Scientists combined detailed images and coordinated time-series multiomics data to show how protein complexes regulate carbon fixation as light conditions change.

Researchers showed that spiking neural networks can be accurate for regression problems, opening opportunities for efficient neuromorphic computing.

A research team from Pacific Northwest National Laboratory used machine reasoning to schedule scientific workflows while guaranteeing quality of service (QoS).

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

PNNL researchers highlighted advances in AI for scientific discovery at the AI+ Expo, showcasing generative AI, autonomous research workflows, and scalable AI systems supporting energy, security, and national competitiveness.

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

PNNL celebrates its sixth Handshake Early Talent Award, showcasing strong early‑career recruiting. Stories from data scientist Joshua Chong and engineer Alex Smith highlight journeys from different career paths to PNNL.

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.

Now, anyone can easily explore and access data from a nationwide map of data centers, the infrastructure that powers them, and projections of future data center locations.

The Scientific Discovery through Advanced Computing institute will focus on making scientific machine learning accessible to domain scientists.

AI for Good event commemorates 60 years of community engagement, features AI applications, and offers practical AI tools to empower people.

PNNL researchers developed a new computational workflow to study day-to-night gene expression dynamics of cyanobacterium in real time.

This achievement earned DIMPLES a Best Paper award at the ACM International Conference on Supercomputing 2025.

Christina Lomasney moderates panel on commercialization pathways for emerging artificial intelligence and high-performance computing technologies.

More than 25,000 participants from industry, government, academia, and the public attended the event.

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.

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

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

CACTUS provides AI-powered cheminformatics for autonomous science.