Extracting an Empirical Intermetallic Hydride Design Principle from Limited Data via Interpretable Machine Learning.
Abstract not provided.
- Research Organization:
- Sandia National Laboratories (SNL-CA), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Fuel Cell Technologies Program (EE-2H)
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 1763612
- Report Number(s):
- SAND2020-0961C; 683215
- Country of Publication:
- United States
- Language:
- English
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