Scientists at the SLAC National Accelerator Laboratory in the U.S. have developed a machine learning algorithm that can identify and track individual particles within a lithium-ion battery cell. Their findings shed more light on how the batteries lose performance over time, and could challenge previous assumptions of scientists working to develop batteries with longer lifetimes.
An international group of scientists has developed a comprehensive method to track the microscopic processes at work in lithium batteries. Employing a ‘virtual unrolling’ model developed for ancient manuscripts too sensitive to be opened, the group peeked inside the layers of a commercial battery to gain a better understanding of the processes at work and the degradation mechanisms affecting them. Their findings, the group says, could provide a benchmark for battery characterization.
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