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.

Experiments focus on catalysts for off-road vehicles that optimize the use of critical minerals while lasting longer and costing less.

Two new publications provide emergency response agencies with critical insights into commercially available unmanned ground vehicles used for hazardous materials response.

Isotopically layered water films and slow heating enable diffusion tracking.

Jonathan Barr, senior systems engineer at PNNL, was recently invited to co-present on a panel at the Texas Department of Emergency Management Annual Conference.

PNNL has created and licensed a system that sniffs out trace levels of fentanyl, other drugs and explosives through the air.

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.

CO2 separation is key for natural gas purification, but conventional techniques are high-emission processes. New research reveals a novel, doubly segmented, CO2-selective membrane that increases CO2 permeability and reduces emissions.

The Wildfire Mitigation Plan Database was built to support electric utilities, state governments, policymakers, and regulators in understanding and improving wildfire risk and resilience strategies.

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.

The first measurement of the proton diffusion constant at cryogenic temperatures provides insights into the mechanism of proton movement in supercooled water.

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

The low-temperature breakdown of polyolefins is driven by carbenium ions generated from chloroaluminate ionic liquids.

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