About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
Novel Strategies for Rapid Acquisition and Processing of Large Datasets From Advanced Characterization Techniques
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| Presentation Title |
Frequency-Domain Thermoreflectance Automation for High Throughput Microstructural and Thermal Characterization |
| Author(s) |
Seth David Leavitt, Christopher Nyborg, Troy Munro |
| On-Site Speaker (Planned) |
Seth David Leavitt |
| Abstract Scope |
Thermal diffusivity and thermal transport anisotropy are critical properties in material selection for a wide variety of fields. Frequency-domain thermoreflectance (FDTR) is a non-contact optical technique that measures thermal diffusivity by analyzing the phase lag between modulated heating from a pump laser and the temperature response of a probe laser. Previous methods of FDTR have required significant investments of time and setup due to the precision needed in laser alignment, sample placement, and manual laser frequency modulation. We have developed an automated FDTR workflow that streamlines data collection and processing across multiple orientations, to produce more repeatable and analysis ready data, faster. This work highlights how integrating automated experimental methods can enable the analysis of structural and functional materials. With the consistently increasing demand for materials with tailored thermal properties in fields like nuclear power and biomedical engineering, automation is a critical tool to meet the growing need for data. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Characterization, Thin Films and Interfaces, Other |