Harnessing the sea for decarbonized energy is the focus of a new collaboration between PNNL and the University of Guam.

A systematic, multiple scenario approach was used to analyze the compounding impacts of demands for land for biofuels with increased land scarcity under a diverse set of uncertainties.

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

rmap enables users with limited to no geographic information system knowledge use R to visualize simple tabular data.

Researchers developed a machine learning model that can analyze chemical reactions as they happen in an electron microscope.

The methods researchers use to estimate crop yield gaps determines the location of projected future agricultural “breadbasket” regions.

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.

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

PNNL researchers are moving energy research forward through collaborative projects with universities across the United States.

One year into an Early Career Research Program award, Marcel Baer is developing new workflows to model biologically inspired systems more efficiently.

A new project will produce a database of optimized conditions for efficient, carbon negative recovery of energy-relevant minerals in red mud waste.

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.

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

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

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

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

PNNL research, featured on the cover of two science journals, describes advancements in using Raman spectrometry for Hanford Site nuclear waste remediation.

Launching a premier partnership, PNNL and the University of Texas El Paso (UTEP) signed a memorandum of agreement on UTEP’s campus on October 6.

Better representing electric capacity markets, economic retirements, and power-plant age structure provides a more robust understanding of the future evolution of the electric sector.