PNNL researchers Daniel Deng and Yehia Ibrahim join the 2025 class of National Academy of Inventors Fellows.

The Scientific Discovery through Advanced Computing institute will focus on making scientific machine learning accessible to domain scientists.

A low-temperature, single-stage catalytic process converts PVC and polyolefin into valuable alkanes.

A comprehensive investigation provides quantitative data on the interaction between zeolite pores and linear alcohols, with hydroxyl group interactions playing the largest role.

This achievement earned DIMPLES a Best Paper award at the ACM International Conference on Supercomputing 2025.

ThermalTracker-3D can help streamline permitting, reduce costs, and shorten development time of energy projects.

After isolating copper hydride monomers, researchers identified the mechanistic details of catalyst aggregation and cluster formation.

The low-temperature breakdown of polyolefins is driven by carbenium ions generated from chloroaluminate ionic liquids.

PNNL chemical engineer Mariefel Olarte shares passion for mentoring students and the next-generation workforce.

Tuning the environment of supported palladium atoms with hydrogen treatment enhances their catalytic activity.

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.

Increasing the concentration of ions in zeolite micropores leads to a significant increase in the rate of acid catalyzed reactions.

In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.

Electronic modifications from hydrogen spillover onto the oxide support increase the activity of single-atom rhodium catalysts.

With the launch of a large research barge, PNNL and collaborators took another significant step to improve offshore wind forecasting that will lower risk and cost associated with offshore wind energy development.

ChemReasoner combines decades of chemistry knowledge with large language models to propose strategies for effective new catalysts.

A new approach validates quantum algorithms for low-energy nuclear physics applications

PNNL played host in mid-May to the Artificial Intelligence for Robust Engineering & Science workshop, an annual event that explores advances in artificial intelligence

PNNL shared recent developments in artificial intelligence at the inaugural Special Competitive Studies Project AI for National Competitiveness Expo.

The software democratizes hardware designs by enabling domain scientists to design their own accelerators.