Five PNNL innovations earned 2026 R&D 100 Awards for advances in biotechnology, manufacturing, critical minerals, and nuclear security.

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.

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.

A streamlined informatics workflow that automatically processes complex data and provides the locations of double bonds in lipids.

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

Metabolomics analysis revealed differences in metabolome profiles for two distinct modes of fungal wood decay.

Data from increasingly complex mass spectrometry instruments met with adaptable data analysis solution.