Separating quantum circuit wiring from molecular data allows researchers to more efficiently perform quantum simulations

Demonstrated that cathodic potential accelerates aqueous phase benzaldehyde hydrogenation.

Amine functionalized graphene oxide yields laminates with an enhanced capacity to adsorb rare earth elements, improved water transport, and greater stability for effective membrane-based separation of critical minerals.

Establishing how electronic redistribution, protonation, and solvent rearrangement are coupled during a proton-coupled electron transfer process.

By selectively stabilizing either a right- or left-handed helical pose of its substrate, an enzyme tunes the final product.

Research provided definitive spectroscopic characterization, reactivity, and deactivation of a reactive monomeric diphosphine-copper hydride intermediate.

PNNL researchers are bringing a data-driven approach to unleashing the potential of geothermal energy.

Five PNNL innovations earned 2026 R&D 100 Awards for advances in biotechnology, manufacturing, critical minerals, and nuclear security.

New software enables the study of nuclear quantum effects in large, condensed phase systems up to 10× faster than traditional methods.

Protein and water environments set the overall redox scale of iron-sulfur clusters, but local coordination geometry fine-tunes the final potential.

New theoretical framings of quantum dynamics enable better quantum-based simulation of molecular systems and dynamics.

PNNL will build an AI-powered modeling platform to help geothermal energy operators maximize electricity generation.

Chiral nanotubes facilitate the direction-specific diffusion of carbon dioxide to be faster than nitrogen gas.

A newly published custom collection of glass formulas for nuclear waste vitrification — developed and validated by PNNL over the past three years — was made possible in that timeframe with AI tools, including a PNNL machine learning model.

An international research team deployed AI-powered computing to solve important chemical structures for energy applications using NVIDIA hardware.

A suite of new modeling methods gives researchers better tools to predict molecular behavior inside cavities.

PNNL has developed a next-generation electrical resistivity tomography system for DOE that uses E4D software and AI-enhanced modeling to produce real-time subsurface images that help guide environmental remediation decisions.

The Hanford Site is now immobilizing radioactive waste in glass: a process known as vitrification. PNNL contributed 60 years of materials science expertise—and is providing operational support—to help the nation meet this cleanup milestone.

Localized gradients in magnetic fields have long-range effects on the concentration of rare earth ions in solution, facilitating field-driven extraction of critical minerals.

Mystery of how important aluminum minerals form and dissolve solved with materials science and advanced imaging studies.