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.

Updated flexible software generates and optimizes monitoring programs for detecting potential leaks from geological carbon storage with an enhanced user experience.

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

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

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

A code comparison study demonstrates a leap in the accuracy and reliability of modeling gas hydrate for the discovery and production of natural gas.

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.