Researchers developed a robust, cost-effective, and easy-to-use cap-based technique for spatial proteome mapping, addressing the lack of accessible proteomics technologies for studying tissue heterogeneity and microenvironments.

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.

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

Advanced proteomic analysis tools dig deep into human blood plasma to understand the molecular nature of advanced alcoholic disease.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

PNNL researchers have developed a new class of chemistry focused on carbon capture technology and made incremental strides in driving down costs.

Pacific Northwest marsh carbon stocks are twice the global average. Long-term sea-level rise impacts will likely decrease ecosystem carbon stocks.