Senior Advisor Isabella van Rooyen shares her journey from child to internationally recognized scientist in nuclear materials and manufacturing.

Scientists have learned more about how to protect the insulin-producing cells that die in patients with Type 1 diabetes.

Reproducible workflows for binning and visualizing nuclear magnetic resonance spectra from environmental samples.

Samantha Erwin, a PNNL data scientist, was recently appointed to the Society for Industrial and Applied Mathematics Membership Committee.

PNNL researchers use chemometric analysis to model chemistry in molten salt.

In soil, microbes produce and consume methane. Using a technique called pool dilution, researchers can separate the rate of methane production and consumption from the net rate.

Scientists stop the motion of atoms to watch electrons move in liquid water.

PNNL researchers helped identify a fragment from the SARS-CoV-2 virus that spurs severe illness.

Differences in water interactions lead to two gibbsite dissolution pathways modulated by solution acidity.

Pacific Northwest may face increase in summer heat-dome-like stationary waves.

Scientists have learned more about how drug resistance develops in patients with acute myeloid leukemia and how the process might be slowed.

PNNL scientists developed a new method to map exactly how a fungus works with leafcutter ants in a complex microbial community to degrade plant material at the molecular level. The team’s insights are important for biofuels development.

Pacific Northwest National Laboratory launches the Training Outreach and Recruitment for Cybersecurity Hydropower program at the University of Texas at El Paso.

PNNL’s Climate Network with MSIs and HBCUs aims to bring opportunities to diverse populations.

Identifying how curvature affects the doping and hydrogen binding energies of carbon-based materials provides a framework for designing hydrogen storage materials.

Visual Sample Plan, a free software tool developed at PNNL that boosts statistics-based planning, has been recognized with a 2024 Federal Laboratory Consortium Award.

Combining X-ray-based techniques allows researchers to locate and characterize small concentrations of electrons in complex semiconductor films.

A simple gel-based system separates metals ions from a model solution of dissolved battery electrodes without the need for specialty chemicals, membranes, or toxic solvents.

Machine learning methods and data science can uncover hidden patterns in nanoparticle synthesis conditions and property outcomes.

Proposing a new synthetic route to layered materials that demonstrate efficient photocatalysis.