As new paradigms in advanced computing take shape, computational chemistry researchers are finding new ways to solve challenging chemistry problems.

A new AI model developed at PNNL can identify patterns in electron microscope images of materials without requiring human intervention, allowing for more accurate and consistent materials science.

In 2006, battery research was practically non-existent at PNNL. Today, the lab is lauded for its battery research. How did PNNL go from a new player to a leader in state-of-the-art storage for EVs and the grid?

Battery energy storage systems are being proposed in municipalities across the U.S. PNNL researchers can help community planners guide safe siting and operations.

The use of disciplines in pure mathematics can increase the reliability and explainability of machine learning models that “transcend human intuition,” according to PNNL scientists.

PNNL’s Grid Storage Launchpad delivers tomorrow’s energy storage solutions today.

The Rapid Assessment of Platform Technologies to Expedite Response project aims to prepare against future pandemics.

To overcome high-performance computing bottlenecks, a research team at PNNL proposed using graph theory, a mathematical field that explores relationships and connections between a number, or cluster, of points in a space.

PNNL battery researcher Jie Xiao collaborates with academic and industry partners to address scientific challenges in manufacturing lithium-based batteries.

PNNL researchers use machine learning and data analytics to assist with detection of nuclear proliferation and nuclear material trafficking.

Scientists are pioneering approaches in the branch of artificial intelligence known as machine learning to design and train computer software programs that guide the development of new manufacturing processes.

In honor of National Intern Day, PNNL and intern Jonathan Mills were named among the Top 100 in the nation by early-career recruiting firm WayUp.

As wildfires grow increasingly severe, PNNL researchers are working to slow their spread and mitigate their harmful effects.

TransMED analyzes patient data from similar diseases across multiple sources to understand COVID-19 patient outcome risk factors.

PNNL researchers developed a new model to help power system operators and planners better evaluate how grid-forming, inverter-based resources could affect the system stability.

Top scientists and officials from government, academia, Alaskan Native communities, and industry are heading to Alaska to focus on driving energy technologies for a more sustainable Arctic region.

PNNL experts perform fundamental climate science work at multiple scales to understand impacts on energy, water, food, and infrastructure systems.

Focused research studies of advanced algorithms and materials are setting the stage for the next generation of quantum computers.

PNNL scientists partnered with colleagues at the University of Akron to create a new molecule that could substantially improve the electrochemical stability of redox flow batteries.

The Energy Storage for Social Equity Initiative will help up to 15 disadvantaged communities consider energy storage technologies to meet local energy goals.