PNNL undergraduate intern Madeline Bartels leads research to verify and quantify carbon mineralization at an unprecedented small scale.

To improve our ability to “see” into the subsurface, scientists need to understand how different mineral surfaces respond to electrical signals at the molecular scale.

A new approach validates quantum algorithms for low-energy nuclear physics applications

Frederick Day-Lewis, Lab Fellow and chief geophysicist at PNNL, was named the 2024 recipient of the Geological Society of America Public Service Award.

Complex metal alloys enter a new era of predictive design for aerospace and other high-temperature applications.

A sustainable ecosystem concept couples marine carbon dioxide removal (mCDR) with algae farming in a win-win scenario for the planet.

PNNL shared recent developments in artificial intelligence at the inaugural Special Competitive Studies Project AI for National Competitiveness Expo.

New research investigating water-lean solvents for carbon dioxide capture identifies the unique chemistry possible with their use, may lead to new design principles that move beyond single carbon capture.

PNNL’s Nell Byler and Elise Bishoff shared their computer vision expertise with high school students at the National Science Bowl Science Day

Researchers are leveraging the ocean’s natural processes to advance approaches to remove carbon dioxide from the atmosphere and store it in the ocean.

Research at PNNL and the University of Texas at El Paso are addressing computational challenges of thinking beyond the list and developing bioagent-agnostic signatures to assess threats.

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.

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

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

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.

In a new approach, quantum flow algorithms are used to simulate many-body systems on quantum computers and effectively describe chemical processes.