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.

Machine learning methods and data science can uncover hidden patterns in nanoparticle synthesis conditions and property outcomes.

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

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.

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

Data-driven autonomous technology to rapidly design and deliver antiviral interventions targeting SARS-CoV-2 to reduce drug discovery timeline and advance bio preparedness capabilities.

The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.

To thwart pathogens, researchers in the epidemiology field of infectious disease (ID) prediction are continuously trying to forecast when, where, and how an ID event will occur.

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

PNNL researchers design an artificial intelligence-guided electron microscope in a Laboratory Directed Research and Development study.

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

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

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.

Researchers achieved the complete assignment of the infrared spectrum of a hydronium-water “magic number” cluster reported in Science in 2004.

A multi-institutional team has developed a deep learning framework to identify novel molecules as drug candidates.

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

New study elucidates the complex relaxation kinetics of supercooled water using a pulsed laser heating technique at previously inaccessible temperatures.

Spectroscopic experiments reveal significant variations in the electronic structures of actinide tetrafluorides despite their nearly identical crystal structures.

A new study connects microscopic molecular-level descriptions with properties of a liquid at the macroscopic scale.