A suite of experiments provide insight into how diopside reacts with carbon dioxide to form stable carbonate species.

Researchers from Pacific Northwest National Laboratory created and embedded a physics-informed deep neural network that can learn as it processes data.

Different sources of low-level moisture perturbation can result in differences in the timing and location of a large, modeled storm.

PNNL-Sequim scientists will spend the next year testing a new technology that could allow the ocean to soak up more carbon dioxide without contributing to ocean acidification.

Randomly constructed neural networks can learn how to represent light interacting with atmospheric aerosols accurately at a low computational cost and improve climate modeling capabilities.

PNNL welcomes six Department of Energy Office of Science Graduate Student Research awardees from across the nation.

This PNNL project was the focus of Nune’s talk when he delivered the keynote for the Carbon Capture and Utilization track at the 2nd Annual Baker Hughes Energy Frontiers Summit.

PNNL researchers led a collaborative effort to showcase the most up-to-date, innovative, commercial cement and concrete technologies.

Across the United States, organic carbon concentration imposes a primary control on river sediment respiration, with additional influences from organic matter chemistry.

The complex interactions between the land and atmosphere can affect cloud growth.

By mimicking nature, scientists make a breakthrough in breaking down wood.

Metabolomics analysis revealed differences in metabolome profiles for two distinct modes of fungal wood decay.

Assessing observed weather conditions that support or suppress the growth of clouds into deep precipitating storms during the Cloud, Aerosol, and Complex Terrain Interactions experiment.

Multiple concurrent single-particle measurements help develop a quantitative and predictive understanding of secondary organic aerosols.

Applying a novel framework to a climate model reveals new characteristics about how elevated concentrations of aerosols affect clouds.

As the world races to discover solutions for reaching net zero carbon emissions, a PNNL analysis quantifies the economic value of the existing nuclear power fleet and its carbon-free energy contributions.

A deep learning model overcomes persistent challenges in emulating long-term simulations of secondary organic aerosols.

Under Secretary for Science and Innovation at the Department of Energy Geri Richmond visited PNNL.

From energy-efficient buildings to new manufacturing techniques, researchers at PNNL strive for sustainability and a decarbonization.

Performing closure studies using aerosol size, aerosol composition, and cloud condensation nuclei measurements of mixed aerosol from the Southern Great Plains region.