About this Abstract |
| Meeting |
2027 TMS Annual Meeting & Exhibition
|
| Symposium
|
Fundamentals of Sustainable Metallurgy and Materials Science
|
| Presentation Title |
Exploring higher copper composition space for the design of impurity tolerant steels |
| Author(s) |
Gorataone Katlo Batsile, Stella Pedrazzini |
| On-Site Speaker (Planned) |
Gorataone Katlo Batsile |
| Abstract Scope |
Recycling is one strategy in achieving circularity in the steel industry, however impurity elements such as copper, limit the use of lower quality copper-containing scrap in secondary steelmaking. The knowledge of how the mechanical property of a steel varies across the impurity composition space could better inform the setting of compositional limits of such impurities both in the alloy and the scrap, enabling steelmakers to utilise lower-quality scrap steel. Using the composition-property-processing relationship, the focus of this work is on alloy chemistry optimisation for the development of copper-tolerant steels. The results of a combined machine learning and multi-objective optimisation procedure aimed at exploring the mechanical performance of steels with higher copper compositions of greater than 0.15wt% are presented. Alongside the calculation of phase diagrams, the results of the generated candidate alloys and the screening process are presented together with a discussion on the trade-offs and feasibility of the selected candidates. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Sustainability, Iron and Steel, Machine Learning |