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.

PNNL’s Richard Saldanha will lead a new project to benchmark and validate models of cosmic ray exposure

PNNL is honoring its postdoctoral researchers as part of the fourteenth annual National Postdoc Appreciation Week with seven profiles of postdocs from around the Laboratory.

Summer internship programs with partnering colleges provide pathways for students to explore careers in science, technology, engineering, and math.

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