Energy storage is increasingly critical to building a resilient electric grid in the United States—a trend embodied by the Grid Storage Launchpad, a newly inaugurated, 93,000-square-foot facility at PNNL.
A Helios Hydra UX DualBeam, which utilizes a plasma focused ion beam and scanning electron microscope for sample preparation and analysis, was installed at the Grid Storage Launchpad.
A new digital twin platform can help hydropower dam operators by providing accurate and predictive models of physical turbines that improve facilities and enhance reliability.
Research that modeled increased heat pump adoption alongside climate change impacts in Texas showed that high-efficiency heat pumps buffer the strain that electric heating might put on the power grid.
The Sodium-ion Alliance for Grid Energy Storage, led by PNNL, is focused on demonstrating high-performance, low-cost, safe sodium-ion batteries tested for real-world grid applications.
Research identifies the mechanisms through which peptoids affect ions in solution and a mineral surface, increasing the rate of carbonate crystal growth.
A team of researchers at PNNL is developing a new approach to explore the higher-dimensional shape of cyber systems to identify signatures of adversarial attacks.
PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.
Samrat (Sam) Chatterjee, a PNNL chief data scientist and team leader with the Data Sciences and Machine Intelligence group, was co-author of a CSET workshop report on agentic artificial intellilligence