PNNL contributes to a nationwide research consortium investigating the molecular mechanisms triggered by endurance training.

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.

PNNL scientists developed a new method to map exactly how a fungus works with leafcutter ants in a complex microbial community to degrade plant material at the molecular level. The team’s insights are important for biofuels development.

PNNL scientists took thousands of measurements of firefighters in training to learn more about how the body responds to vigorous exercise.

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

PNNL scientists design a highly sensitive neutrino detector for the Deep Underground Neutrino Experiment.

PNNL scientists are creating new ways to learn more about the vast sea of chemicals that haven't been identified—yet.

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.

Physicist Emily Mace will share her science journey and an interactive presentation about her current research with middle school and high school students from across the country at the National Science Bowl.

New research findings published in Science Advances (November 2022), help explain the progression of Alzheimer-related dementia in each patient. The findings outline a biological classification system that predicts disease severity.

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.

A new testbed facility capable of testing superconducting qubit fidelity in a controlled environment free of stray background radiation will benefit quantum information sciences and the development of quantum computing.

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 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.

In adjoining Energy Sciences Center laboratories, researchers develop better energy storage devices by understanding the fundamental reactions that form interfaces.