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.

Global exercise advances nuclear forensic science and investigative capabilities.

PNNL scientists were among the specialists keeping the crowds safe at the recent FIFA World Cup competition.

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.

Researchers at PNNL have developed an interpretable, lightweight AI model that can easily predict weld microstructure features using only basic machine sensor inputs.

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

PNNL has developed a next-generation electrical resistivity tomography system for DOE that uses E4D software and AI-enhanced modeling to produce real-time subsurface images that help guide environmental remediation decisions.

Through the Air Force Education with Industry program, PNNL is forging powerful connections between research, leadership, and industry.

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.

Researchers at PNNL shared advances in artificial intelligence, cybersecurity, advanced imaging, and more at the Department of Homeland Security Research, Development, Test, and Evaluation Summit.

A team from PNNL contributed several articles to the Domestic Preparedness Journal showcasing recent efforts to explore the emergency management and artificial intelligence research and development landscape.

RemPlex and IAEA convene international leaders to tackle recruitment and retention in complex environmental cleanup efforts.

PNNL staff in the Artificial Intelligence and Data Analytics division were recognized by the TSA’s Innovation Task Force (ITF) for their contributions to cloud capabilities, development strategies, and smart management of cloud resources.

Researchers found that in a future where the Great Plains are 4 to 6 degrees Celsius (°C) warmer as projected in a high-emission scenario, these storms could bring three times more intense rainfall.

In the latest issue of the Domestic Preparedness Journal, Ashley Bradley and Kristin Omberg share how new research is shedding light on the scientific and technological challenges with detecting fentanyl.

A recent study suggests a higher global mean precipitation increase and narrows the uncertainty range.

Research at PNNL and the University of Texas at El Paso are addressing computational challenges of thinking beyond the list and developing bioagent-agnostic signatures to assess threats.

PNNL is supporting the Department of Homeland Security Science and Technology Directorate's Chemical Security Analysis Center in improving capabilities to enhance detection and analysis of chemical threats.

A new report highlights the results of an assessment PNNL conducted of field-portable detection products used by first responders to detect illicit substances like fentanyl in the field.