Increasing concentrations of ions slows the rate of particle aggregation in boehmite suspensions.

PNNL Program Development Office Director Karl Mueller explains how the TEC4 project seeks to make advanced chemical computations accessible to all.

Electronic structure codes in a cloud environment can enable efficient computational chemistry simulations.

Molecular simulations highlight the key interactions between mineral surfaces and organic matter that lead to carbon stabilization in soils.

CACTUS provides AI-powered cheminformatics for autonomous science.

New IDREAM research explores the effects of electrolyte species on boehmite nanoparticle aggregation in legacy wastes.

Pacific Northwest National Laboratory researchers developed a new theoretical method for studying highly correlated systems.

University of Washington Professor David Baker won the 2024 Nobel Prize in Chemistry for computational protein design.

Proton shuffling in hydrated nicotine at low temperatures occurs via a Grotthuss mechanism, identified through experimental and computational work.

ChemReasoner combines decades of chemistry knowledge with large language models to propose strategies for effective new catalysts.

The atomic-level distribution of nickel and cobalt in forsterite depends on the concentration of the different elements.

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 informs the development of foundational models for computational chemistry through hardware-software co-design.

New methodological approach demonstrates how to assess the economic value, including non-traditional value streams, of converting non-powered dams to hydroelectric facilities.

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.

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.

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

Pacific Northwest National Laboratory launches the Training Outreach and Recruitment for Cybersecurity Hydropower program at the University of Texas at El Paso.

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