Practical decontamination of industrial wastewater depends on energy-efficient separations. This study explored using ionic liquids as part of the process, enabling efficient electrochemical separation from aqueous solutions.
Study demonstrates that choosing more accurate numerical process coupling helps improve simulation of dust aerosol life cycle in a global climate model.
Catalysts that efficiently transfer hydrogen for storage in organic hydrogen carriers are key for more sustainable generation and use of hydrogen. New research identifies activity descriptors that can accelerate novel catalyst development.
The SHASTA program is doing a deep dive on subsurface hydrogen storage in underground caverns, helping to lay the foundation for a robust hydrogen economy.
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
Researchers show that small-scale turbulent fluctuations lead to larger concentrations of cloud droplets than would be possible in conventional models of atmospheric clouds
The world is becoming reliant on increasingly smaller sensors that improve daily life in many ways. A PNNL-led paper takes a closer look at these technologies and their future development for environmental and sensitive species monitoring.
Researchers investigated how stable nanoparticle suspensions form using facet engineering on hematite nanoparticles, demonstrating that controlling the faceting of nanoparticles can effectively maintain particle dispersity.
PNNL is supporting the Department of Homeland Security Science and Technology Directorate's Chemical Security Analysis Center in improving capabilities to enhance detection and analysis of chemical threats.
Researchers seeking to enhance a climate model’s predictive capability identify parameters that cause the largest sensitivities for several important cloud-related fidelity metrics.
Researchers developed a groundbreaking database that includes 40,000 synthetic tropical cyclones, crafted using the Risk Analysis Framework for Tropical Cyclones and pioneering the application of advanced artificial intelligence.