Led by interns from multiple DOE programs, a newly expanded dataset allows researchers to use easy-to-obtain measurements to determine the elemental composition of a promising carbon storage mineral.
In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.
PNNL researchers earned five Papers of Note, 17 Superior Papers, and one poster award for their environmental remediation, radioactive waste, and nuclear energy-related presentations.
PNNL has developed a decision tool that provides contractors and installers with the information they need to properly select and install cold climate heat pumps, which are a key technology for achieving decarbonization.
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.