Machine Learning Guided Screen and Design of Perovskite Oxides for High-Temperature Oxygen Sensing
- National Energy Technology Laboratory (NETL)
- NETL Site Support Contractor, National Energy Technology Laboratory
- NETL
Machine learning (ML) is a powerful tool for functional material design. In this work, we combine first-principles density function theory with ML to develop perovskite database and design O<sub>2</sub> sensors for harsh environmental applications.
- 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)
- DOE Contract Number:
- ;
- OSTI ID:
- 3023604
- Resource Type:
- Conference poster
- Conference Information:
- Conference Name: APS Global Physics Summit 2026 Location: Denver, CO, United States Start Date: 3/15/2026 12:00:00 AM End Date: 3/20/2026 12:00:00 AM
- Country of Publication:
- United States
- Language:
- English
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