Maps of particle cracking and degradation at the surfaces of particles, called “interfacial debonding,” can now serve as a reference tools for knowing ranging degrees of damage in battery electrodes. Researchers at ESRF and SSRL created the ability to scan as many electrode particles in these batteries as possible in a single go, then produce these X-ray images for analysis.
Virginia Tech researchers manufactured the materials and batteries for testing – ranging from the pouch cell batteries in smartphones to the coin cells in watches. These facilities host particles traveling at almost the speed of light, giving off radiation that is used to create images called synchrotron X-rays.
The researchers turned to massive, miles-long facilities called synchrotrons at the European Synchrotron Radiation Facility (ESRF) and the Stanford Synchrotron Radiation Lightsource (SSRL) of SLAC National Laboratory. (European Synchrotron Radiation Facility image/Yang Yang)īut to truly study this in more detail, the team needed to create a new technique altogether existing methods wouldn’t entirely capture damage in battery electrodes. The goal is to understand how cracks in these particles impact battery performance, so that the industry can build more reliable batteries with higher charging capacity. Researchers have created a new technique that scans thousands of particles in the electrode of a battery at once. The researchers’ work to map out damage in lithium-ion batteries started with their finding that degradation in battery particles doesn’t happen at the same time or in the same location some particles fail more quickly than others. Increasing a battery’s capacity often means sacrificing its reliability. It’s hard for a battery to have a high capacity and be reliable at the same time, Zhao says. Electrode damage reduces a battery’s charging capacity.
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These ions interact with particles in electrodes, causing them to crack and degrade over time. But there’s obviously a gap there a lot differs between a single particle at a micron scale and the whole battery at a much larger scale,” said Zhao, whose lab studies the fundamental science of how the mechanical and electrochemical aspects of a battery affect each other.Įvery time that a battery charges, lithium ions travel back and forth between a positive electrode and a negative electrode.
“Most work had been focused on the single particle level and using that analysis to understand the whole battery. But researchers can now analyze them more thoroughly than they could before – and at the various operating conditions that we use commercial batteries in the real world, such as their voltage window and how quickly they charge. Granted, there are actually millions of particles in a battery electrode.
It can automatically scan thousands of particles in a lithium-ion battery electrode at once – all the way down to the atoms that make up the particles themselves – using machine-learning algorithms. The technique, explained in the journals Advanced Energy Materials and the Journal of the Mechanics and Physics of Solids, is essentially an X-ray tool driven by artificial intelligence. “Before, people didn’t have the techniques or theory to understand this problem.” “The creation of knowledge is sometimes more valuable than solving the problem of battery electrode damage,” said Kejie Zhao, an assistant professor of mechanical engineering at Purdue University. In-depth computational models of commercial lithium-ion battery electrodes specifically reveal where damage happens with use.
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