Quantum simulators help navigate noise on GPU-based HPC systems.

New work developed a methodology to generate building temperature setpoint schedules for use by modelers in large-scale building energy simulations.

COVID-19 changed when and where we use electricity. Researchers showed that commonly available total demand data masked the actual changes.

Storage Targets and Release Function Inference Tool uses data to infer the operating policies of large reservoirs on a national scale.

PNNL researchers utilized the Peeters-Devreese-Soldatov formulation to improve the accuracy of calculations for quantum chemistry.

A multisectoral analysis that combines land use data with hydrological simulations reveals wide disparities in potential source water contamination.

PNNL scientist Brian O’Neill led the compilation of an IPCC chapter about climate-related risks.

COVID-19 had multiple impacts on the electric sector and the nature of those impacts varied on the scale analyzed.

To improve the study of human-Earth interactions, a 10-year vision report by the MultiSector Dynamics community of practice encourages the use of emerging human systems datasets, embedded intelligence in modeling, and workforce diversity.

A hybrid computing approach for solving quantum chemical problems offers a practical bridge between classical and quantum computing.

Williams brings his deep understanding of the technology industry and PNNL’s quantum and national security expertise to this Technical Advisory Committee.

A team of researchers developed a simulation approach to identify how atomic structures can affect the phonon transport of energy and information in quantum systems near absolute zero temperatures.

Using a novel settlement-related dataset produced more accurate population downscaling than using other, more traditional datasets.

Despite an increase in future electricity demands, virtual water trading in the U.S. electricity sector is expected to decline as renewable energy expands.

Fundamental research conducted at the $90-million research facility will help the nation meet its clean energy goals.

High-performance imaging provides a cornerstone for innovation at the Energy Sciences Center opening at PNNL.

Scott Chambers creates layered structures of thin metal oxide films and studies their properties, creating materials not found in nature. He will soon move his instrumentation and research to the new Energy Sciences Center.

PNNL computer scientist Ang Li serves as one of the principal investigators for a project selected to receive DOE funding.

PNNL’s Karol Kowalski leads one of the 29 projects selected to receive a total of $73 million in funding.

The U.S. Department of Energy has selected the Scalable Predictive Methods for Excitations and Correlated Phenomena project to receive funding to develop software for chemical research.