A study by researchers at PNNL assessed the feasibility of using strontium isotope ratios and an existing machine learning–based model to predict and verify a product’s source—in this case, honey.

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

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

Neural networks techniques enable the efficient capture of electron correlation effects in reduced-dimensionality spaces.

In the search for rare physics events, extremely pure materials are essential. A partnership between PNNL and Ultramet has led to tungsten with low contamination from other elements.

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

Developing a new scheme to more efficiently solve quantum chemistry problems.

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.

Nineteen PNNL-affiliated researchers have been named to Clarivate’s 2024 list of the world's most highly cited researchers.

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.

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

In the latest issue of the Domestic Preparedness Journal, Ashley Bradley and Kristin Omberg share how new research is shedding light on the scientific and technological challenges with detecting fentanyl.

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

Research at PNNL and the University of Texas at El Paso are addressing computational challenges of thinking beyond the list and developing bioagent-agnostic signatures to assess threats.

A new quantum algorithm speeds up simulations of coupled oscillator dynamics.