In the search for rare physics events, extremely pure materials are essential. A partnership between PNNL and Ultramet has led to tungsten with low contamination from other elements.

Neural networks techniques enable the efficient capture of electron correlation effects in reduced-dimensionality spaces.

The Center for Continuum Computing at PNNL aims to integrate cloud platforms, high-performance computing, and edge devices into a seamless ecosystem that accelerates scientific discovery.

Erik Lentz and Christian Boutan will research quantum information science-enabled discoveries in high energy physics with these awards.

Developing a new scheme to more efficiently solve quantum chemistry problems.

John VerWey, an advisor in the Mission Alignment group at PNNL, has recently been selected to lead a panel discussion at the inaugural Special Competitive Studies Project (SCSP) AI+ Compute & Connectivity Summit.

The Resilience Analysis Specialty Group is part of the Society for Risk Analysis, the premier international society for risk analysis professionals.

The ARPA-E Energy Innovation Summit brings together researchers, industry leaders, entrepreneurs, and investors to showcase the latest technologies shaping tomorrow’s energy landscape. This year, eight projects led by PNNL were featured.

Lauren Charles, a chief data scientist at PNNL, showcased the vital research coming out of her program at The National Academies Forum workshop in Washington, D.C., January 15–16, 2025.

PNNL's ASSORT model will help airports balance passenger screening and security risks with throughput. It also quantifies risks for different traveler types and optimizes checkpoint operations, improving efficiency while enhancing safety.

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.

PNNL's “co-scientist” serves as a one-stop AI shop for accelerating scientific discovery. By leveraging AI agents, researchers can explore scientific databases, conduct analyses and request step-by-step plans for testing their hypotheses.

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.

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

PNNL chemical engineer Mariefel Olarte shares passion for mentoring students and the next-generation workforce.