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

PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.

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.

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

HiSVSIM enables large-scale quantum simulations through graph partitioning.

Research organizations work toward compelling market-ready solutions for building operations.