New research informs the development of foundational models for computational chemistry through hardware-software co-design.

Three PNNL-affiliated researchers have been named fellows of the American Association for the Advancement of Science, the world’s largest multidisciplinary scientific society.

Tennessee State University received Department of Energy funding to establish an academy focused on preparing students and professionals to work in an emerging field: clean energy systems. PNNL is helping with that effort and others.

The software democratizes hardware designs by enabling domain scientists to design their own accelerators.

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

PNNL joint appointee Sergei Kalinin earned the Peter Duncumb Award for excellence in microanalysis.

Lauren Charles was selected as a guest editor for a One Health collection, published by Nature’s Scientific Reports.

PNNL recently partnered with Amazon Web Services for AWS GameDay, a gamified learning event that challenges participants to use AWS solutions to solve real-world technical problems in a team-based setting.

GUV can reduce transmission of airborne disease while reducing energy use and carbon emissions. But fulfilling that promise depends on having accurate and verifiable performance data.

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

Researchers from PNNL have been assessing installation and use of electric heat pumps in an Alaskan community that relies on fuel oil for heat. The resulting information could advance electrification in cold rural areas across the nation.

Steven Spurgeon, materials scientist supporting the National Security Directorate at PNNL, was recently named lead machine learning editor for the journal Microscopy and Microanalysis.

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.

PNNL is supporting the Department of Homeland Security Science and Technology Directorate's Chemical Security Analysis Center in improving capabilities to enhance detection and analysis of chemical threats.

PNNL scientists have put forth a new approach to protect the electric grid, creating an approach that sorts and prioritizes cyber threats on the fly.

ChatGrid is a practical application of the Department of Energy’s exascale computing efforts and offers a new experience in easy, intuitive, and interactive data interaction.

The physics-informed machine learning optimization framework is now PNNL’s most popular open-source repository on GitHub.

PNNL researchers use chemometric analysis to model chemistry in molten salt.

Ang participated in a White House-hosted CHIPS R&D event and roundtable discussion with senior leaders from industry, academia and key government agencies.

PNNL helps deliver efficiency-related rules and requirements that steadily improve performance of America’s buildings, saving energy and costs and reducing carbon emissions.