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

This research helps predict how coastal forests will respond to future sea level changes which is crucial for protecting these ecosystems.

The Coastal Observations, Mechanisms, and Predictions Across Systems and Scales: Field, Measurements, and Experiments project established a network of observational field sites across Chesapeake Bay and western Lake Erie.

Due to their inherent variability and complexity over space and time, scientists are challenged to understand the complex interactions among soil, vegetation, and water along coastal terrestrial-aquatic interfaces.

This study characterized above- and below-ground properties to explore the spatial heterogeneity of the terrestrial aquatic interface ecosystem within the Chesapeake Bay area and evaluate the major drivers of soil respiration.

Neural networks techniques enable the efficient capture of electron correlation effects in reduced-dimensionality spaces.

In the search for rare physics events, extremely pure materials are essential. A partnership between PNNL and Ultramet has led to tungsten with low contamination from other elements.

Developing a new scheme to more efficiently solve quantum chemistry problems.

PNNL's accomplishments in FY 2024 help address the remaining challenges the wind industry faces.

Pacific Northwest National Laboratory researchers developed a new theoretical method for studying highly correlated systems.

Nineteen PNNL-affiliated researchers have been named to Clarivate’s 2024 list of the world's most highly cited researchers.

This study evaluated the sensitivity of multiple geophysical methods to measure and evaluate the spatiotemporal variability of select soil properties across terrestrial–aquatic interfaces.

Researchers integrated field measurements, lab experiments, and model simulations to study oxygen consumption dynamics in soils along a coastal gradient.

This research explores how changes in groundwater levels affect the chemistry of underground water, especially in areas where land meets water, like wetlands.

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.

The 2024 State of the Science Report on environmental effects of marine renewable energy research has been released.

The Delaware River Basin is projected to experience a regional increase in flood severity under future climate scenarios.

A new approach validates quantum algorithms for low-energy nuclear physics applications

Study explores Exploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments, a consortium of scientists interested in the exchange between water and land in coastal systems.

A new quantum algorithm speeds up simulations of coupled oscillator dynamics.