Researchers developed a machine learning model that can analyze chemical reactions as they happen in an electron microscope.

PNNL and Georgia Tech launch a joint institute focused on accelerating security for the critical infrastructure community.

To thwart pathogens, researchers in the epidemiology field of infectious disease (ID) prediction are continuously trying to forecast when, where, and how an ID event will occur.

As leaders in AI and machine learning, PNNL experts are sharing their latest findings at the 36th annual Neural Information Processing Systems (NeurIPS) Conference, Nov. 28–Dec. 9, 2022.

Silicone wristbands could be more convenient option for collecting exposure data.

Space Systems Command and PNNL welcome the University of Texas at El Paso to the Cyber Halo Innovation Research Program.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

PNNL joint appointee Auroop Ganguly uses data science to study the impacts of climate change.

A new web-based tool provides easy-to-understand progress metrics and other data about groundwater cleanup sites overseen by the DOE Office of Environmental Management.

Launching a premier partnership, PNNL and the University of Texas El Paso (UTEP) signed a memorandum of agreement on UTEP’s campus on October 6.

SEA-CROGS is one of four Mathematical Multifaceted Integrated Capability Centers selected for support by the Department of Energy.

New research makes molecular-level calculations of water faster and easier.

PNNL researchers teamed up with SambaNova to enhance artificial intelligence for scientific computing.

PNNL researchers developed a hybrid quantum-classical approach for coupled-cluster Green’s function theory that maintains accuracy while cutting computational costs.

PNNL researchers created a model that helps materials scientists not only predict what is, but what could be.

PNNL researchers design an artificial intelligence-guided electron microscope in a Laboratory Directed Research and Development study.

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

Researchers achieved the complete assignment of the infrared spectrum of a hydronium-water “magic number” cluster reported in Science in 2004.

A multi-institutional team has developed a deep learning framework to identify novel molecules as drug candidates.

PNNL researchers developed a way to produce accurate simulations of complex physical systems using renormalized approximations across multiple scales