A detailed snapshot of proteins by PNNL scientists marks a big step toward a diagnostic blood test for a deadly form of liver disease.

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.

Radha Kishan Motkuri lends skill and knowledge to co-lead special edition journal.

Harnessing the sea for decarbonized energy is the focus of a new collaboration between PNNL and the University of Guam.

Findings show method to better prepare human lung tissue for study; it represents the latest mass spectrometry-based omics advances.

PNNL mathematician Aaron Luttman contributed to the organizing committee for workshop exploring robust machine learning and artificial intelligence systems for the U.S. Army.

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

PNNL scientists Daniel Gaspar and Wei Wang were among nine scientists featured in journal article recognizing 2021-2022 ACS award honorees.

Steven Spurgeon’s research is featured in the cover of the MRS Bulletin along with his team’s invited perspective on the future of machine learning for electron and scanning probe microscopy.

Research published in Journal of Manufacturing Processes demonstrates innovative single-step method to manufacture oxide dispersion strengthened copper materials from powder.

New research findings published in Science Advances (November 2022), help explain the progression of Alzheimer-related dementia in each patient. The findings outline a biological classification system that predicts disease severity.

A PNNL team developed and used a model framework to understand the performance and structural reliability of a state-of-the-art solid oxide electrolysis cell design.

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.

Multidisciplinary teams from research and industry are brought together using management systems developed by a team of software engineers at PNNL.

Tailoring hydrogen-based energy storage solutions to specific real-world applications.

Direct visualization of metal atoms during shear deformation has broad applications from battery design to vehicle lightweighting.

PNNL researchers use machine learning and data analytics to assist with detection of nuclear proliferation and nuclear material trafficking.

Scientists are pioneering approaches in the branch of artificial intelligence known as machine learning to design and train computer software programs that guide the development of new manufacturing processes.

PNNL chemist Ying Zhu was honored as one of the top 40 researchers under the age of 40 in analytical science by The Analytical Scientist.

In honor of National Intern Day, PNNL and intern Jonathan Mills were named among the Top 100 in the nation by early-career recruiting firm WayUp.