University of California San Diego researchers have developed a simple scanning electron microscopy (SEM) method capable of characterizing lithium metal battery performance. The method could lead to safer, longer-lasting batteries for electric vehicles and other large scale energy storage needs.
Recently published in Proceedings of the National Academy of Sciences, the work addresses concerns surrounding tradition lithium battery analysis techniques which require visually assessing microscopic images to determine lithium deposit uniformity. These techniques have led to inconsistencies in the past between different labs, making comparing results across studies difficult.
“What one battery group may define as uniform might be different from another group’s definition,” said Jenny Nicolas, a materials science and engineering Ph.D. candidate at UC San Diego. “The battery literature also uses so many different qualitative words to describe lithium morphology — words like chunky, mossy, whisker-like and globular, for example. We saw a need to create a common language to define and measure lithium uniformity.”
To overcome this variability in analysis the team developed a simple algorithm which analyzes how evenly lithium is spread across SEM images. To use the algorithm the team first captures SEM images of battery electrodes which are then converted to black and white pixels, with the white pixels representing the topmost lithium deposits. The algorithm then uses these pixels to calculate a metric called the index of dispersion (ID).
“The index of dispersion is a measure of lithium uniformity,” Nicolas explained. “The closer it is to zero, the more uniform the lithium deposits. A higher value means less uniformity and more clustering of lithium particles in certain areas.”
To validate the algorithm the team tested it on 2,048 synthetic SEM images with known particle size distributions, ultimately finding that the measurements aligned with the known distributions confirming its accuracy.
Given that battery researchers already rely on SEM imaging as part of their studies, the method developed is exceedingly accessible to researchers. Using the method allows battery scientists to calculate the ID from existing data they are already collecting.
“Our tool can be employed as a low-hanging fruit for researchers to take their analysis to the next level by utilizing image analysis to its fullest potential,” Nicolas concluded.