Now, anyone can easily explore and access data from a nationwide map of data centers, the infrastructure that powers them, and projections of future data center locations.

For nearly 20 years, PNNL has invested in a multidisciplinary effort to develop better batteries.

In a recent study, PNNL researchers found that noncrystalline mineral surfaces can bind microbial residues to build soil organic matter.

PNNL researchers are opening up a new front in the fight to stop viral pathogens, protecting people against multiple viruses.

Distributed science is thriving at PNNL, where scientists share data and collaborate with researchers around the world to increase the impact of the work.

From developing new energy storage materials to revealing patterns of Earth’s complex systems, studies led by PNNL researchers are recognized for their innovation and influence.

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.

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

Dušan Veličković, a PNNL mass spectrometry imaging scientist received a $2.1 million grant to develop techniques to understand how changes in carbohydrate structure affect human health.

Large clusters of organized thunderstorms, called mesoscale convective systems, account for half of summer rainfall in the central and eastern U.S. Their formation can be influenced by weather patterns in the mid-levels of the troposphere.

Atmospheric aerosol particles modulate climate and the Earth’s energy balance by scattering and absorbing sunlight. They also seed clouds, acting as cloud condensation nuclei.

High-resolution hydrodynamic-sediment modeling shows that inundation, suspended sediment concentration in the Amazon River, and floodplain hydrodynamics drive sediment deposition in Amazonian floodplains.

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.

This study used historical data, remote sensing, and aquatic sensors to measure how far wildfire impacts propagated through the watershed after the 2022 Hermit’s Peak/Calf Canyon fire, New Mexico’s largest wildfire in history.

The prediction of rainfall over the Amazon rainforest by weather and climate models is highly uncertain, particularly for large rainstorms which are commonly seen during the wet season, from March to May.

Extensive in situ and remote sensing measurements were collected to address data gaps and better understand the interactions of convective clouds and the surrounding environment.

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

PNNL scientist James Stegen and an international team of collaborators recently published a comprehensive review of variably inundated ecosystems (VIEs).

PNNL has created and licensed a system that sniffs out trace levels of fentanyl, other drugs and explosives through the air.