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

A study by researchers at PNNL assessed the feasibility of using strontium isotope ratios and an existing machine learning–based model to predict and verify a product’s source—in this case, honey.

Nanoscale domains of magnetically susceptible critical materials encounter enhanced magnetic interactions under external magnetic fields, providing a promising new avenue for separations.

David Heldebrant was selected for the 2025 Distinguished Service Award from the American Chemical Society Division of Energy & Fuels, recognizing his impact to energy and fuels chemistry.

The size of graphene oxide sheets affects the ability of assembled membranes and adsorbents to separate rare earth elements.

Scientists have tapped AI and powerful computing to speed up how quickly officials are able to learn important details about nuclear events.

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

Brown University professor and PNNL joint appointee was honored for his exceptional work in applied mathematics.

PNNL researchers have published their paper, “Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data,” in the Journal of Proteome Research.

The Center for Continuum Computing at PNNL aims to integrate cloud platforms, high-performance computing, and edge devices into a seamless ecosystem that accelerates scientific discovery.

A PNNL team has developed an energy- and chemical-efficient method of separating valuable critical minerals from dissolved solutions of rare earth element magnets.

Lauren Charles, a chief data scientist at PNNL, showcased the vital research coming out of her program at The National Academies Forum workshop in Washington, D.C., January 15–16, 2025.

Surface manganese mining from nodules in South Dakota is now possible with a new scalable selective precipitation process.

Formal mathematics both reveals what’s inside the black box of AI algorithms and pushes the boundary of what’s possible within math as a discipline.

Cobalt substitution for magnesium in a model mafic mineral dramatically slows reaction with carbon dioxide to form a cobalt-doped carbonate.

PNNL’s year in review includes highlights ranging from advancing soil science to understanding Earth systems, expanding electricity transmission, detecting fentanyl, and applying artificial intelligence to aid scientific discovery.

Precipitation with sodium hydroxide in a flow-gel device enables the rapid extraction of magnesium from seawater in a new scalable process.

Federal environmental permitting process to be fast-tracked with AI-powered tools and cloud-supported data analysis.

Scientists are developing ways to detect previously unseen forms of fentanyl as well as other synthetic opioids known as nitazenes.

Calculating quantum chemistry quickly allows scientists to refine their understanding of complex chemical systems.