The 98th ACS Colloid and Surface Science Symposium will be co-organized by Shuai Zhang and Jim De Yoreo.

Researchers devised a quantitative and predictive understanding of the cloud chemistry of biomass-burning organic gases helping increase the understanding of wildfires.

Models have identified a new source of anthropogenic emissions driving the observed weakening of the Atlantic Meridional Overturning Circulation.

Reproducible workflows for binning and visualizing nuclear magnetic resonance spectra from environmental samples.

PNNL researchers use chemometric analysis to model chemistry in molten salt.

Scientists stop the motion of atoms to watch electrons move in liquid water.

Differences in water interactions lead to two gibbsite dissolution pathways modulated by solution acidity.

Post-consumer recycled aluminum to be transformed into high strength building materials and consumer goods with patented ShAPE™ manufacturing process.

A simple gel-based system separates metals ions from a model solution of dissolved battery electrodes without the need for specialty chemicals, membranes, or toxic solvents.

Machine learning methods and data science can uncover hidden patterns in nanoparticle synthesis conditions and property outcomes.

Physicist Elke Arenholz’s contributions to x-ray magnetic spectroscopy led to her elevation to Fellow status by the IEEE.

Irradiation in a sodium hydroxide solution increases the dissolution rate and particle roughness of gibbsite compared to dry irradiation.

From energy storage to cybersecurity, this 2023 wrap-up offers a glimpse of PNNL innovations with a seasonal twist.

PNNL research unlocks key findings needed for potential commercial deployment of carbon mineralization technology.

A newly developed, highly conductive copper wire could find applications in the electric grid, as well as in homes and businesses. The finding defies what's been thought about how metals conduct electricity.

Elias Nakouzi brings 3D atomic force microcopy expertise to a project focused on understanding how hybrid bio-based nanomaterials assemble.

A seemingly simple shift in lithium-ion battery manufacturing could pay big dividends, improving electric vehicles’ ability to store more energy per charge and to withstand more charging cycles.

A team of scientists at PNNL developed new computational models to predict the behavior of these impurities and reduce the expense and risk related to actinide metal production.

PNNL is one of the founding partners of the Trillion Parameter Consortium, which was formed to create reliable generative AI models.

Resolving how nanoparticles come together is important for industry and environmental remediation. New work predicts nanoparticle aggregation behavior across a wide range of scales for the first time.