The next-generation ShAPE machine has arrived at PNNL, where it will help prove the mettle of the ShAPE extrusion technique. ShAPE 2 is designed to allow researchers to produce larger, more complex extrusions.

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 officials travel to Cyprus as subject matter experts and trainers for U.S. State Department Export Control and Border Security Program.

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 PNNL research makes it easier to differentiate between chemical and nuclear explosions.

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.

A new extrusion process eliminates pre-heating to provide significant energy savings during production of extruded aluminum alloys.

The first-ever simulation of aluminum conductivity offers a recipe for an inexpensive, lightweight alternative to copper.

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.

Developed at PNNL, Shear Assisted Processing and Extrusion, or ShAPE™, uses significantly less energy and can deliver components like wire, tubes and bars 10 times faster than conventional extrusion, with no sacrifice in quality.

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.

PNNL combines AI and cloud computing with damage assessment tool to predict path of wildfires and quickly evaluate the impact of natural disasters, giving first responders an upper hand.

At PNNL, women in engineering tackle some of the world’s most complex problems in environmental science, sustainable energy, and national security.

PNNL provided ultra-low measurements of argon-39 to date groundwater as part of a collaborative study of the aquifer in California’s San Joaquin Valley. PNNL is one of only a few laboratories worldwide with this capability.

NNSA and PNNL celebrated 48 fellows whose year-long assignments spanned the nuclear security technology and policy mission.

National Nuclear Security Administration Graduate Fellow Marc Wonders has spent the past year working with researchers exploring artificial intelligence in the national security mission space.

Risk analysis on the plutonium-fueled power system that supplies electricity to the Mars rover answered the “what if” nuclear safety questions for NASA.