The search for dark matter includes expertise in radio frequency signal detection, quantum sensing, and high-energy physics at PNNL.

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

A team of researchers at PNNL is developing a new approach to explore the higher-dimensional shape of cyber systems to identify signatures of adversarial attacks.

Artificial intelligence, high-throughput experimentation, and materials science expertise combine to efficiently develop next-generation energy storage materials.

Researchers are planning for an electric grid that deploys machine learning to think ahead, plan for the worst, anticipate demand, and meet consumer needs safely and securely.

James Koch, a data scientist, developed a technique that enables high-fidelity remote sensing with limited data.

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.

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.

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

By adding rain, snow, and rain-on-snow precipitation data to a background model, a new scheme pinpoints local flood risks in order to improve the design of small-scale hydrological infrastructure.

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.

Abigail Gutierrez Deniz is a first-generation, Latina student working to pursue her goal of working in cybersecurity.

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.

New college-to-career program provides students a direct pathway to cybersecurity careers at U.S. Space Force's Space Systems Command.

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