First-principles calculations with machine learning modeling to predict high-temperature gas sensing materials
- NETL Site Support Contractor, National Energy Technology Laboratory
- Oak Ridge Institute for Science and Education (ORISE)
- NETL
This talk introduced our research on developing sensing materials for harsh environmental applications. By combining first-principles density functional theory simulations with AI/ML approach, we have established a sensor database which can predict candidate materials at given operating conditions.
- Research Organization:
- National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)
- Sponsoring Organization:
- USDOE Office of Fossil Energy and Carbon Management (FECM); USDOE Office of Fossil Energy and Carbon Management (FECM), Office of Carbon Management (FE-20)
- OSTI ID:
- 2586381
- Country of Publication:
- United States
- Language:
- English
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