Researchers developed a machine learning model that can analyze chemical reactions as they happen in an electron microscope.

As leaders in AI and machine learning, PNNL experts are sharing their latest findings at the 36th annual Neural Information Processing Systems (NeurIPS) Conference, Nov. 28–Dec. 9, 2022.

A process developed at PNNL that converts biomass and waste into a chemical intermediate or into gasoline, diesel, and jet fuel is available for commercial licensing.

PNNL researchers teamed up with SambaNova to enhance artificial intelligence for scientific computing.

The Co-Optimization of Fuels & Engines initiative recently outlined six years of research in a findings and impact report.

PNNL researchers design an artificial intelligence-guided electron microscope in a Laboratory Directed Research and Development study.

Scientists from PNNL and the U.S. Department of Agriculture-Forest Services’ Pacific Northwest Research Station have partnered to evaluate potential climate and wildfire adaptation scenarios and resulting benefits from restoration forestry.

A multi-institutional team has developed a deep learning framework to identify novel molecules as drug candidates.

Researchers developed a new tool that combines artificial intelligence and microscopy data to rapidly test new materials for fusion reactor use.

Contributions from researchers across Pacific Northwest National Laboratory (PNNL) were recently recognized in the preliminary findings of a Secretary of Energy Advisory Board (SEAB) report.