Scientists provide a guide for the rational application of continuum descriptions of fluid flows based on interfacial chemistry.

This achievement earned DIMPLES a Best Paper award at the ACM International Conference on Supercomputing 2025.

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.

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

PNNL will engage with transmission planners and other regional partners through technical assistance and listening sessions with the goal of exploring opportunities to integrate equity into transmission planning.

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.

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

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.

ExaGO, a power grid simulation and optimization platform developed at PNNL is the first of its kind to run on Frontier.