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

PNNL will engage with transmission planners and other regional partners through technical assistance and listening sessions with the goal of exploring opportunities to integrate equity into transmission planning.

Researchers designed ultra-low radiation cables to reduce background noise for highly sensitive neutrino and dark matter detectors.

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

ExaGO, a power grid simulation and optimization platform developed at PNNL is the first of its kind to run on Frontier.