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

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

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.