Ice crystals are surprisingly tolerant of defects in their structure. The findings come from the first-ever molecular-resolution observations of nanoscale samples of ice frozen from liquid water.

PNNL brings its expertise to the space domain by joining an organization that facilitates collaboration across the global space industry.

A new peptoid force field better predicts the cis/trans equilibrium of peptoids in multiple solvents.

Nanoscale domains of magnetically susceptible critical materials encounter enhanced magnetic interactions under external magnetic fields, providing a promising new avenue for separations.

A new approach combining computational processes enables the more accurate simulation of nuclear quantum effects in molecular systems.

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

Researchers have begun a series of experiments that could bring about more energy for grid, thanks to a special delivery of 11 "high burnup" rods.

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.

The Department of Energy Art of Science contest entry focuses on the extraordinary universe of chemical bond making and breaking under irradiation.

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.

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.

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

Researchers at PNNL studied the effects of high temperatures and ionizing radiation on tungsten heavy alloys.