Researchers at PNNL have developed an interpretable, lightweight AI model that can easily predict weld microstructure features using only basic machine sensor inputs.

Engineers at PNNL devised a system that allows radar antennae to maintain stable orientation while mounted on platforms in open water that pitch and roll unpredictably. They were recently invited to participate in DOE's I-Corps program.

PNNL's accomplishments in FY 2024 help address the remaining challenges the wind industry faces.

A streamlined informatics workflow that automatically processes complex data and provides the locations of double bonds in lipids.

Hi-C metagenomics-informed phage-host infection networks detected in soil pre- and post-drying.

Metabolomics analysis revealed differences in metabolome profiles for two distinct modes of fungal wood decay.

DOE announced a new project, led by PNNL and National Renewable Energy Laboratory, to expand wind energy transmission off the nation’s West Coast.

Data from increasingly complex mass spectrometry instruments met with adaptable data analysis solution.