The Center for Continuum Computing at PNNL aims to integrate cloud platforms, high-performance computing, and edge devices into a seamless ecosystem that accelerates scientific discovery.

PNNL’s Center for Cloud Computing is addressing challenges in data management and hybrid cloud solutions with industry and academic partnerships.

A cross-institutional team of scientists developed PeakQC, a new software tool for automated quality control of mass spectrometry data.

In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.

The Department of Energy’s Vehicle Technologies Office recognized Livewire’s outstanding teamwork and technical expertise.

At a one-day summit on PNNL’s Richland campus, scientists and engineers gather to hear from leaders and learn to lead others.

Researchers are leveraging the ocean’s natural processes to advance approaches to remove carbon dioxide from the atmosphere and store it in the ocean.

Reaching net-zero carbon emissions goals requires finding transformative paths to manage carbon in difficult-to-electrify economic sectors.

In soil, microbes produce and consume methane. Using a technique called pool dilution, researchers can separate the rate of methane production and consumption from the net rate.

Scientists have developed a better way to recognize denial-of-service internet attacks, improving detection by 90 percent.

Across the United States, organic carbon concentration imposes a primary control on river sediment respiration, with additional influences from organic matter chemistry.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

PNNL and The University of Texas at El Paso expand their premier partnership to include the Cyber Halo Innovation Research Program.

By mimicking nature, scientists make a breakthrough in breaking down wood.

Researchers have knitted together three large databases of information to help cybersecurity experts detect and prevent attacks.

Newly developed models can help rapidly optimize systems to meet the need for rapidly deployable commercial carbon capture.

Scientists have taken a key step toward harnessing a form of AI known as deep reinforcement learning to protect computer networks.

PNNL scientists carve a path to profit from carbon capture by creating a system that efficiently captures CO2 and converts it into one of the world’s most widely used chemicals: methanol.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

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.