PNNL computer scientist Ang Li serves as one of the principal investigators for a project selected to receive DOE funding.

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

A discovery from PNNL and Washington State University could help reduce the amount of expensive material needed to treat vehicle exhaust by making the most of every precious atom.

A Q&A with Lauren Charles, veterinarian and PNNL data scientist, on zoonotic diseases and the role biosurveillance plays in mitigating the growing threat to global health.

A new report led by PNNL identifies the top 13 most promising waste- and biomass-derived diesel blendstocks for reducing greenhouse gas emissions, other pollutants, and overall system costs.

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.

When training for chemical and biological threats, in-person exercises and drills can be very limited due to the hazardous nature of the agent.

PNNL’s new Hydrogen Energy Storage Evaluation Tool allows users to examine multiple energy delivery pathways and grid applications to maximize benefits.

PNNL combines AI and cloud computing with damage assessment tool to predict path of wildfires and quickly evaluate the impact of natural disasters, giving first responders an upper hand.

At PNNL, women in engineering tackle some of the world’s most complex problems in environmental science, sustainable energy, and national security.

Svitlana Volkova uses natural language processing and AI to reveal how misinformation and disinformation spread through social media.

Researchers to design their own computer accelerators for faster analysis of large datasets.

OpenCGRA expedites the design-prototype cycle of computer architecture development.

Scientists have created a cybersecurity technology that stops hackers from doing damage by feeding them illusory tidbits of success.

The multi-year project funded by DOE’s High Energy Physics program will focus on using machine learning to prevent power outages.

Risk analysis on the plutonium-fueled power system that supplies electricity to the Mars rover answered the “what if” nuclear safety questions for NASA.

A collaboration among PNNL, Washington State University, and Tsinghua University has led to the discovery of a mechanism behind the decline in performance of an advanced copper-based catalyst.

Marcel Baer is a computational scientist working in PNNL’s Physical Sciences Division with a prominent effort in materials science and physical bioscience.

New computational modeling research provides insights into biological processes and metabolic regulation.