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.

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.

Connecting energy generation, electricity storage, and using sensors and control software to track load, including precommercial market marine energy generation technologies.

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.

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.

AI for Good event commemorates 60 years of community engagement, features AI applications, and offers practical AI tools to empower people.

A closed-loop workflow brings together digital and physical frameworks to advance high-throughput experimentation on redox-active molecules in flow batteries.

PNNL researchers developed a new computational workflow to study day-to-night gene expression dynamics of cyanobacterium in real time.

This achievement earned DIMPLES a Best Paper award at the ACM International Conference on Supercomputing 2025.

A new approach combining computational processes enables the more accurate simulation of nuclear quantum effects in molecular systems.

Researchers at PNNL are asking: how compatible, exactly, is hydrogen fuel with the existing natural gas pipeline network?

ThermalTracker-3D can help streamline permitting, reduce costs, and shorten development time of energy projects.

Researchers at PNNL shared advances in artificial intelligence, cybersecurity, advanced imaging, and more at the Department of Homeland Security Research, Development, Test, and Evaluation Summit.