Beyond melting ice and higher temperatures: On Earth Day, scientists consider how climate change will affect national security.

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?

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 researchers explore the feasibility of using low-flying drones to survey sites for low levels of radiation.

PNNL researchers created rugged, adaptable, mass-manufacturable luminescent particle tracers for use in harsh environments.

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

Scientists at PNNL are working to better prepare authorities, emergency responders, communities and the grid in the face of increasingly extreme hurricanes.

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.

Lighting control data are critical for optimizing the design and operation of future lighting systems for the benefit of occupants and energy efficiency.

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

DOE Integrated Lighting Campaign organizers introduce new recognition categories in horticulture, innovative financing, and energy equity.

A new PNNL study quantifies hydropower's contribution to grid stability. When other power sources go out, hydropower can ramp up, recoup shortfalls, and stabilize the grid nearly instantaneously.