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.

Data from SOSAT web tool informs site selection and management for the subsurface injection of captured carbon dioxide.

To improve our ability to “see” into the subsurface, scientists need to understand how different mineral surfaces respond to electrical signals at the molecular scale.

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

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

The SHASTA program is doing a deep dive on subsurface hydrogen storage in underground caverns, helping to lay the foundation for a robust hydrogen economy.

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

PNNL research unlocks key findings needed for potential commercial deployment of carbon mineralization technology.

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.

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

A review article led by researcher Jade Holliman explores the different classes of metamaterials, from the underlying fundamental science to potential applications.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

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

Updated flexible software generates and optimizes monitoring programs for detecting potential leaks from geological carbon storage with an enhanced user experience.

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

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