Developing a new scheme to more efficiently solve quantum chemistry problems.

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.

PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.

PNNL researchers will pursue both fundamental and applied projects with this support from the Department of Energy

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.

In the latest issue of the Domestic Preparedness Journal, Ashley Bradley and Kristin Omberg share how new research is shedding light on the scientific and technological challenges with detecting fentanyl.

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.

Research at PNNL and the University of Texas at El Paso are addressing computational challenges of thinking beyond the list and developing bioagent-agnostic signatures to assess threats.

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

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.