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.
Early life exposure to polycyclic aromatic hydrocarbons (PAHs), found in smoke, has been linked to developmental problems. To study the impacts of these pollutants, PAH metabolism in infants and adults were compared.
Research at PNNL and the University of Texas at El Paso are addressing computational challenges of thinking beyond the list and developing bioagent-agnostic signatures to assess threats.
PNNL computing experts Robert Rallo and Court Corley contribute their knowledge to a recent DOE report on applications of AI to energy, materials, and the power grid.
Researchers used a combination of sophisticated laboratory incubations and field measurements to determine the role of microbial production and consumption of methane in soils with different exposure to tidal inundation
New methodological approach demonstrates how to assess the economic value, including non-traditional value streams, of converting non-powered dams to hydroelectric facilities.
Researchers devised a quantitative and predictive understanding of the cloud chemistry of biomass-burning organic gases helping increase the understanding of wildfires.
A PNNL study developed a water management module for Xanthos that distinguishes between the operational characteristics of hydropower, irrigation, and flood control reservoirs.
Pacific Northwest National Laboratory launches the Training Outreach and Recruitment for Cybersecurity Hydropower program at the University of Texas at El Paso.