Pyrocumulonimbus clouds are increasing in frequency as large wildfires become more prevalent in a warming climate. These clouds can inject smoke particles into the atmosphere, where they can remain suspended for several months.

PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.

This study explored the future effects of climate change and low-carbon energy transition (i.e., emission reduction) on Arctic offshore oil and gas production.

Hydropower could expand substantially during the 21st century in many regions of the world to meet rising or changing energy demands. However, this expansion might harm river ecosystems.

Three PNNL-supported projects are at the forefront of developing advanced data analytics technologies to enhance the U.S. power grid’s reliability, resilience, and affordability.

Using numerical simulations to reproduce the laboratory experiments, this study reveals that liquid droplets are present near the bottom surface, which warms and moistens the air in the chamber.

This work shows that linear pattern scaling is an effective means of obtaining global-to-local relationships for CMIP6 models, as it has been in past model eras.

PNNL researchers will pursue both fundamental and applied projects with this support from the Department of Energy

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.

The first tidal turbine deployed in the Pacific Northwest at PNNL-Sequim showcases the Lab’s growing role as a regional center for marine energy research.

A cross-institutional team of scientists developed PeakQC, a new software tool for automated quality control of mass spectrometry data.

This study examined the role of river sinuosity using computer models to understand what drives hyporheic exchange, a process that significantly affects water quality and ecosystem health.

Increasing the concentration of ions in zeolite micropores leads to a significant increase in the rate of acid catalyzed reactions.

Proton shuffling in hydrated nicotine at low temperatures occurs via a Grotthuss mechanism, identified through experimental and computational work.

Skillful predictions of tropical cyclone activity on subseasonal time scales may help mitigate their destructive impacts. This study investigates the combined impacts of atmospheric phenomena to better understand cyclone activity.

PNNL researchers are exploring the kinds of flicker waveforms that the eye and brain can detect, seeking to understand the different visual and non-visual effects that result.

Hydrogen atoms released and trapped in irradiated gibbsite are destabilized by synthetic-precursor residuals.

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.

Topographic variations have substantial impacts on surface hydrologic processes. This study introduced a new subgrid structure and methods to increase model accuracy for snow water equivalent predictions.