PNNL chemist and AI scientist Nancy Washton invited to present on AI literacy at National Science Bowl.

Formal mathematics both reveals what’s inside the black box of AI algorithms and pushes the boundary of what’s possible within math as a discipline.

Chemist Wendy Shaw, a nationally recognized scientific leader, has been chosen to serve as the associate laboratory director for PNNL's Physical and Computational Sciences Directorate.

Researchers can now quantify uncertainty in trained AI models aimed at solving difficult chemistry, biology and materials science problems.

Researchers have created an algorithm that slashes the calculations necessary to prepare and customize data for quantum computing.

Over the next four years, PNNL and University of Arizona will develop open-source computational tools to better identify and characterize the viruses associated with the human microbiome.

Nine national laboratories, including PNNL, bring together over 1,000 scientists for a day to use AI to accelerate scientific discovery.

Scientists are exploring how web search engine technology might also keep the lights on, the water running and the trains moving.

Mini flow cell battery provides the first step toward an AI-driven, robotic energy storage discovery laboratory.

A potential quantum advantage for fluid dynamics simulations from molecular to atmospheric scales with a new formula for success.

A new generation of microelectronics research begins at PNNL.

Federal environmental permitting process to be fast-tracked with AI-powered tools and cloud-supported data analysis.

Scientists are using artificial intelligence and powerful computing to sculpt new molecules in an effort to treat disease.

The search for dark matter includes expertise in radio frequency signal detection, quantum sensing, and high-energy physics at PNNL.

Calculating quantum chemistry quickly allows scientists to refine their understanding of complex chemical systems.

A team of researchers at PNNL is developing a new approach to explore the higher-dimensional shape of cyber systems to identify signatures of adversarial attacks.

The speed and agility of cloud computing opens doors to completing advanced computational chemistry workflows in days instead of months.

Artificial intelligence, high-throughput experimentation, and materials science expertise combine to efficiently develop next-generation energy storage materials.

Three PNNL technologies have been named 2024 R&D 100 Award winners.

Researchers are planning for an electric grid that deploys machine learning to think ahead, plan for the worst, anticipate demand, and meet consumer needs safely and securely.