Machine learning methods and data science can uncover hidden patterns in nanoparticle synthesis conditions and property outcomes.

At the GovAI Summit 2023, Ryan Eddy joined the Department of Homeland Security Science and Technology Directorate on a panel highlighting artificial intelligence impacts and opportunities in the field of emergency management.

The Desert Tortoise Council presented PNNL Earth Scientist Cyler Conrad with the Robert C. Stebbins Research Award.

The convergence of artificial intelligence, cloud, and high-performance computing to accelerate scientific discovery is the focus of a multi-year collaboration between Microsoft and PNNL.

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

Irradiation in a sodium hydroxide solution increases the dissolution rate and particle roughness of gibbsite compared to dry irradiation.

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.

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.

Resolving how nanoparticles come together is important for industry and environmental remediation. New work predicts nanoparticle aggregation behavior across a wide range of scales for the first time.

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

Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications.

PNNL chemical engineer Reid Peterson helped develop the process to pretreat Hanford Site tank waste by removing cesium-137.

Soil is a massive reservoir of carbon, holding three times the amount of carbon than in the atmosphere. Soil is a massive reservoir of carbon, holding three times the amount of carbon than in the atmosphere.

Researchers from PNNL, CSET, and Google DeepMind delved into the potential risks of artificial intelligence in a roundtable discussion.

Robert Rallo from Pacific Northwest National Laboratory will direct a machine learning thrust for a new Department of Energy-funded project led by SLAC National Accelerator Laboratory.

A poem inspired by radioactive tank waste—“Can a Scientist Dream it Alone?”—was awarded first place in the Department of Energy’s Poetry of Science Art Contest.

PNNL’s software tool brings together artificial intelligence and satellite imagery to help responders assess damage and take action.