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.

Three PNNL researchers will receive five continuous years of funding for projects through highly competitive DOE Early Career Research Program awards.

Bylaska and team will aim to make computational design of functional materials more targeted, impactful, and user friendly through this award.

A new approach validates quantum algorithms for low-energy nuclear physics applications

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.

Scott Whalen, a chief scientist in the Applied Materials and Manufacturing group at PNNL, has been named 2023 PNNL Inventor of the Year

A new quantum algorithm speeds up simulations of coupled oscillator dynamics.

As new paradigms in advanced computing take shape, computational chemistry researchers are finding new ways to solve challenging chemistry problems.

The next-generation ShAPE machine has arrived at PNNL, where it will help prove the mettle of the ShAPE extrusion technique. ShAPE 2 is designed to allow researchers to produce larger, more complex extrusions.

In a new approach, quantum flow algorithms are used to simulate many-body systems on quantum computers and effectively describe chemical processes.

Newly developed ultra-low radiation cables reduce background noise for neutrino and dark matter detectors.

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.

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.

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 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.

Multidisciplinary teams from research and industry are brought together using management systems developed by a team of software engineers at PNNL.