A novel electrode functionalization strategy enables efficient removal of toxic heavy metals from wastewater.

This study revealed that fresh organic vapors are soluble in particulate organics that are actively growing in size. However, if the particulate matter ages, fresh organic vapors can no longer mix with the organic matter.

Partitioning measured ice nucleating particle concentrations into individual particle types leads to a better understanding of the sources and model representations of these particles.

A poem inspired by radioactive tank waste—“Can a Scientist Dream it Alone?”—was awarded first place in the Department of Energy’s Poetry of Science Art Contest.

PNNL is honoring its postdoctoral researchers as part of the fourteenth annual National Postdoc Appreciation Week with seven profiles of postdocs from around the Laboratory.

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.

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.

A new review describes the insights that may be gained into important electrochemical processes using ion soft landing.

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

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

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.

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

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

How a model treats gas transfer behavior onto dust and sea salt particles significantly influences nitrate aerosols and their effects on climate.

Combining peptoids and carbon nanotube porins creates a new class of stable membranes with potential applications in separations science.

When wildfires burn in the west, the heat and airborne particles they release inflict stronger rain and larger hail upon central states.

Secondary organic aerosol formation from monoterpenes is more strongly influenced by oxidant and monoterpene structure than by nitric oxides and hydroperoxy radical concentrations.