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| Conference Tools for MS&T24: Materials Science & Technology |
About this Symposium |
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| Meeting | MS&T24: Materials Science & Technology |
| Symposium | Advanced Characterization of Materials for Nuclear, Radiation, and Extreme Environments V |
| Sponsorship | TMS: Nuclear Materials Committee |
| Organizer(s) | Cheng Sun, Clemson University Caitlin A. Kohnert, Los Alamos National Laboratory Cody A. Dennett, Commonwealth Fusion Systems Samuel A. Briggs, Oregon State University Michael Philip Short, Massachusetts Institute Of Technology Keyou Mao, Florida State University Khalid Hattar, University of Tennessee Knoxville Yuanyuan Zhu, University of Connecticut |
| Scope | In the last decade, a wealth of new characterization methods, in-situ experimental techniques, and machine learning have emerged to drastically increase the speed and fidelity with which microstructure, and its dynamic evolution, can be characterized. This symposium solicits presentations that apply any of these advanced techniques to the study of materials structure, properties, and performance in irradiation and other extreme environments, e.g., nuclear energy and space applications. These technique advancements have occurred in areas including microstructural characterization, thermophysical property measurement, in situ measurements, and small-scale mechanical property testing. There is a specific interest in techniques that directly impact materials research for environments exhibiting high radiation fields, extreme temperatures, and corrosive or chemically reactive environments. In addition to the extremes present during routine operations, off-normal events, or transients, such as the aggressive thermal oxidation and decomposition of plasma facing components during air ingress accidents, call for rapid material innovations at this defining moment of rehabilitation for nuclear energy systems. The unique data provided by these advanced characterization tools also provide a new bridge to enhance the framing, refining, and validation of predictive models. With successful recurring in the past four years, the symposium of this year is expanded to include advanced data-driven methods in materials characterization.
Specific topics include, but are not limited to: |
| Abstracts Due | 05/15/2024 |
PRESENTATIONS APPROVED FOR THIS SYMPOSIUM INCLUDE |
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