In honor of National Intern Day, PNNL and intern Jonathan Mills were named among the Top 100 in the nation by early-career recruiting firm WayUp.

Better representing electric capacity markets, economic retirements, and power-plant age structure provides a more robust understanding of the future evolution of the electric sector.

MSD-LIVE, a cloud-based data and code management system, will be released in summer 2022 for hundreds of scientists.

PNNL researchers teamed up with SambaNova to enhance artificial intelligence for scientific computing.

As wildfires grow increasingly severe, PNNL researchers are working to slow their spread and mitigate their harmful effects.

TransMED analyzes patient data from similar diseases across multiple sources to understand COVID-19 patient outcome risk factors.

PNNL researchers design an artificial intelligence-guided electron microscope in a Laboratory Directed Research and Development study.

An improved model captures the interactions between the U.S. economy, energy, water, and land systems with increased spatial and temporal detail.

A climate change study co-authored by PNNL scientist Hailong Wang inspired an artist to create an exhibit based on the research.

PNNL contributes to 30 years of data on clouds, radiation, and other climate-making factors as part of field campaigns and analysis conducted by DOE's Atmospheric Radiation Measurement user facility.

Sue Southard's one thousand dives as a PNNL staff member leave a ripple effect on efforts to keep our ocean healthy, our economy thriving, and our waters safe.

Parallel graph neural networks identify protein-ligand 3-D structural interactions to aid in protein function prediction and drug discovery.

Brian O’Neill joins a Roundtable on climate security organized by the National Academies of Sciences, Engineering, and Medicine.

An analysis of land use in watersheds that supply drinking water to over a hundred United States cities identified a wide range of exposure to potential contamination.

PNNL experts perform fundamental climate science work at multiple scales to understand impacts on energy, water, food, and infrastructure systems.

PNNL researchers have uncovered a plant-derived process that leads to the formation of aerosol particles over the Amazon rainforest and potentially other forested parts of the world. 

New work developed a methodology to generate building temperature setpoint schedules for use by modelers in large-scale building energy simulations.

COVID-19 changed when and where we use electricity. Researchers showed that commonly available total demand data masked the actual changes.

PNNL Chief Scientist for Computing Jim Ang will be part of a DOE Office of Science virtual discussion regarding industry collaborations on AI hardware.

Storage Targets and Release Function Inference Tool uses data to infer the operating policies of large reservoirs on a national scale.