Researchers at PNNL have developed a bacteria testing system called OmniScreen that combines biological and synthetic chemistry with machine learning to hunt down pathogens before they strike.

PNNL’s new Smart Power Grid Simulator, or Smart-PGSim, combines high-performance computing and artificial intelligence to optimize power grid simulations without sacrificing accuracy.

A PNNL engineering team has designed personal protective equipment in support of COVID-19 aid.

The Facility Cybersecurity toolkit, developed by PNNL, is designed for federal facilities to help implement the presidential executive order on cybersecurity, but it is also available for commercial facilities without charge.

Today’s critical infrastructure systems are increasingly vulnerable to attacks that could cripple civil society, according to cybersecurity experts.

PNNL researchers established an Internet of Things Common Operating Environment (IoTCOE) laboratory to explore the risks associated with IoT connectivity to the internet, the energy grid and other critical infrastructures.

PNNL researchers used machine learning to develop a tool for a nonprofit to identify orthopedic implants in X-ray images to improve surgical speed and accuracy.

PNNL team has developed and implemented a generalizable computational framework to study the resilience of the multilayered London Rail Network to the compound threat of intense flooding and a targeted cyberattack.

PNNL recognizes researchers during National Postdoc Appreciation Week.

In a new review, PNNL researchers outline how to convert stranded biomass to sustainable fuel using electrochemical reduction reactions in mini-refineries powered by renewable energy.

The PNNL-developed VOLTTRON™ software platform’s advancement has benefited from a community-driven approach. The technology has been used in buildings nationwide, including most recently on a university campus.

PNNL scientists have created a tool called WatchOwl to collect more than 4 million tweets per day related to the COVID-19 pandemic. The tool analyzes tweets related to interventions like social distancing and movement restrictions.

Embedding the known physics of the system to be controlled in the AI model of the system is data efficient and provides safety guarantees.

A cadre of physical scientists, engineers and computing experts at Pacific Northwest National Laboratory is poised to participate in the launch of three new DOE Office of Science-sponsored quantum information science research centers.

As author of her first publication, PNNL bioinformaticist Isabelle O’Bryon developed the first forensic proteomics method to more quickly detect ricin, a toxin often crudely made in home laboratories that can kill in trace amounts.

Six months into a pandemic that has claimed more than 570,000 lives worldwide, scores of PNNL scientists are engaged in dozens of projects in the fight against COVID-19.

PNNL quantum algorithm theorist and developer Nathan Wiebe is applying ideas from data science and gaming hacks to quantum computing

PNNL study evaluated "tunable" lighting and its effects on sleep at study in a California nursing home. Tunable refers to the ability to adjust LED light output and the warmth or coolness of the light color.

PNNL employs deep learning strategies to advance Model Predictive Control (MPC), a highly promising solution for intelligent building operations.

PNNL researchers and professional staff led discussions ranging from biothreats and climate change to science careers at the 2020 annual meeting of the American Association for the Advancement of Science, held this year in Seattle.