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.

PNNL played host in mid-May to the Artificial Intelligence for Robust Engineering & Science workshop, an annual event that explores advances in artificial intelligence

PNNL shared recent developments in artificial intelligence at the inaugural Special Competitive Studies Project AI for National Competitiveness Expo.

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 at PNNL harnessing advances in deep learning, deep reinforcement learning and generative AI to change how science is conducted and achieve original scientific results and breakthroughs.

Study explores Exploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments, a consortium of scientists interested in the exchange between water and land in coastal systems.

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.

With Earth system models running at higher resolutions, researchers evaluated the sensitivity of aerosol properties to horizontal grid spacing.

IDREAM scientists capture electronic response to ionization.

This study demonstrates a new model that integrates complex organic matter (OM) chemistry and multiple electron acceptors to predict kinetic rates of OM oxidation.

PNNL computing experts Robert Rallo and Court Corley contribute their knowledge to a recent DOE report on applications of AI to energy, materials, and the power grid.

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.

Study reviews the loss of carbon dioxide from soils and explores most compelling challenges and opportunities for the future.

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

The software democratizes hardware designs by enabling domain scientists to design their own accelerators.

A set of papers combines surface science measurements on tiny particles with uncrewed aerial systems to better understand and model aerosols.

PNNL recently partnered with Amazon Web Services for AWS GameDay, a gamified learning event that challenges participants to use AWS solutions to solve real-world technical problems in a team-based setting.

Study demonstrates that choosing more accurate numerical process coupling helps improve simulation of dust aerosol life cycle in a global climate model.

Study introduces a mathematically rigorous analysis framework that provides insight into the features and implications of coupling method choices.