PNNL’s Climate Network with MSIs and HBCUs aims to bring opportunities to diverse populations.

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

PNNL study explored multiple factors that could impact future snowpack—a critical source of water for communities, irrigation and energy generation.

Spatial proteomics enables researchers to link protein measurements to features in the image of a tissue sample, which are lost using standard approaches.

A 19-person, multi-institutional national laboratory team received the inaugural Gordon Bell Prize for Climate Modeling from the Association for Computing Machinery for their work on more accurately modeling deep convective clouds.

An energy expert and economist who has played a leading role in formulating and coordinating U.S. climate policy is the new director of the Joint Global Change Research Institute in College Park, Maryland.

New research shows how cloud shapes affect the process of cloud evolution, resulting in better understanding of how clouds behave, improving weather forecasts, and enhancing comprehension of climate systems.

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 50th anniversary of the Finnish Institute for Verification of the Chemical Weapons Convention was recently celebrated in Helsinki, Finland. PNNL's Jonathan Forman and Raul Aranzazu attended this international event.

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.

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

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.

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

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.

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

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

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