Shear Assisted Processing and Extrusion (ShAPE) imparts significantly more deformation compared to conventional extrusion. The latest ShAPE system at PNNL, ShAPEshifter, is a purpose-built machine designed for maximum configurability.

Christina Lomasney moderates panel on commercialization pathways for emerging artificial intelligence and high-performance computing technologies.

The Center for Continuum Computing at PNNL aims to integrate cloud platforms, high-performance computing, and edge devices into a seamless ecosystem that accelerates scientific discovery.

PNNL’s Center for Cloud Computing is addressing challenges in data management and hybrid cloud solutions with industry and academic partnerships.

A multi-institutional team of researchers systematically compared extraction techniques for characterizing plant litter composition that relies on organic matter extraction.

A new database allows researchers to connect lattice parameters and composition in olivine.

New methodology can evaluate the potential for carbon storage and critical mineral recovery in undercharacterized geological settings.

Research identifies the mechanisms through which peptoids affect ions in solution and a mineral surface, increasing the rate of carbonate crystal growth.

In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.

Data from SOSAT web tool informs site selection and management for the subsurface injection of captured carbon dioxide.

PNNL research unlocks key findings needed for potential commercial deployment of carbon mineralization technology.

Department of Energy’s Advanced Research Projects Agency-Energy selects PNNL project to help accelerate the development of marine carbon dioxide removal technologies.

A suite of experiments provide insight into how diopside reacts with carbon dioxide to form stable carbonate species.

PNNL-Sequim scientists will spend the next year testing a new technology that could allow the ocean to soak up more carbon dioxide without contributing to ocean acidification.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

Newly developed models can help rapidly optimize systems to meet the need for rapidly deployable commercial carbon capture.

The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.

A review article led by researcher Jade Holliman explores the different classes of metamaterials, from the underlying fundamental science to potential applications.

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

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