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

Pacific Northwest National Laboratory researchers developed a new theoretical method for studying highly correlated systems.

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.

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.

Catalysts that efficiently transfer hydrogen for storage in organic hydrogen carriers are key for more sustainable generation and use of hydrogen. New research identifies activity descriptors that can accelerate novel catalyst development.

Researchers investigated how stable nanoparticle suspensions form using facet engineering on hematite nanoparticles, demonstrating that controlling the faceting of nanoparticles can effectively maintain particle dispersity.

PNNL is one of the founding partners of the Trillion Parameter Consortium, which was formed to create reliable generative AI models.

Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications.

1-propanol converts from a monomer into a trimer at aluminum sites within zeolite pores.

The first study modeling the mechanism of hydrated electron formation from aqueous iodide.

Researchers unveil user-friendly software to keep complex projects on budget and on schedule.

Studying single crystal reactions provides molecular-level insight into catalytic processes.

PNNL researchers present challenges and opportunities for fusing graph neural networks with deep reinforcement learning.

Highly precise and controllable single-atom catalysts are affected by reaction conditions, which can alter the bonding around the atoms and the activity.

PNNL and University of Texas at El Paso leverage partnership and joint appointment program for a laboratory directed research and development project.

Computational chemistry libraries from NWChem, NWChemEX, SPEC, and more are now available on Azure Quantum Elements.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.