PNNL computational biologists, structural biologists, and analytical chemists are using their expertise to safely accelerate the design step of the COVID-19 drug discovery process.
A special issue of the Marine Technology Society Journal, titled “Utilizing Offshore Resources for Renewable Energy Development,” focuses on research and development efforts including those at Pacific Northwest National Laboratory (PNNL).
A research team from Pacific Northwest National Laboratory developed an apparatus that evaluates the performance of high-temperature fluids in hydraulic fracturing for enhanced geothermal systems.
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.
Pacific Northwest National Laboratory researchers developed a graphical processing unit (GPU)-centered quantum computer simulator that can be 10 times faster than any other quantum computer simulator.
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.
PNNL researchers developed two web-based tools to assess and mitigate cyberthreats to utilities—inside and outside their firewalls. Both are low cost and can be used by control room operators who are not cybersecurity experts.
Infusing data science and artificial intelligence into electron microscopy could advance energy storage, quantum information science, and materials design.
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.
Tracking down nefarious users is just one example of work at PNNL’s Center for Advanced Technology Evaluation, a computing proving ground supported by DOE’s Advanced Scientific Computing Research program.
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.
Pacific Northwest National Laboratory researchers used machine learning to explore the largest water clusters database, identifying—with the most accurate neural network—important information about this life-essential molecule.
A new agreement between Pacific Northwest National Laboratory and The University of Texas at El Paso will create research and internship opportunities.
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.
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.