PNNL researchers demonstrate high-purity production of two essential gases to ensure a U.S. domestic feedstock for advanced quantum computing.

PNNL has named atmospheric scientist Larry Berg director of the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) User Facility, where he will oversee a global network of atmospheric research observations.

Coding agents repurposed to draft complex environmental impact statement sections through PermitAI public-private partnership model.

AutoLabs is a new agentic AI system that translates experimental goals into robot-specific language.

PNNL will build an AI-powered modeling platform to help geothermal energy operators maximize electricity generation.

The comprehensive guide can help companies build AI data centers that keep energy costs low and maintain grid stability.

Mechanical engineer Scott Whalen is named the Department of Energy’s Innovator of the Year for turning the patented metal extrusion invention ShAPE™ into an industrially relevant extruded metal product juggernaut.

Battery researchers are ready to work with private companies who want to test their own chemistries in a prismatic cell format.

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

PNNL helps strengthen domestic supply of critical mineral needed for new cutting-edge cancer therapy.

PNNL has named Douglas Mans and Daniel Stephens as associate laboratory directors to lead science and national security strategies.

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.

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

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.

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.

PNNL cyber defenders are using the Laboratory’s own artificial intelligence research to recognize and address threats quickly.

Margaret Cheung elected to premier scientific society.