Global exercise advances nuclear forensic science and investigative capabilities.

Artificial intelligence helps analyze images and reduce uncertainty for a key measure of watershed function.

Dynamic organic matter traits tied to reactions can surpass static descriptors in explaining decomposition rates and responses to environmental change.

Using an AI approach to combine outputs from microbial models and apply them as inputs to reactive-transport models reduces computational time by several orders of magnitude.

Amine functionalized graphene oxide yields laminates with an enhanced capacity to adsorb rare earth elements, improved water transport, and greater stability for effective membrane-based separation of critical minerals.

Five PNNL innovations earned 2026 R&D 100 Awards for advances in biotechnology, manufacturing, critical minerals, and nuclear security.

A new report highlights a public workshop hosted by the National Academies Forum on Microbial Threats and features PNNL's Lauren Charles and the AI-Driven One Health Security program.

Integrating new functions into a genome-scale model enabled researchers to simulate and experimentally validate viral hijacking pathways.

PNNL has developed a next-generation electrical resistivity tomography system for DOE that uses E4D software and AI-enhanced modeling to produce real-time subsurface images that help guide environmental remediation decisions.

Replacing commercial acid with acidic waste enables researchers to improve nickel extraction efficiency, lower projected costs, and improve process economics.

RemPlex 2025 Global Summit on Environmental Remediation attendees share knowledge about cleanup and monitoring of complex sites worldwide; more than 100 presentations are posted online.

Localized gradients in magnetic fields have long-range effects on the concentration of rare earth ions in solution, facilitating field-driven extraction of critical minerals.

Studying a series of rare earth element compounds revealed differences in their magnetic behavior that will be leveraged for separations.

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.

Soil mineral preferentially incorporates rare earth elements based on size, with implications for critical mineral extraction.

The first direct molecular-scale evidence of the temperature-driven transformation of the coordination environment of ytterbium at geologically relevant conditions.

RemPlex and IAEA convene international leaders to tackle recruitment and retention in complex environmental cleanup efforts.

A new database allows researchers to connect lattice parameters and composition in olivine.

New methodology can evaluate the potential for carbon storage and critical mineral recovery in undercharacterized geological settings.

Data from SOSAT web tool informs site selection and management for the subsurface injection of captured carbon dioxide.