A decade-long evolution in making omics data easier to analyze earns widespread recognition.

Researchers showed that spiking neural networks can be accurate for regression problems, opening opportunities for efficient neuromorphic computing.

Tracking water age using a new precipitation tagging method within a hydrologic model generates key information to support hydropower energy and other water-dependent systems.

​​Tests show which low-cost 3D method best matches field measurements to minimize errors in mapping headwaters.​

More rain and less snow shorten how long water stays in watersheds.

Longtime PNNL researcher resumes leadership role, continuing AGI’s partnership between PNNL and WSU.

Genesis Mission awards to PNNL will advance scientific discovery, next-generation energy systems and advanced manufacturing, among others.

PNNL mathematician and AI researcher Henry Kvinge bridges math and AI, finding connections between the two fields and studying ways where they can foster mutual progress.

Computer scientist Antonino Tumeo is guest editing a special issue of IEEE’s Computer publication focused on democratizing microelectronics.

Novel Applications for Synchronized Power Instrumentation seeks to improve electric grid resilience, reliability, security, and affordability.

A research team from Pacific Northwest National Laboratory used machine reasoning to schedule scientific workflows while guaranteeing quality of service (QoS).

Critical minerals could be sourced from industrial waste at scale thanks to an AI-guided separation workflow developed by researchers at PNNL.

PNNL’s Robert Rallo and Nathan Hodas speak to students about the future of AI.

At the summit, PNNL engaged with partners and investors, highlighting seven projects that accelerate the deployment of new energy technologies.

An international research team deployed AI-powered computing to solve important chemical structures for energy applications using NVIDIA hardware.

David Wunschel, a chemist and Laboratory Fellow, participated on a panel focused on how emerging technologies are transforming CBRN defense, detection, and response across military and government operations.

Automated liquid handling, combined with data analysis and AI, optimizes microbiological growth conditions at PNNL.

PNNL set to create a practical path for near-term hybrid classical-quantum computers with NVIDIA accelerated computing.

From exploring the development of transformative materials to strengthening biotechnology, six up-and-coming PNNL scientists were recognized for their scientific vision and prowess.

Emilie Purvine, a chief data scientist at PNNL, was elected as a council member at large of the American Mathematical Society.