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

Researchers have developed the first coastal transport model for microplastics to understand how particles move in waterways and coastal currents.

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.

Neural networks techniques enable the efficient capture of electron correlation effects in reduced-dimensionality spaces.

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

In the search for rare physics events, extremely pure materials are essential. A partnership between PNNL and Ultramet has led to tungsten with low contamination from other elements.

A new study led by PNNL researcher TC Chakraborty provides some answers about how irrigated agricultural land near cities affects urban heat stress.

Developing a new scheme to more efficiently solve quantum chemistry problems.

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.

New datasets delineating global urban land support scientific research, application, and policy, but they can produce different results when applied to the same problem making it difficult for researchers to decide which to use.

Pacific Northwest National Laboratory researchers developed a new theoretical method for studying highly correlated systems.

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

Nineteen PNNL-affiliated researchers have been named to Clarivate’s 2024 list of the world's most highly cited researchers.

The demand for energy is growing—and so is the technology supporting it. However, future development of power generation technologies could be affected by a key factor: material supply.

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

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.

The Delaware River Basin is projected to experience a regional increase in flood severity under future climate scenarios.