PNNL offers a third-party testing environment to provide battery companies with independent data about their grid-scale systems.

For nearly 20 years, PNNL has invested in a multidisciplinary effort to develop better batteries.

The Scientific Discovery through Advanced Computing institute will focus on making scientific machine learning accessible to domain scientists.

GSL's utility-grade battery testing operation is now fully operational.

The Genesis Mission will mobilize the Department of Energy’s 17 National Laboratories, industry, and academia to build an integrated discovery platform.

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

As Laboratory Director Steve Ashby pens his last monthly column, he highlights PNNL’s accomplishments with pride and gratitude.

Micron and PNNL co-design the Crete computer system, delivering a new memory architecture for data-intensive scientific computing and AI applications.

Big energy storage science is brewing at GSL just one year after its groundbreaking.

Matt Fayette, a materials scientist, is testing a new method to extend battery life for grid storage by circulating the electrolyte.

di Vacri’s expertise in low-background detection earned her a place on the Executive Board of the Coordinating Panel for Advanced Detectors.

In the search for rare physics events, extremely pure materials are essential. A partnership between PNNL and Ultramet has led to tungsten with low contamination from other elements.

Researchers have created an algorithm that slashes the calculations necessary to prepare and customize data for quantum computing.

Mini flow cell battery provides the first step toward an AI-driven, robotic energy storage discovery laboratory.

A new generation of microelectronics research begins at PNNL.

Calculating quantum chemistry quickly allows scientists to refine their understanding of complex chemical systems.

The speed and agility of cloud computing opens doors to completing advanced computational chemistry workflows in days instead of months.

Researchers discussed this topic at the 2024 Analog Computing for Science Workshop co-led by Antonino Tumeo.

In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.

The Department of Energy’s Vehicle Technologies Office recognized Livewire’s outstanding teamwork and technical expertise.