At a conference featuring the most advanced computing hardware and software, ML in its various guises was on full display and highlighted by Nathan Baker’s featured invited presentation.

PNNL and Argonne researchers developed and tested a chemical process that successfully captures radioactive byproducts from used nuclear fuel so they could be sent to advanced reactors for destruction while also producing electrical power.

In the third year of the DISCOVR Consortium project, the consortium team has identified an algal strain that progressed successfully through multiple evaluation phases.

Scientists at PNNL are bringing artificial intelligence into the quest to see whether computers can help humans sift through a sea of experimental data.

In today’s digital age, the rabbit hole of connected information can be not only a time sink, but downright overwhelming. Even for high-performance computers.

A new Co-Optima report describes an assessment of 400 biofuel-derived samples and identifies the top ten candidates for blending with petroleum fuel to improve boosted spark ignition engine efficiency.

Twenty-four analysts from U.S. intelligence organizations met in August for a machine learning activity with PNNL researchers Nicole Nichols, Jeremiah Rounds, Lawrence Phillips, and Brian Kritzstein.

New PNNL research shows that a pairing of humble minerals outshines other reactive materials when it comes to producing hydrogen.

Researchers at PNNL have solved a mystery for a chemical reaction essential for fuel and fertilizer production.

Trouble on the electric grid might start with something relatively small: a downed power line, or a lightning strike at a substation. What happens next?

Pacific Northwest National Laboratory is leading efforts to address next-generation computing’s critical role in protecting the nation from cybersecurity threats.

Nitrogen oxides, also known as NOx, form when fossil fuels burn at high temperatures. When emitted from industrial sources such as coal power plants, these pollutants react with other compounds to produce harmful smog.

Researchers are seeking to better understand how nitrogenase acts as a catalyst to break down nitrogen.

Researchers at PNNL have developed a model that predicts outcomes from the algae hydrothermal liquefaction process in a way that mirrors commercial reality much more closely than previous analyses.

PNNL’s Tim Johnson and lead researcher Tanya Myers were recently selected for the Applied Spectroscopy William F. Meggers Award.

Researchers at PNNL have introduced an alternative method using a molecular-based pump that could potentially use a quarter less energy than the age-old mechanical pump.

Researchers at PNNL are applying deep learning techniques to learn more about neutrinos, part of a worldwide network of researchers trying to understand one of the universe’s most elusive particles.

PNNL and National Renewable Energy Laboratory have partnered on a first-of-its-kind tool that estimates costs of catalysts.

Researchers at PNNL and their collaborators have made a significant improvement to a catalyst that is more rugged and can reduce tailpipe pollution at lower temperatures than existing methods.

Kelsey Stoerzinger leverages advances in surface chemistry to develop materials for clean energy and water purification.