About this Abstract |
Meeting |
2025 TMS Annual Meeting & Exhibition
|
Symposium
|
Computational Thermodynamics and Kinetics
|
Presentation Title |
Applying Computer Vision to Electron
Micrography in AI-Supported Alloy Synthesis and Solidification |
Author(s) |
Kaelin Mittel, Taylor D. Sparks |
On-Site Speaker (Planned) |
Taylor D. Sparks |
Abstract Scope |
This work seeks to explore how computer vision can be applied to scanning electron micrography of alloy surfaces. The use of machine learning has enabled a great increase in the current rate of materials discovery; however, computer vision has seen little application in the world of materials discovery. During the course of this work, computer vision will be used in the analysis of scanning electron micrographs of thin film alloys of two highly immiscible metals, germanium and tin. The goal is to generate an image segmentation model to identify and characterize nucleation features found in scanning electron micrographs for discovering methods for synthesizing glassy alloys of these two elements with broader implications for the practice of alloy synthesis. The expected outcome is the discovery of the best solidification techniques and parameters for creating a perfectly disordered alloy of tin and germanium through use of computer vision and tabular regression. |
Proceedings Inclusion? |
Planned: |
Keywords |
Solidification, Machine Learning, Characterization |