This summer, scientists at PNNL led discussions on their latest research related to artificial intelligence and One Health at the Health and Environmental Sciences Institute conference.

Three research teams led by PNNL organizers achieve journal publications following the Mathematics Research Communities program.

After isolating copper hydride monomers, researchers identified the mechanistic details of catalyst aggregation and cluster formation.

Trace amounts of iron and chromium can incorporate into gibbsite, affecting how the mineral dissolves.

Expanding the nation’s largest wind power plant time series database; helping grid planners navigate a resilient energy future with better data.

Christina Lomasney moderates panel on commercialization pathways for emerging artificial intelligence and high-performance computing technologies.

Properly identifying iodoplumbate species that are present and stable in a perovskite precursor solution is vital. New research offers insight into reactivity and dynamical processes in solution and the chemical properties of precursors.

A new time-dependent wavefunction formulation for the cumulant Green’s functions can produce more accurate simulations.

Scientists are reviewing the current science of the mechanism and structural dynamics of methyl coenzyme-M reductase, an enzyme involved in biological methane conversion.

A team combined experiments and theory to predict the collective properties of electrolyte solutions.

Neural networks techniques enable the efficient capture of electron correlation effects in reduced-dimensionality spaces.

Under an optical field, nanoparticle attachment in a model system heavily depends on surface roughness.

PNNL researchers have published their paper, “Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data,” in the Journal of Proteome Research.

Directionally biased electrostatic interactions are the key to significantly tuning the reduction potential of iron/sulfur clusters.

The Center for Continuum Computing at PNNL aims to integrate cloud platforms, high-performance computing, and edge devices into a seamless ecosystem that accelerates scientific discovery.

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.