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.
Two new publications provide emergency response agencies with critical insights into commercially available unmanned ground vehicles used for hazardous materials response.
To assess the impact of observation period and gauge location, model parameters were learned on scenarios using different chunks of streamflow observations.
Jonathan Barr, senior systems engineer at PNNL, was recently invited to co-present on a panel at the Texas Department of Emergency Management Annual Conference.
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.
PDX, PNNL, and Sandia National Laboratories are exploring the feasibility of hydrogen fuel for the PDX bus fleet—an idea that could have novel benefits for hazard resilience.
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 Wildfire Mitigation Plan Database was built to support electric utilities, state governments, policymakers, and regulators in understanding and improving wildfire risk and resilience strategies.
Ampcera has an exclusive licensing agreement with PNNL to commercially develop and license a new battery material for applications such as vehicles and personal electronics.
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.
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.
PNNL will analyze current and projected transportation fuel dynamics, supply chain risks, and risk comparators with relevant sectors, such as transportation electrification.
Sergei Kalinin, a joint appointee at the University of Tennessee, Knoxville and PNNL, and Ji-Guang (Jason) Zhang, a PNNL Lab Fellow, are part of the 2024 class of National Academy of Inventors Fellows.
