Rapid Assessment and Optimization of Electrodes for Solid Oxide Fuel Cells and Electrolyzers using Long-Term Performance Modeling and Machine Learning
Conference
·
OSTI ID:1923800
- NETL
- NETL Site Support Contractor, National Energy Technology Laboratory
Computer vision techniques are combined with NETL’s machine learning based model trained on results from NETL's long-term SOFC/SOEC performance prediction tool, in order to produce a rapid assessment tool for evaluation and improvement of SOC electrodes from more easily collected microstructural data.
- Research Organization:
- National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)
- Sponsoring Organization:
- USDOE Office of Fossil Energy (FE)
- DOE Contract Number:
- Other
- OSTI ID:
- 1923800
- Report Number(s):
- DOE/NETL-2022/3270
- Resource Relation:
- Conference: Conference Name: 23rd International Conference on Solid State Ionics (SSI-23) Location: Boston, Massachusetts, United States Start Date: 7/17/2022 12:00:00 AM End Date: 7/22/2022 12:00:00 AM
- Country of Publication:
- United States
- Language:
- English
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