Three research teams led by PNNL organizers achieve journal publications following the Mathematics Research Communities program.

Delivering an integrated quantum-mechanical and experimental perspective on the effects of both intrinsic and externally applied electric fields at atomic-scale interfaces.

Expanding the nation’s largest wind power plant time series database; helping grid planners navigate a resilient energy future with better data.

Isotopically layered water films and slow heating enable diffusion tracking.

A team combined experiments and theory to predict the collective properties of electrolyte solutions.

The first measurement of the proton diffusion constant at cryogenic temperatures provides insights into the mechanism of proton movement in supercooled water.

PNNL researchers have published their paper, “Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data,” in the Journal of Proteome Research.

The Center for Continuum Computing at PNNL aims to integrate cloud platforms, high-performance computing, and edge devices into a seamless ecosystem that accelerates scientific discovery.

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

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.

Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications.

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

Pasco School District teachers join PNNL for an immersive teaching experience.

Researchers unveil user-friendly software to keep complex projects on budget and on schedule.

Scientists at PNNL were awarded nearly $12 million to better understand pathogens, how they spread, and how to prepare the nation against future outbreaks.

PNNL researchers present challenges and opportunities for fusing graph neural networks with deep reinforcement learning.

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.