Micron and PNNL co-design the Crete computer system, delivering a new memory architecture for data-intensive scientific computing and AI applications.

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

Alex Beliaev, a biologist at PNNL, was named a Society for Industrial Microbiology and Biotechnology fellow.

Quantum computing promises leaps in chemistry and materials science, and PNNL is preparing to realize its potential with a collaborative approach.

New electees represent research in genomics, grid resilience, coastal ecology, and more.

Researchers from PNNL and Parallel Works, Inc., applied machine learning methods to predict how much oxygen and nutrients are used by microorganisms in river sediments.

This study used historical data, remote sensing, and aquatic sensors to measure how far wildfire impacts propagated through the watershed after the 2022 Hermit’s Peak/Calf Canyon fire, New Mexico’s largest wildfire in history.

The Coastal Observations, Mechanisms, and Predictions Across Systems and Scales: Field, Measurements, and Experiments project established a network of observational field sites across Chesapeake Bay and western Lake Erie.

This study characterized above- and below-ground properties to explore the spatial heterogeneity of the terrestrial aquatic interface ecosystem within the Chesapeake Bay area and evaluate the major drivers of soil respiration.

More than 25,000 participants from industry, government, academia, and the public attended the event.

PNNL scientist James Stegen and an international team of collaborators recently published a comprehensive review of variably inundated ecosystems (VIEs).

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.

A new time-dependent wavefunction formulation for the cumulant Green’s functions can produce more accurate simulations.

Brown University professor and PNNL joint appointee was honored for his exceptional work in applied mathematics.

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.

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.

PNNL is hosting a scientific conference focused directly on understanding and predicting the collection of an organism’s traits.