Novel Applications for Synchronized Power Instrumentation seeks to improve electric grid resilience, reliability, security, and affordability.

Battery researchers are ready to work with private companies who want to test their own chemistries in a prismatic cell format.

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

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.

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

Critical minerals could be sourced from industrial waste at scale thanks to an AI-guided separation workflow developed by researchers at PNNL.

PNNL researchers will deploy advanced AI systems to study how to best secure the future electric grid.

PNNL’s Robert Rallo and Nathan Hodas speak to students about the future of AI.

Scientists are optimizing microbes to harvest critical minerals and produce bioproducts using AI and autonomous lab equipment.

An international research team deployed AI-powered computing to solve important chemical structures for energy applications using NVIDIA hardware.

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

Stakeholders convened at PNNL to build a shared understanding of energy storage siting, permitting, safety, and local engagement.

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

Margaret Cheung elected to premier scientific society.

Custom AI research assistant allows users to ask questions and get answers from hundreds of wildfire mitigation plans.

PNNL's Building Energy Model AI is an open-source bot that can help energy modelers save time and money.

Automated liquid handling, combined with data analysis and AI, optimizes microbiological growth conditions at PNNL.

PNNL set to create a practical path for near-term hybrid classical-quantum computers with NVIDIA accelerated computing.

An AI program called AtomAI helped PNNL researchers reveal key design principles for protein interfaces with mineral surfaces.

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.