The ability of a storm-resolving weather model to predict the growth of storms over central Argentina was evaluated with data from the Clouds, Aerosols, and Complex Terrain Interactions (CACTI) field campaign in central Argentina.

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

Researchers have developed the first coastal transport model for microplastics to understand how particles move in waterways and coastal currents.

Researchers from PNNL and Parallel Works, Inc., applied machine learning methods to predict how much oxygen and nutrients are used by microorganisms in river sediments.

Christina Lomasney moderates panel on commercialization pathways for emerging artificial intelligence and high-performance computing technologies.

Lakes are important sentinels of climate change and contribute significantly to the emissions of the second most important greenhouse gas—methane.

The rate of conversion of cloud droplets to precipitation, known as the autoconversion rate, remains a major source of uncertainty in characterizing aerosol’s cloud lifetime effects and precipitation in global and regional models.

To assess the impact of observation period and gauge location, model parameters were learned on scenarios using different chunks of streamflow observations.

This study presents an automated method to detect and classify open- and closed-cell mesoscale cellular convection (MCC) using long-term ground-based radar observations.

The Center for Continuum Computing at PNNL aims to integrate cloud platforms, high-performance computing, and edge devices into a seamless ecosystem that accelerates scientific discovery.

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.

PNNL’s Center for Cloud Computing is addressing challenges in data management and hybrid cloud solutions with industry and academic partnerships.

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.

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.