The papers were featured in the security and quantum sessions at the 2023 International Symposium on Computer Architecture.

Researchers created the first open-source database of exotic materials eyed for use in quantum applications.

A combined experimental and theoretical study identified multiple interactions that affect the performance of redox-active metal oxides for potential electrochemical separation and quantum computing applications.

PNNL’s Isabella van Rooyen leads the JOM special section on Additive Manufacturing for High Temperature Energy Systems.

The PNNL-patented ShAPE™ manufacturing process produces high-strength aluminum vehicle parts that lower costs and are more environmentally friendly.

PNNL senior materials scientist Keerti Kappagantula has been named to the 2023 Nominating Committee of ASM International.

A PNNL-developed computational framework accurately predicts the thermomechanical history and microstructure evolution of materials designed using solid phase processing, allowing scientists to custom design metals with desired properties.

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

A new approach broadens the reach of quantum computers to previously challenging systems.

Research published in Journal of Manufacturing Processes demonstrates innovative single-step method to manufacture oxide dispersion strengthened copper materials from powder.

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.

A new testbed facility capable of testing superconducting qubit fidelity in a controlled environment free of stray background radiation will benefit quantum information sciences and the development of quantum computing.

New research shows that compressing quantum circuits decreases noise and increases the accuracy of quantum calculations.

New research from PNNL results in faster and more accurate variational quantum algorithm training.

Tiffany Kaspar’s work has advanced the discovery and understanding of oxide materials, helping develop electronics, quantum computing, and energy production. She strives to communicate her science to the public.

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

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

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