Researchers synthesize molecular-level laboratory experiments to develop comprehensive model representations of new particle formation and the chemical transformation of precursor gases.

Researchers show application of a causal model better identifies direct and indirect causal relations compared to correlation and random forest analyses performed over the same dataset.

Researchers introduce revised emission treatment that conserves mass and preserves the original heterogeneity.

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

PNNL researchers review ceramic-metal composite technology for immobilizing radioactive wastes from nuclear reactors, including advanced reactors.

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.

Visit featured information exchange and tours of PNNL work and facilities that relate to the work of the International Atomic Energy Agency.

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.

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.

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

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

A new quantum algorithm speeds up simulations of coupled oscillator dynamics.

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.

A new model accounts for co-occurring environmental parameters to improve predictions of a hurricane’s intensification.

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

The SHASTA program is doing a deep dive on subsurface hydrogen storage in underground caverns, helping to lay the foundation for a robust hydrogen economy.