A new quantum algorithm speeds up simulations of coupled oscillator dynamics.

PNNL electrical engineer Samrat Acharya led a team that earned the 2024 IEEE Innovative Smart Grid Technologies Conference Best Paper Award.

As new paradigms in advanced computing take shape, computational chemistry researchers are finding new ways to solve challenging chemistry problems.

In a new approach, quantum flow algorithms are used to simulate many-body systems on quantum computers and effectively describe chemical processes.

PNNL scientists have put forth a new approach to protect the electric grid, creating an approach that sorts and prioritizes cyber threats on the fly.

Visual Sample Plan, a free software tool developed at PNNL that boosts statistics-based planning, has been recognized with a 2024 Federal Laboratory Consortium Award.

Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications.

Battery energy storage systems are being proposed in municipalities across the U.S. PNNL researchers can help community planners guide safe siting and operations.

Tumeo will lead the ChemComp project, which was awarded for Exploratory Research in Extreme Scale Science

Clean hydrogen energy infrastructure is coming to the Pacific Northwest with a newly announced hydrogen hub, and PNNL experts are advising the work to come.

Newly developed ultra-low radiation cables reduce background noise for neutrino and dark matter detectors.

PNNL celebrates World Energy Storage Day (September 22) by introducing you to some of our best and brightest in this area.

Stinis will serve as a principal investigator on two of the four projects selected for funding by the Advanced Scientific Computing Research program.

Researchers unveil user-friendly software to keep complex projects on budget and on schedule.

The Rapid Assessment of Platform Technologies to Expedite Response project aims to prepare against future pandemics.

The award was given at the 29th International Conference on Information, Communication and Automation Technologies.

Zhijie (Jay) Xu will apply his expertise in multiscale modeling to this editorial role.

PNNL researchers present challenges and opportunities for fusing graph neural networks with deep reinforcement learning.

ACMD staff contributed to 30 years of atmospheric data collection for the Department of Energy’s Atmospheric Radiation Measurement user facility.

The papers were featured in the security and quantum sessions at the 2023 International Symposium on Computer Architecture.