Chemist Wendy Shaw, a nationally recognized scientific leader, has been chosen to serve as the associate laboratory director for PNNL's Physical and Computational Sciences Directorate.

Researchers can now quantify uncertainty in trained AI models aimed at solving difficult chemistry, biology and materials science problems.

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

Researchers discovered a new way to more efficiently and affordably create nickel-rich battery materials.

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

A new analysis shows how renewable energy sources like solar, wind and hydropower respond to climate patterns, and how utilities can use this data to save money and invest in energy storage.

Federal environmental permitting process to be fast-tracked with AI-powered tools and cloud-supported data analysis.

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

New transmission lines and renewable energy projects would bring economic and climate change benefits to the Western United States’s electricity grid.

Three PNNL technologies have been named 2024 R&D 100 Award winners.

The Grid Storage Launchpad will enable researchers to accelerate and validate new battery materials and systems.

Ji-Guang (Jason) Zhang has been named the first Department of Energy Lab Innovator of the Year.

A new iron-based aqueous flow battery shows promise for grid energy storage applications.

PNNL scientists have put forth a new approach to protect the electric grid, creating an approach that sorts and prioritizes cyber threats on the fly.

ChatGrid™ is a practical application of the Department of Energy’s exascale computing efforts and offers a new experience in easy, intuitive, and interactive data interaction.

Results of the PR100 study outline near- and short-term strategies for Puerto Rico to achieve a renewable power grid by 2050.

The convergence of artificial intelligence, cloud, and high-performance computing to accelerate scientific discovery is the focus of a multi-year collaboration between Microsoft and PNNL.

PNNL has created the Center for AI @PNNL to coordinate the pioneering research of hundreds of scientists working on a range of projects in artificial intelligence.

Understanding the risk of compound energy droughts—times when the sun doesn’t shine and the wind doesn’t blow—will help grid planners understand where energy storage is needed most.

Input from humans helps when deciding whether to trust the recommendations or decisions of a machine-learning system.