Research provided definitive spectroscopic characterization, reactivity, and deactivation of a reactive monomeric diphosphine-copper hydride intermediate.

Developed a method for selectively anchoring diverse divalent metal cations in zeolites, important for precise control over catalytic materials.

Developed a simple kinetic framework for evaluating catalyst hydride transfer ability.

PNNL has formed a partnership with the Orlando-based firm Refinity, which has licensed a key process from PNNL that will help the company convert mixed plastic waste into valuable industrial products like chemicals, plastics, and fuels.

Researchers at PNNL have developed an interpretable, lightweight AI model that can easily predict weld microstructure features using only basic machine sensor inputs.

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.

Researchers at PNNL are asking: how compatible, exactly, is hydrogen fuel with the existing natural gas pipeline network?

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

PDX, PNNL, and Sandia National Laboratories are exploring the feasibility of hydrogen fuel for the PDX bus fleet—an idea that could have novel benefits for hazard resilience.

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.

Klickitat Valley Health's fuel cell and microgrid project boosts rural healthcare, enhancing energy resilience and sustainability for social equity.

After 20 years of contributions to the field of hydrogen safety, the Hydrogen Safety Panel launched its new mentoring program at PNNL earlier this year. Now, the program has selected its first two mentees.

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

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

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.

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

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