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 researchers are developing and evaluating bat tagging and tracking tools that will help design solutions to protect the bat population from wind turbines.

Many industries are increasingly looking at hydrogen as a relatively new but efficient, clean, and quiet power source.

Scientists created a fast-track tutorial that equips a neural network to tackle drug discovery and other applications where there's a shortage of precisely labeled chemical data.

Researchers at PNNL used key metrics to develop visualizations that show how the combined effects of climate change on hydropower and load influence the frequency, duration, and severity of power shortfalls.

A recent study pinpointed the reaction front where lithium (Li) dendrites can come into contact with cathode materials. It also detailed the Li propagation pathway and reaction steps that lead to cathode failure.

Plug and Play DER Challenge seeks to enable distributed energy technologies to integrate, connect and operate in harmony on the power grid.

Scientists are exploring the use of deep neural network to interpret highly technical data related to national security, the environment and the cosmos.

An organic molecule used in dyes and antibiotics may be the key to less expensive, more efficient redox flow batteries.