Pacific Northwest National Laboratory scientists discussed their materials research at Accelerate’24.

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

Joint Appointee Mitra Taheri spoke on the AI in Government episode of the EY Leading into Tomorrow podcast.

Sergei Kalinin honored with the David Adler Lectureship Award for contributions to materials physics through automated experimentation and ferroelectric materials work.

PNNL researchers will pursue both fundamental and applied projects with this support from the Department of Energy

A switchable single-atom catalyst is activated in the presence of surface intermediates and reverts to its stable inactive form when the reaction is completed.

Two PNNL materials scientists were involved in co-editing an issue of MRS Advances focused on crystallization and assembly at interfaces.

Artificial intelligence, high-throughput experimentation, and materials science expertise combine to efficiently develop next-generation energy storage materials.

Ultra-thin layers of silk deposited on graphene in perfect alignment represent a key advance for the control needed in microelectronics and advanced neural network development.

Geochemist Kevin Rosso named an American Geophysical Union fellow in recognition of his work leading the field of molecular geochemistry.

Hydrogen atoms released and trapped in irradiated gibbsite are destabilized by synthetic-precursor residuals.

Vijay Murugesan highlights how AI can accelerate materials discovery at the Volta Foundation’s Battery Forum.

Combining cold spray deposition and friction stir processing for a more efficient route to oxide dispersion strengthened steel.

A launch from Cape Canaveral early today carried a PNNL experiment to space so scientists can learn more about radiation far above Earth.

PNNL researchers earned five Papers of Note, 17 Superior Papers, and one poster award for their environmental remediation, radioactive waste, and nuclear energy-related presentations.

An atomic sieving effect selectively promotes diffusion of some species, leading to different oxidation rates at surface facets.

Bylaska and team will aim to make computational design of functional materials more targeted, impactful, and user friendly through this award.

New funding spurs a new approach to researching the effective retrieval and processing of legacy radioactive waste. Four-year focus of the IDREAM EFRC will link attosecond timescales to decades-long chemical processes.

Long-duration energy storage gets the spotlight in a new Energy Storage Research Alliance featuring PNNL innovations, like a molecular digital twin and advanced instrumentation.

Three PNNL technologies have been named 2024 R&D 100 Award winners.