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.

Study finds regional priorities shape people’s interest in improving the energy efficiency of their homes.

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.

PNNL had a significant presence at October’s North American Wind Energy Academy/WindTech 2023 Conference in Denver, Colorado. Thirteen PNNL wind experts participated in various capacities.

As electricity grids incorporate renewables, several factors will constrain future output, according to a new paper.

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

Mandy Mahoney, director of the DOE Building Technologies Office, visited PNNL in late November. One key agenda item involved meeting with staff for a discussion of effective equity and justice integration in buildings-related research.

Fiscal year 2023 offered PNNL wind researchers a wealth of opportunity to address wind implementation challenges and expand its support of various federal and state agency wind energy goals.

Understanding the risk of compound energy droughts—times when the sun doesn’t shine and the wind doesn’t blow—will help grid planners understand where energy storage is needed most.

Department of Energy’s Advanced Research Projects Agency-Energy selects PNNL project to help accelerate the development of marine carbon dioxide removal technologies.

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

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.

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.

PNNL chemical engineer Reid Peterson helped develop the process to pretreat Hanford Site tank waste by removing cesium-137.

From air-sealing windows and checking for leaky ducts to insulating the attic, PNNL researchers offer tips on how to keep a home warm in winter weather.

A novel electrode functionalization strategy enables efficient removal of toxic heavy metals from wastewater.