Through two U.S. Department of Energy funding calls awarded in 2020, PNNL is partnering with industry and academia to advance battery materials and processes.

PNNL has published a report that sets the foundation for modeling gaps and technical challenges in optimizing hydropower operations for both energy production and water management.

As COVID-19 was limiting in-person contact, halting travel, and creating additional barriers, researchers at PNNL were working to find solutions on how they could still get work done while establishing new safety protocols.

PNNL researchers say that offshore wind energy can add value to the electric grid, beyond just the power it can produce, if locations and strategies are optimized.

PNNL’s longstanding grid and buildings capabilities are driving two projects that test transactive energy concepts on a grand scale and lay the groundwork for a more efficient U.S. energy system.

PNNL researchers have shown an improved binarized neural network can deliver a low-cost and low-energy computation to help the performance of smart devices and the power grid.

PNNL and Microsoft Quantum partner to link quantum circuits to powerful government supercomputers.

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 is one of the collaborating partners on a new grid-scale solar and energy storage installation near the PNNL campus in a project led by Energy Northwest.

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.

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.

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.

A PNNL research team compared two types of pumped storage hydropower (open and closed loop) to identify potential environmental impacts.

Their consistency and predictability makes tidal energy attractive, not only as a source of electricity but, potentially, as a mechanism to provide reliability and resilience to regional or local power grids.