Uncovered the molecular basis of nitric acid speciation across dilute and concentrated solutions and identified competing hydration-shell rearrangements around lanthanide ions at the dilute limit.

PNNL and its partners are advancing battery energy storage projects nationwide through the Energy Storage for Resiliency Hubs initiative.

A new memorandum of understanding creates a framework for expanded research, talent development, and technology transfer between Georgia Tech and PNNL.

Yong Wang’s joint appointment connects PNNL, WSU, and the next generation of scientists.

Using multiple specialized techniques, IDREAM researchers gained a better understanding of how trace impurities within gibbsite affect the hydrogen yield.

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

PNNL scientists were among the specialists keeping the crowds safe at the recent FIFA World Cup competition.

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

An innovative new approach enables direct measurements of electronic effects at solid–liquid interfaces.

A perspective paper recently published by PNNL researchers underscores how the Lab’s research on electrochemical energy storage is preparing the electric grid to meet the energy needs of the future.

New partnership agreement to focus on AI, robotics, and advanced energy systems.

Chiral nanotubes facilitate the direction-specific diffusion of carbon dioxide to be faster than nitrogen gas.

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

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.

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

Researchers at PNNL have developed an interpretable, lightweight AI model that can easily predict weld microstructure features using only basic machine sensor inputs.

PNNL researchers highlighted advances in AI for scientific discovery at the AI+ Expo, showcasing generative AI, autonomous research workflows, and scalable AI systems supporting energy, security, and national competitiveness.

At a geospatial intelligence conference, senior data scientist Adam Attarian participated in a panel discussing how national laboratories are delivering science, technology, and partnerships to enhance modeling, analysis, and innovation.

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

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.