A breakthrough in electron microscopy based on deep learning can automatically visualize and identify areas of interest, helping to speed advances in 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.

Scientists are studying tiny subatomic particles that pass through humans and possess clues about the origins of the universe.

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.

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.

As the world races to discover solutions for reaching net zero carbon emissions, a PNNL analysis quantifies the economic value of the existing nuclear power fleet and its carbon-free energy contributions.

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.

Artificial intelligence may help humans and computers work together to monitor materials that could be used to make weapons.

Exploring why some brains are more resilient to the impact of Alzheimer’s disease could lead to improved diagnoses, treatment and prevention.

Tungsten heavy alloys show promise for nuclear fusion energy development, according to new research conducted at PNNL.

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.

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

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

Two PNNL interns are behind recent innovation in real-time testing and continuous monitoring for pH and the concentration of chemicals of interest in chemical solutions; outcomes have applicability not only to nuclear, but to industries.

PNNL data scientists are refining their artificial intelligence tools with COVID-19 data to advance therapeutics and treatments for a future pandemic.

PNNL commemorates 9/11 and reflects on the 20 years of science and technology produced since to protect against threats and make America safer.

PNNL report reflects 10 years of dedication to effectively plan for the safe and uneventful removal of radioactive waste from nuclear power plants.