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.

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

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

Researchers in the IDREAM Energy Frontier Research Center unearth new defects during gibbsite crystallization using a multi-instrument approach.

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

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

Newly determined energy transfer mechanisms help identify how water releases from and damages irradiated interfaces.

Developing an understanding of how water breaks apart after radiation exposure.

IDREAM researchers use fast force mapping to provide insights into the boehmite interfacial solution structure.

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.

New PNNL research provides the first direct evidence that amorphous intermediates influence subsequent crystallization outcomes using in situ imaging.

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

IDREAM study characterizes chemical species and mechanisms that control aluminum salt and mineral crystallization for nuclear waste retrieval, processing.

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.