PNNL has developed a next-generation electrical resistivity tomography system for DOE that uses E4D software and AI-enhanced modeling to produce real-time subsurface images that help guide environmental remediation decisions.
Distributed science is thriving at PNNL, where scientists share data and collaborate with researchers around the world to increase the impact of the work.
A closed-loop workflow brings together digital and physical frameworks to advance high-throughput experimentation on redox-active molecules in flow batteries.
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.
To improve our ability to “see” into the subsurface, scientists need to understand how different mineral surfaces respond to electrical signals at the molecular scale.
In soil, microbes produce and consume methane. Using a technique called pool dilution, researchers can separate the rate of methane production and consumption from the net rate.
