Quantum computing promises leaps in chemistry and materials science, and PNNL is preparing to realize its potential with a collaborative approach.

Christina Lomasney moderates panel on commercialization pathways for emerging artificial intelligence and high-performance computing technologies.

PNNL's E-COMP initiative is helping unleash American energy innovation with advanced theories, models, and software tools to better operate power systems that rely heavily on high-speed power electronic control.

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.

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.

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.

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.

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.

James Ang, John Feo, and Marco Minutoli organized a high performance computing workshop at the prestigious ISC High Performance 2022 conference.

A new perspective article discusses how integrating carbon dioxide capture and conversion in solvents can lead to cheaper and more efficient carbon management systems.

PNNL researchers contributed to the International Conference on Data Science and Advanced Analytics 2021 Best Paper Award-winning publication.