Understanding molecular modifications of proteins in the red yeast could help scientists re-engineer the organism’s phenotype.

Three research teams led by PNNL organizers achieve journal publications following the Mathematics Research Communities program.

Researchers developed a way to precisely control dopant structures and locations in carbon-based materials.

Expanding the nation’s largest wind power plant time series database; helping grid planners navigate a resilient energy future with better data.

Continued studies will deepen scientists’ understanding of virus-host interactions at the molecular level and also pave the way for developing better drugs to fight emerging viruses.

Researchers developed a pathway for the solution synthesis of core–crown heterostructures with controlled electronic properties.

Flexible, high-throughput proteomics approach identifies protein modifications related to pancreatic stress and insulin production.

Under an optical field, nanoparticle attachment in a model system heavily depends on surface roughness.

PNNL researchers have published their paper, “Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data,” in the Journal of Proteome Research.

Scientists uncover how cyanobacteria's circadian cycle controls carbon and energy metabolism, increasing carbon dioxide-to-bioproducts yields.

Scientists map how transitions from day to night control gene regulatory networks in cyanobacteria, revealing key orchestrators of metabolic switching.

Chromium cations better adapt to changes in oxygen stoichiometry than iron cations.

Using interfacial charge transfer to control cation charges in oxide superlattices offers insights for designing functional heterostructures.

Calcium carbonate mineralization occurs through a multi-step process that begins with a dense liquid phase.

PNNL scientists use proteomics to unveil how high-density lipoproteins protect against cholesterol accumulation in the artery wall.

Computing and artificial intelligence aid scientists who seek to understand function-driven design and control of biological systems.

A newly funded project will develop the fundamental understanding of phenomena that underpin material properties important for quantum applications.

Fully identifying what controls nanocrystal assembly requires incorporating non-traditional forces into models.