Researchers developed a robust, cost-effective, and easy-to-use cap-based technique for spatial proteome mapping, addressing the lack of accessible proteomics technologies for studying tissue heterogeneity and microenvironments.

PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.

PNNL Ocean Engineer James McVey collaborates with U.S. company Noria Energy on floating solar technologies through DOE voucher program.

The nation is closer to its offshore wind energy goals than ever before, but better wind forecasting is still needed. To address this challenge, PNNL and collaborators are charting a new course with help from novel technology.

PNNL signs memorandum of understanding with Oregon State University to support marine science and technology advancements.

PNNL convenes ocean leaders to tackle climate challenges and support the Ocean Climate Action Plan.

Advanced proteomic analysis tools dig deep into human blood plasma to understand the molecular nature of advanced alcoholic disease.