PNNL’s Center for Cloud Computing is addressing challenges in data management and hybrid cloud solutions with industry and academic partnerships.

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

PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.

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.

Researchers investigated how stable nanoparticle suspensions form using facet engineering on hematite nanoparticles, demonstrating that controlling the faceting of nanoparticles can effectively maintain particle dispersity.

The first study modeling the mechanism of hydrated electron formation from aqueous iodide.

PNNL and University of Texas at El Paso leverage partnership and joint appointment program for a laboratory directed research and development project.

Computational chemistry libraries from NWChem, NWChemEX, SPEC, and more are now available on Azure Quantum Elements.

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

Research from PNNL and the University of Washington demonstrates the extension of the MBE for periodic systems and its use to decompose the lattice energies of different ice polymorphs.

Advances in understanding the nature of the chemical bond are featured in this special issue of The Journal of Chemical Physics.

A combined experimental and computational approach showed that the hydration shell of hydroxide has a four-coordinate binding.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

New research makes molecular-level calculations of water faster and easier.

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

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

Structural changes in heavy water occur at different temperatures than in standard water.

The size of the alkali metal within the material influences the crystallization pathway.

PNNL researchers utilized the Peeters-Devreese-Soldatov formulation to improve the accuracy of calculations for quantum chemistry.

A comprehensive understanding of the electronic structure of uranyl ions provides insight into the chemistry of nuclear waste and uranium separation technologies.