Earth Scientist Laura Fierce mentors Department of Energy Science Graduate Student Research program awardees.

Researchers at PNNL joined more than 600 national experts who contributed to NCA5.

The new PTM-Psi workflow opens the door for uncovering molecular insights within proteomics datasets.

From energy storage to cybersecurity, this 2023 wrap-up offers a glimpse of PNNL innovations with a seasonal twist.

An initiative from Washington State University and Snohomish County leaders is aiming to make Paine Field a nexus for testing and improving sustainable aviation fuels made from non-petroleum materials.

PNNL research unlocks key findings needed for potential commercial deployment of carbon mineralization technology.

As electricity grids incorporate renewables, several factors will constrain future output, according to a new paper.

Harish Gadey, David Peeler, and Tom Brouns named to Waste Management Symposia Program Advisory Committee positions to help develop radioactive waste management discussions.

PNNL researchers comment on the “Adversarial Machine Learning” white paper from the National Institute of Standards and Technology.

PNNL has created the Center for AI @PNNL to coordinate the pioneering research of hundreds of scientists working on a range of projects in artificial intelligence.

Hi-C metagenomics-informed phage-host infection networks detected in soil pre- and post-drying.

If current warming trends continue, heat waves like Washington's deadliest could grow stronger and afflict the Pacific Northwest more often.

Scientists at PNNL have published a new article that focuses on understanding the composition, dynamics, and deployment of beneficial soil microbiomes to get the most out of soil.

PNNL is one of the founding partners of the Trillion Parameter Consortium, which was formed to create reliable generative AI models.

A team of scientists at PNNL developed new computational models to predict the behavior of these impurities and reduce the expense and risk related to actinide metal production.

More than a dozen PNNL scientists have been named among the world’s most influential researchers on Clarivate’s 2023 Highly Cited Researchers List.

Researchers use models to represent relationships between climate and socio-economic processes, helping inform decisions for slowing climate change and enhancing resilience.

Input from humans helps when deciding whether to trust the recommendations or decisions of a machine-learning system.

PNNL’s DataLife tool analyzes and identifies bottlenecks in scientific workflows.

Investigating the impact of global warming on mesoscale convective systems initiation and growth with a theoretical model.