X-Ray Experiments, Machine Learning Could Trim Years Off Battery R&D
An X-ray instrument at Berkeley Lab contributed to a battery study that used an innovative approach to machine learning to speed up the learning curve about a process that shortens the life of fast-charging lithium batteries.
Researchers used Berkeley Lab’s Advanced Light Source, a synchrotron that produces light ranging from the infrared to X-rays for dozens of simultaneous experiments, to perform a chemical imaging technique known as scanning transmission X-ray microscopy, or STXM, at a state-of-the-art ALS beamline dubbed COSMIC.
Researchers also employed “in situ” X-ray diffraction at another synchrotron – SLAC’s Stanford Synchrotron Radiation Lightsource – which attempted to recreate the conditions present in a battery, and additionally provided a many-particle battery model. All three forms of data were combined in a format to help the machine-learning algorithms learn the physics at work in
Science snapshots from Berkeley Lab -- April 1, 2021
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X-Ray Experiments, Machine Learning Could Trim Years Off Battery R&D
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SLAC, MIT, TRI researchers advance machine learning to accelerate battery development; insights on fast-charging
Scientists have made a major advance in harnessing machine learning to accelerate the design for better batteries. Instead of using machine learning just to speed up scientific analysis by looking for patterns in data as typically done the researchers combined it with knowledge gained from experiments and equations guided by physics to discover and explain a process that shortens the lifetimes of fast-charging lithium-ion batteries.
It was the first time this approach known as “scientific machine learning” has been applied to battery cycling, said Will Chueh, an associate professor at Stanford University and investigator with the Department of Energy’s SLAC National Accelerator Laboratory who led the study. He said the results overturn long-held assumptions about how lithium-ion batteries charge and discharge and give researchers a new set of rules for engineerin