PNNL’s Andrew Engel, Tony Chiang, and Sutanay Choudhury at the 2024 ICLR in Vienna.

Data scientist at PNNL receives the Environmental and Engineering Geophysical Society and Geonics Limited Early Career Award for work with geophysical modeling and subsurface inversion codes.

Reaching net-zero carbon emissions goals requires finding transformative paths to manage carbon in difficult-to-electrify economic sectors.

PNNL computing experts Robert Rallo and Court Corley contribute their knowledge to a recent DOE report on applications of AI to energy, materials, and the power grid.

A breakthrough in electron microscopy based on deep learning can automatically visualize and identify areas of interest, helping to speed advances in materials science.

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.

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 electrical engineer Samrat Acharya led a team that earned the 2024 IEEE Innovative Smart Grid Technologies Conference Best Paper Award.

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.

A new look at a carbon capture solvent shows clusters and new types of carbon dioxide chemistry that could double carbon conversion.

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.

The SHASTA program is doing a deep dive on subsurface hydrogen storage in underground caverns, helping to lay the foundation for a robust hydrogen economy.

PNNL’s Jeff Burghardt, joins Sanford Underground Research Facility’s User Association Executive Committee.

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.