New partnership agreement to focus on AI, robotics, and advanced energy systems.

Novel Applications for Synchronized Power Instrumentation seeks to improve electric grid resilience, reliability, security, and affordability.

PNNL has developed a next-generation electrical resistivity tomography system for DOE that uses E4D software and AI-enhanced modeling to produce real-time subsurface images that help guide environmental remediation decisions.

PNNL addresses vulnerabilities interconnected to operational technologies by improving cybersecurity with targeted tools and trainings.

RemPlex 2025 Global Summit on Environmental Remediation attendees share knowledge about cleanup and monitoring of complex sites worldwide; more than 100 presentations are posted online.

Connecting energy generation, electricity storage, and using sensors and control software to track load, including precommercial market marine energy generation technologies.

A new patent-pending technology can quickly identify refrigerant leakage in heating, cooling, and refrigeration systems.

The ability of a storm-resolving weather model to predict the growth of storms over central Argentina was evaluated with data from the Clouds, Aerosols, and Complex Terrain Interactions (CACTI) field campaign in central Argentina.

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

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.

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 ARPA-E Energy Innovation Summit brings together researchers, industry leaders, entrepreneurs, and investors to showcase the latest technologies shaping tomorrow’s energy landscape. This year, eight projects led by PNNL were featured.

RemPlex and IAEA convene international leaders to tackle recruitment and retention in complex environmental cleanup efforts.

Research that modeled increased heat pump adoption alongside climate change impacts in Texas showed that high-efficiency heat pumps buffer the strain that electric heating might put on the power grid.

Secretary Granholm praises heat pump workforce development efforts at this year's instructor training program.

PNNL researchers are exploring the kinds of flicker waveforms that the eye and brain can detect, seeking to understand the different visual and non-visual effects that result.