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

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.

PNNL scientists have developed a new mass spectrometry method for in-depth analysis of proteins in individual cells.

Proteomics revealed molecular mechanisms by which the drug Verapamil could prolong beta cell function in early-onset type 1 diabetes patients.

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

Study highlights microbiome’s role in regulating xenobiotic metabolism.

Development of a one-meter path length miniature ion mobility spectrometer based on multilevel structures for lossless ion manipulations.

Researchers characterize protein signatures that indicate Acute Kidney Injury in COVID-19 patients.

Simulations reveal advantages of using new model vs. allometric scaling for risk assessment.

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.

A multi-institutional team has obtained information about nanoscale interactions between the spike protein of the novel coronavirus SARS-CoV-2 and common household inorganic surfaces.

Exposure to polycyclic aromatic hydrocarbons found at Superfund Sites induces enzymes in dose- and time-dependent patterns in mice.

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

Scientists created a benchmark dataset and explored new algorithms to better predict changes in the intensity of North Atlantic tropical cyclones.

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.