A new study demonstrates a hybrid model that can simulate part of a system at the molecular scale and other parts at larger scales in a computationally efficient manner, providing greater simulation flexibility.

New research investigating water-lean solvents for carbon dioxide capture identifies the unique chemistry possible with their use, may lead to new design principles that move beyond single carbon capture.

Long-range electron transfer reactions play important roles in many chemical and biochemical processes. A new study demonstrates that a common organic host molecule can behave like an alkali metal in long-range electron transfer reactions.

Scientists unravel a secret to oil production in plants, opening up the possibility of increasing production for biofuels and other applications.

Twinned nanocrystals have unique physical and chemical properties, a variety of which are detailed by a new study. These findings can help guide future efforts in controlling twinning and detwinning in gold nanoparticles.

IDREAM scientists capture electronic response to ionization.

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.

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.

IDREAM research shows the size of cations in highly concentrated nitrite solutions affects the production of radicals.

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.

In a new approach, quantum flow algorithms are used to simulate many-body systems on quantum computers and effectively describe chemical processes.

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

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

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.

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

The convergence of artificial intelligence, cloud, and high-performance computing to accelerate scientific discovery is the focus of a multi-year collaboration between Microsoft and PNNL.

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

PNNL has created the Center for AI @PNNL to coordinate the pioneering research of hundreds of scientists working on a range of projects in artificial intelligence.

Input from humans helps when deciding whether to trust the recommendations or decisions of a machine-learning system.