Americans produce enough waste every year to replace up to a quarter of the country’s jet fuel with sustainable alternatives, new research shows.

As new paradigms in advanced computing take shape, computational chemistry researchers are finding new ways to solve challenging chemistry problems.

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.

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.

Researchers at PNNL have developed a new technique to get a high-resolution look at how—and why—corrosion happens.

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?

Now in its twentieth year, the Hydrogen Safety Panel is led by PNNL and includes more than two dozen experts. These experts developed a trusted resource for best practices for hydrogen energy.

A seemingly simple shift in lithium-ion battery manufacturing could pay big dividends, improving electric vehicles’ ability to store more energy per charge and to withstand more charging cycles.

Converting seawater into hydrogen fuel using electrochemistry offers a renewable energy future for Guam.

A new discovery by PNNL researchers has illuminated a previously unknown key mechanism that could inform the development of new, more effective catalysts for abating NOx emissions from combustion-engines burning diesel or low carbon fuel.

From Mexico and Ethiopia to a U.S. national lab, interns are ready to contribute to a sustainable energy future.

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

Researchers created the first open-source database of exotic materials eyed for use in quantum applications.

PNNL scientists investigate the promising properties of a common, Earth-abundant salt.

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-developed catalytic process and catalyst to upgrade ethanol to sustainable aviation fuel wins American Chemical Society award.

PNNL battery researcher Jie Xiao collaborates with academic and industry partners to address scientific challenges in manufacturing lithium-based batteries.

Direct visualization of metal atoms during shear deformation has broad applications from battery design to vehicle lightweighting.

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.