Researchers combined crystallographic data and computational studies to investigate plutonium-ligand bonding within a hybrid material construct.

In a water-containing system, the open circuit potential stabilizes positively charged species and lowers the energy barrier of the reaction.

A new approach broadens the reach of quantum computers to previously challenging systems.

Researchers identified a new intermediate phase that forms during the crystallization of hydrated aluminum-containing salts.

The nature of an iron oxide mineral and amount of light control electron movement from a light-absorbing molecule to the mineral, rather than the conditions of the surrounding aqueous environment.

Data-driven experiments can help determine best practices for Random Forest machine learning to predict water quality, particularly nitrate levels.

A review article examines a decade of work on the atom-scale process of turning carbon dioxide into stable minerals.

The amount of radiation in a system influences how fast aggregated boehmite particles dissolve.

A new deep learning approach allows researchers to rapidly analyze three-dimensional representations of multi-component catalysts.

Using electrocatalysis offers a different path for reactions involving polar groups.

Where molybdenum dopants sit within catalytic material affects catalysis at a mechanistic level.

Simulations show that pH influences boehmite nanoparticle structure and sorption ability.

Researchers isolated a molecular copper hydride monomer for the first time.

A new simple and scalable synthesis produces nanoparticle assemblies that can perform catalytic hydrogen sensing at room temperature for the first time.

A study that combined experiments and theory showed how model enzymes control challenging reactions involving highly reactive carbocations.

By decreasing the amount of precious metal in a catalyst, the system increased its efficiency and selectivity for breaking apart plastics.

The size and concentration of ions influences the aggregation behavior of solutions of boehmite.

PNNL researchers developed a hybrid quantum-classical approach for coupled-cluster Green’s function theory that maintains accuracy while cutting computational costs.

PNNL researchers design an artificial intelligence-guided electron microscope in a Laboratory Directed Research and Development study.

The size of the alkali metal within the material influences the crystallization pathway.