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

New apps help researchers with statistical analyses of data.

A team of researchers from PNNL provided technical knowledge and support to test a suite of techniques that detect genetically modified bacteria, viruses, and cells.

Researchers unveil user-friendly software to keep complex projects on budget and on schedule.

PNNL researchers combined deep operator networks with spectral methods to efficiently and accurately solve complex equations.

A new web-based tool provides easy-to-understand progress metrics and other data about groundwater cleanup sites overseen by the DOE Office of Environmental Management.