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

PNNL researchers teamed up with SambaNova to enhance artificial intelligence for scientific computing.

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.

PNNL researchers created a model that helps materials scientists not only predict what is, but what could be.

Researchers use machine learning to speed up the analysis of aerosol datasets from mass spectrometry.

Combining advanced powder synthesis with solid state processing allows researchers to streamline oxide dispersion-strengthened steel fabrication.

Quantum simulators help navigate noise on GPU-based HPC systems.

Different sized helium cavities that form after ion irradiation are unevenly distributed in a ductile-phase toughened tungsten composite.

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

IDREAM researchers assess the potential of photon-in/photon-out XFEL techniques to explore early time reaction steps and ultimately improve nuclear waste processing strategies.

PNNL researchers developed a way to produce accurate simulations of complex physical systems using renormalized approximations across multiple scales

Hypergraphs can more faithfully identify important genes in complex immune responses.

The web-based tool, called PLATIPUS, is publicly available and interacts with publications available in the CovidScholar database.

Seeking a deeper understanding of when, where, and why large wildfires occur using explainable artificial intelligence.

New mathematical tools developed at PNNL hold promise to transform the way we operate and defend complex cyber-physical systems, such as the power grid.

Predictive models indicate cells regulate enzyme activity to maintain liquid center.

Contributions from researchers across Pacific Northwest National Laboratory (PNNL) were recently recognized in the preliminary findings of a Secretary of Energy Advisory Board (SEAB) report.