A new algorithmic approach breaks apart large quantum problems into smaller subproblems, enabling quantum simulation of more complex systems.

Researchers at PNNL are sharing work grounded in One Health, which connects human, animal, plant, and environmental data to improve situational awareness, early warning, and decision-making.

Assistant Secretary Katie Jereza toured PNNL capabilities that translate laboratory innovation into operational and industry impact.

Separating quantum circuit wiring from molecular data allows researchers to more efficiently perform quantum simulations

The Iowa Nuclear Energy Task Force, chaired by PNNL’s Mark Nutt, evaluated the state’s potential nuclear future including emerging technologies, workforce needs, waste management, and economic growth opportunities.

Global exercise advances nuclear forensic science and investigative capabilities.

PNNL experts trained Armenian engineers in ultrasonic testing, advancing local expertise for nuclear power plant inspections.

Five PNNL innovations earned 2026 R&D 100 Awards for advances in biotechnology, manufacturing, critical minerals, and nuclear security.

A new report highlights a public workshop hosted by the National Academies Forum on Microbial Threats and features PNNL's Lauren Charles and the AI-Driven One Health Security program.

Integrating new functions into a genome-scale model enabled researchers to simulate and experimentally validate viral hijacking pathways.

A suite of new modeling methods gives researchers better tools to predict molecular behavior inside cavities.

A recent article highlighted a PNNL report focused on post-quantum cryptography and electric vehicle charging infrastructure.

Secretary Wright visited PNNL's campus in Richland, Washington, late last year to meet with innovators in chemistry, biology, computing, and more.

Darío Gil, DOE's Undersecretary for Science, makes his inaugural visit to PNNL.

An approach combining multiple theories increases the accuracy of quantum-based simulations without increasing computational demands.

A study by researchers at PNNL assessed the feasibility of using strontium isotope ratios and an existing machine learning–based model to predict and verify a product’s source—in this case, honey.

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

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.

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

Pacific Northwest National Laboratory researchers developed a new theoretical method for studying highly correlated systems.