Graduate student researcher wins best poster awards from the American Ceramic Society.

PNNL and Maritime Blue, a Washington state-based strategic alliance promoting maritime business in the Pacific Northwest, have released a report highlighting challenges—and solutions—for reinvigorating shipbuilding in the region.

Working with DOE and PNNL, Google has created a new badge that will help consumers find highly skilled home energy specialists.

PNNL researchers will deploy advanced AI systems to study how to best secure the future electric grid.

High-Velocity Joining is a new joining technology that could reduce energy use and cost for manufacturers.

A newly published custom collection of glass formulas for nuclear waste vitrification — developed and validated by PNNL over the past three years — was made possible in that timeframe with AI tools, including a PNNL machine learning model.

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.

PNNL has chosen three proven leaders to serve in key roles guiding lab research and operations.

Stakeholders convened at PNNL to build a shared understanding of energy storage siting, permitting, safety, and local engagement.

PNNL chemist Sarah Saslow received the ACS Rising Star Award for her research supporting environmental cleanup, including work on legacy waste and subsurface contamination.

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.

Custom AI research assistant allows users to ask questions and get answers from hundreds of wildfire mitigation plans.

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

PNNL's Building Energy Model AI is an open-source bot that can help energy modelers save time and money.

Explore the past, present, and future of technological advancements made by scientists at PNNL.

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

An AI program called AtomAI helped PNNL researchers reveal key design principles for protein interfaces with mineral surfaces.

Autonomous science laboratories are taking shape quickly across the PNNL campus.