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.

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.

Across the United States, organic carbon concentration imposes a primary control on river sediment respiration, with additional influences from organic matter chemistry.

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.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

A new perspective article discusses how integrating carbon dioxide capture and conversion in solvents can lead to cheaper and more efficient carbon management systems.