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.

To thwart pathogens, researchers in the epidemiology field of infectious disease (ID) prediction are continuously trying to forecast when, where, and how an ID event will occur.

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.