Scientists at PNNL harnessing advances in deep learning, deep reinforcement learning and generative AI to change how science is conducted and achieve original scientific results and breakthroughs.

Policy changes in power, energy, buildings, and more could help slow global temperature rise, according to a new report with co-authors from PNNL’s Joint Global Change Research Institute.

Scientists unravel a secret to oil production in plants, opening up the possibility of increasing production for biofuels and other applications.

The 2024 Jack Simons Award honor recognizes Li for his expertise in integrating chemistry with computing for fundamental science research.

Visit featured information exchange and tours of PNNL work and facilities that relate to the work of the International Atomic Energy Agency.

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

A new study suggests accessing groundwater in key regions could become prohibitively expensive as lower-cost stores are used up.

PNNL researchers learn to control peptoid “handedness,” one key to precision drug delivery and diagnostics.

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.

Five PNNL scientists participated in an invitation-only Department of Energy-sponsored workshop on coastal systems. 

New work finds hurricanes are intensifying faster close to the coast—a trend that’s likely to ramp up in a warmer world.

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

Study explores Exploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments, a consortium of scientists interested in the exchange between water and land in coastal systems.

Twinned nanocrystals have unique physical and chemical properties, a variety of which are detailed by a new study. These findings can help guide future efforts in controlling twinning and detwinning in gold nanoparticles.

With Earth system models running at higher resolutions, researchers evaluated the sensitivity of aerosol properties to horizontal grid spacing.

IDREAM scientists capture electronic response to ionization.

This study demonstrates a new model that integrates complex organic matter (OM) chemistry and multiple electron acceptors to predict kinetic rates of OM oxidation.

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.

Practical decontamination of industrial wastewater depends on energy-efficient separations. This study explored using ionic liquids as part of the process, enabling efficient electrochemical separation from aqueous solutions.