Researchers have developed the first coastal transport model for microplastics to understand how particles move in waterways and coastal currents.

Quantum computing promises leaps in chemistry and materials science, and PNNL is preparing to realize its potential with a collaborative approach.

Researchers from PNNL and Parallel Works, Inc., applied machine learning methods to predict how much oxygen and nutrients are used by microorganisms in river sediments.

Christina Lomasney moderates panel on commercialization pathways for emerging artificial intelligence and high-performance computing technologies.

Lakes are important sentinels of climate change and contribute significantly to the emissions of the second most important greenhouse gas—methane.

The rate of conversion of cloud droplets to precipitation, known as the autoconversion rate, remains a major source of uncertainty in characterizing aerosol’s cloud lifetime effects and precipitation in global and regional models.

To assess the impact of observation period and gauge location, model parameters were learned on scenarios using different chunks of streamflow observations.

PNNL's E-COMP initiative is helping unleash American energy innovation with advanced theories, models, and software tools to better operate power systems that rely heavily on high-speed power electronic control.

This study presents an automated method to detect and classify open- and closed-cell mesoscale cellular convection (MCC) using long-term ground-based radar observations.

The Center for Continuum Computing at PNNL aims to integrate cloud platforms, high-performance computing, and edge devices into a seamless ecosystem that accelerates scientific discovery.

A new report details the potential for floating offshore wind to lower energy costs and enhance the resilience of the nation’s western grid.

PNNL’s Center for Cloud Computing is addressing challenges in data management and hybrid cloud solutions with industry and academic partnerships.

PNNL’s year in review includes highlights ranging from advancing soil science to understanding Earth systems, expanding electricity transmission, detecting fentanyl, and applying artificial intelligence to aid scientific discovery.

The National Transmission Planning Study presents several transmission expansion scenarios that would reliably support the growing demand for energy across the nation.

In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.

New transmission lines and renewable energy projects would bring economic and climate change benefits to the Western United States’s electricity grid.

PNNL will engage with transmission planners and other regional partners through technical assistance and listening sessions with the goal of exploring opportunities to integrate equity into transmission planning.

PNNL electrical engineer Samrat Acharya led a team that earned the 2024 IEEE Innovative Smart Grid Technologies Conference Best Paper Award.

Department of Energy presented six teams from PNNL with the Secretary's Honor Award.

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