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.

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

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.

A series of conference panels recently explored how new and evolving technologies can support emergency managers’ responsibilities.

PNNL Program Development Office Director Karl Mueller explains how the TEC4 project seeks to make advanced chemical computations accessible to all.

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

CACTUS provides AI-powered cheminformatics for autonomous science.

Adam Attarian, a PNNL applied mathematician and data scientist in the Applied Artificial Intelligence Systems group, has been accepted into an Office of the Director of National Intelligence fellowship.

PNNL’s Center for Cloud Computing is addressing challenges in data management and hybrid cloud solutions with industry and academic partnerships.

PNNL’s year in review includes highlights ranging from advancing soil science to understanding Earth systems, expanding electricity transmission, detecting fentanyl, and applying artificial intelligence to aid scientific discovery.

The Testing Risks of AI for National Security Taskforce will address critical safety and security concerns related to artificial intelligence.

A new generation of microelectronics research begins at PNNL.

Sergei Kalinin, a joint appointee at the University of Tennessee, Knoxville and PNNL, and Ji-Guang (Jason) Zhang, a PNNL Lab Fellow, are part of the 2024 class of National Academy of Inventors Fellows.

His expertise in data science and commitment to open science will drive dataset dissemination and advance collaborative global research efforts.

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