In a new approach, quantum flow algorithms are used to simulate many-body systems on quantum computers and effectively describe chemical processes.

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

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.

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.

The Triton Initative discusses special issue publications from the Triton Field Trials on environmental monitoring recommendations for marine energy applications.

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.

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

Triton project coordinator Nicole Loosveldt supports marine energy environmental monitoring technology development projects for marine energy.

This Triton Story discusses the many types of marine energy devices and the Triton Field Trials environmental monitoring research around wave, tidal, and riverine energy devices.

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

Ocean engineer Emma Cotter supports the Triton Initiative's environmental monitoring projects.

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

The Triton Initiative highlights different creative science communications, including photography, writing, and science art, and the impact they have on the project's marine energy research.

Triton highlights research partners in environmental monitoring for marine energy.

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

Triton is piloting research on the interactions of receptors and anthropogenic light associated with marine energy devices.

The Triton Initiative introduces its next generation of projects focused on researching stressor/receptor interactions for marine energy applications.

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