Machine learning techniques are accelerating the development of stronger alloys for power plants, which will yield efficiency, cost, and decarbonization benefits.
A research project that brings together mathematicians and atmospheric scientists has developed into a deep collaboration for improving atmospheric models.
With quantum chemistry, researchers led by PNNL computational scientist Simone Raugei are discovering how enzymes such as nitrogenase serve as natural catalysts that efficiently break apart molecular bonds to control energy and matter.
PNNL highlights four researchers whose joint appointments are creating new and diverse opportunities for expanding knowledge and scientific impact across institutions.
PNNL teamed with academia and industry to develop a novel zero-emission methane pyrolysis process that produces both hydrogen and high-value carbon solids suitable for an array of manufacturing applications.
PNNL’s newest solvent captures carbon dioxide from power plants for as little as $47.10 per metric ton, marking a significant milestone in the journey to lower the cost of carbon capture.
Red teaming for CPS, the process of challenging systems, involves a group of cybersecurity experts to emulate end-to-end cyberattacks following a set of realistic tactics, techniques, and procedures.
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.
Using public data from the entire 1,500-square-mile Los Angeles metropolitan area, PNNL researchers reduced the time needed to create a traffic congestion model by an order of magnitude, from hours to minutes.
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.