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.

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

Researchers have been investigating if machine learning techniques could be used to help create novel beers.

Human-machine teaming may sound like something from the distant future. In “Human-Machine Teaming: A Vision of Future Law Enforcement” in Domestic Preparedness, Corey Fallon, Kris Cook, and Grant Tietje of PNNL examine this topic.

New role for Harker-Klimeš merges her expertise in marine energy research and her love for the ocean.

Artificial intelligence-based decision tool enables grid operators to respond more quickly and effectively to grid emergencies.

PNNL is highlighting scientific and technical experts in the national security domain who were recently promoted to scientist and engineer Level 5, one of PNNL’s most senior research roles.

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.

PNNL has received 119 R&D 100 Awards since 1969, when the laboratory began submitting entries in the contest that recognizes top 100 inventions each year.

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 has paired one of its offshore wind research buoys with its ThermalTracker-3D technology to correlate avian activity with ocean and weather conditions off the California coast.

A new model offers more accurate predictions of how intensely hurricanes may strike.

PNNL data scientists are refining their artificial intelligence tools with COVID-19 data to advance therapeutics and treatments for a future pandemic.

PNNL data scientist was invited to give the first big-picture talk about autonomous control systems at the Autonomous Discovery in Science and Engineering Workshop.

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.

A team of PNNL researchers are looking at how to evaluate robustness and accountability, fairness, and transparency of artificial intelligence models used to detect and quantify deceptive content online.