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.
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.
John VerWey, East Asia national security advisor, delivered remarks on competition in global supply chains at a U.S.-China Economic Security Review Commission hearing in June 2022.
PNNL is highlighting scientific and technical experts in the national security domain who were recently promoted to scientist and engineer level 5, one of PNNL’s most senior research roles.
Chemist April Carman was recognized for her career accomplishments with the Professional Achievement Award from the University of Nevada, Reno, College of Science.
New study elucidates the complex relaxation kinetics of supercooled water using a pulsed laser heating technique at previously inaccessible temperatures.
PNNL's Rich Ozanich, project manager of opioids standards and equipment testing, served on an expert panel about opioid detection as part of a Department of Homeland Security S&T research and development showcase.