A suite of new modeling methods gives researchers better tools to predict molecular behavior inside cavities.

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.

A microbial community expresses a phenotype of interest ~20 percent higher than the sum of each member species.

PNNL celebrates its sixth Handshake Early Talent Award, showcasing strong early‑career recruiting. Stories from data scientist Joshua Chong and engineer Alex Smith highlight journeys from different career paths to PNNL.

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.

Structural proteomics reveal how cyanobacteria adapt to changing light.

Secretary Wright visited PNNL's campus in Richland, Washington, late last year to meet with innovators in chemistry, biology, computing, and more.

Darío Gil, DOE's Undersecretary for Science, makes his inaugural visit to PNNL.

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.

Researchers use multiomics to confirm role of lipid synthesis during infection, leading to model of how to restrict virus replication.

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.

Nanosize platelets of an aluminum material slide and join in a staggered orientation to form larger crystals.

PNNL researchers Daniel Deng and Yehia Ibrahim join the 2025 class of National Academy of Inventors Fellows.

Anthony Pugliese, director of the Department of Energy Office of Technology Commercialization, makes inaugural visit to PNNL.

The Scientific Discovery through Advanced Computing institute will focus on making scientific machine learning accessible to domain scientists.

Researchers at PNNL share a research- and practitioner-informed approach to assess the threat landscape, elicit and integrate feedback into solutions, and ultimately share outcomes with the emergency response and public safety community.

An approach combining multiple theories increases the accuracy of quantum-based simulations without increasing computational demands.

IDREAM researchers uncovered how dimeric complexes control how aluminum hydroxide minerals dissolve.

Hydrogen preferentially inserts at grain boundaries between interconnected chains of palladium nanoparticles, which have a lower energy barrier for hydrogen incorporation into the material.

Scientists provide a guide for the rational application of continuum descriptions of fluid flows based on interfacial chemistry.