Annual Meeting & Exhibition
|
Symposium
|
Bulk Metallic Glasses XX
|
Presentation Title |
Genetic Algorithm-assisted Discovery and Characterization of New Metallic Glass Coatings For Extreme Conditions |
Author(s) |
Jerry R. Howard, Leslie Mushongera, Dev Chidambaram, Krista Carlson |
On-Site Speaker (Planned) |
Jerry R. Howard |
Abstract Scope |
Metallic glasses (MGs) are an emerging class of materials possessing high corrosion and wear resistance and ease of fabrication when compared to their crystalline counterparts. However, most previously studied MGs are not useful in high-temperature environments because they undergo the glass transition phenomenon and crystallize below the melting point. In this study, GenMG – an in-house developed genetic algorithm-based tool for the discovery of novel MGs with the desired properties – was used to locate regions of high glass forming ability (GFA) and high-temperature stability in several W-based MG systems. Powders of the predicted optimal MGs were then produced via gas atomization, and the GFA of each composition was measured. MG coatings were then produced via the cold spray method. The corrosion and wear resistance of the coatings were characterized via electrochemical and tribological testing. The measured physiochemical and thermodynamic properties were used to improve future predictions made by GenMG. |
Proceedings Inclusion? |
Planned: |
Keywords |
Modeling and Simulation, High-Temperature Materials, Characterization |