A breakthrough in electron microscopy based on deep learning can automatically visualize and identify areas of interest, helping to speed advances in materials science.

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

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.

From energy-efficient buildings to new manufacturing techniques, researchers at PNNL strive for sustainability and a decarbonization.

Artificial intelligence may help humans and computers work together to monitor materials that could be used to make weapons.

Exploring why some brains are more resilient to the impact of Alzheimer’s disease could lead to improved diagnoses, treatment and prevention.

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.

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.

Road tripping? PNNL’s researchers driving science and technology for clean, efficient and convenient transportation.

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

The PNNL-developed Eclipse VOLTTRON™ software platform continues to support new applications in energy efficiency and clean energy.

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

PNNL will provide technical resources and support to a national coalition of states and cities focused on implementing building performance standards to improve energy efficiency and reduce carbon emissions.

From water purification, to better batteries and tools to foil a cyberattack—a look back at how PNNL helped to invent a brighter and better future over the last year.

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.

Researchers developed two solutions for air-conditioning—a novel, energy-efficient dehumidification system and a technology to detect refrigerant leaks. Both help increase energy-efficiency and reduce costs.

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