Thin oxide films play an important role in electronics and energy storage. Researchers in PNNL’s film growth laboratory create, explore, and improve new thin oxide films.
Mitra Taheri served as a co-editor on a special issue of the Materials Research Society Bulletin, which also featured work from Daniel Schreiber and Cindy Powell.
Machine learning models help identify important environmental properties that influence how often extreme rain events occur with critical intensity and duration.
Data-driven autonomous technology to rapidly design and deliver antiviral interventions targeting SARS-CoV-2 to reduce drug discovery timeline and advance bio preparedness capabilities.
Data scientist Jung Lee accepted the position of review editor for Frontiers in Computational Neuroscience after serving as a guest editor for a special issue.
The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.
PNNL mathematician Aaron Luttman contributed to the organizing committee for workshop exploring robust machine learning and artificial intelligence systems for the U.S. Army.