This study presents an automated method to detect and classify open- and closed-cell mesoscale cellular convection (MCC) using long-term ground-based radar observations.

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.

PNNL’s year in review includes highlights ranging from advancing soil science to understanding Earth systems, expanding electricity transmission, detecting fentanyl, and applying artificial intelligence to aid scientific discovery.

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.

PNNL’s patented Shear Assisted Processing and Extrusion (ShAPE™) technique is an advanced manufacturing technology that enables better-performing materials and components while offering opportunities to reduce costs and energy consumption.

Senior Advisor Isabella van Rooyen shares her journey from child to internationally recognized scientist in nuclear materials and manufacturing.

From energy storage to cybersecurity, this 2023 wrap-up offers a glimpse of PNNL innovations with a seasonal twist.

The Department of Energy’s Vehicle Technologies Office recently issued two awards to researchers at PNNL for their contributions to areas that are crucial for the expansion of electric vehicles.

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

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

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

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

The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.

PNNL will partner with Commonwealth Fusion Systems to develop innovative steel materials for fusion applications under the INFUSE program

Direct visualization of metal atoms during shear deformation has broad applications from battery design to vehicle lightweighting.

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 extrusion process eliminates pre-heating to provide significant energy savings during production of extruded aluminum alloys.

The first-ever simulation of aluminum conductivity offers a recipe for an inexpensive, lightweight alternative to copper.