Developing a new scheme to more efficiently solve quantum chemistry problems.

Pacific Northwest National Laboratory researchers developed a new theoretical method for studying highly correlated systems.

Nineteen PNNL-affiliated researchers have been named to Clarivate’s 2024 list of the world's most highly cited researchers.

A new database allows researchers to connect lattice parameters and composition in olivine.

New methodology can evaluate the potential for carbon storage and critical mineral recovery in undercharacterized geological settings.

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.

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

New research investigating water-lean solvents for carbon dioxide capture identifies the unique chemistry possible with their use, may lead to new design principles that move beyond single carbon capture.

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

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

Department of Energy’s Advanced Research Projects Agency-Energy selects PNNL project to help accelerate the development of marine carbon dioxide removal technologies.

Metabolomics analysis revealed differences in metabolome profiles for two distinct modes of fungal wood decay.

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.

Under Secretary for Science and Innovation at the Department of Energy Geri Richmond visited PNNL.

First-of-its-kind genomic catalog lends insight into previously unknown processes at the river’s edge.

Department of Energy, Office of Science Director Asmeret Asefaw Berhe visited PNNL to learn about the Lab’s drive to conduct discovery science, commitment to science for an equitable future, and development of a diversified STEM workforce.

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

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

A new project will produce a database of optimized conditions for efficient, carbon negative recovery of energy-relevant minerals in red mud waste.

HiSVSIM enables large-scale quantum simulations through graph partitioning.