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Machine Learning Design of Perovskite Catalytic Properties
Ryan Jacobs, Jian Liu, Harry Abernathy +1
Discovering new materials that efficiently catalyze the oxygen reduction and evolution reactions is critical for facilitating the widespread adoption of solid oxide fuel cell and e…
A Critical Assessment of Electronic Structure Descriptors for Predicting Perovskite Catalytic Properties
Ryan Jacobs, Jian Liu, Harry Abernathy +1
The discovery and design of new materials which can efficiently catalyze the oxygen reduction and evolution reactions at reduced temperatures is important for facilitating the wide…
Time-dependence of SrVO thermionic electron emission properties
Md Sariful Sheikh, Ryan Jacobs, Dane Morgan +1
Thermionic electron emission cathodes are critical components of various high power and high frequency vacuum electronic devices, electron microscopes, e-beam lithographic devices,…
Role of Multifidelity Data in Sequential Active Learning Materials Discovery Campaigns: Case Study of Electronic Bandgap
Ryan Jacobs, Philip E. Goins, Dane Morgan
Materials discovery and design typically proceeds through iterative evaluation (both experimental and computational) to obtain data, generally targeting improvement of one or more…
Predictions and Uncertainty Estimates of Reactor Pressure Vessel Steel Embrittlement Using Machine Learning
Ryan Jacobs, Takuya Yamamoto, G. Robert Odette +1
An essential aspect of extending safe operation of the active nuclear reactors is understanding and predicting the embrittlement that occurs in the steels that make up the Reactor…
Computational Discovery of Fast Interstitial Oxygen Conductors
Jun Meng, Md Sariful Sheikh, Ryan Jacobs +4
New highly oxygen-active materials may enhance many energy-related technologies by enabling efficient oxygen-ion transport at lower temperatures, e.g., below 400 Celsius. Interstit…