Micron and PNNL co-design the Crete computer system, delivering a new memory architecture for data-intensive scientific computing and AI applications.

Understanding molecular modifications of proteins in the red yeast could help scientists re-engineer the organism’s phenotype.

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

Scientists have tapped AI and powerful computing to speed up how quickly officials are able to learn important details about nuclear events.

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

Quantum computing promises leaps in chemistry and materials science, and PNNL is preparing to realize its potential with a collaborative approach.

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.

Continued studies will deepen scientists’ understanding of virus-host interactions at the molecular level and also pave the way for developing better drugs to fight emerging viruses.

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

PNNL researchers received an award from the Materials, Metals & Materials Society (TMS) for a publication on friction riveting.

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.

Flexible, high-throughput proteomics approach identifies protein modifications related to pancreatic stress and insulin production.

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

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

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

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

Scientists uncover how cyanobacteria's circadian cycle controls carbon and energy metabolism, increasing carbon dioxide-to-bioproducts yields.

Scientists map how transitions from day to night control gene regulatory networks in cyanobacteria, revealing key orchestrators of metabolic switching.