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New Technique with Microscope and Algorithm Creates Standardized Index to Measure Lithium Uniformity and Predict Failures in Metal Batteries.
Researchers from the University of California, San Diego, have developed a simple and accurate method to measure the performance of metal lithium batteries. The technique combines a commonly used imaging tool in research, scanning electron microscopy (SEM), with an algorithm that analyzes the results.
Most importantly, according to the scientists, this advancement could lead to the creation of safer and longer-lasting batteries. This would benefit both electric vehicles and large-scale energy storage systems.
The Challenge of Lithium Morphology
One of the biggest obstacles to popularizing metal lithium batteries is the so-called “lithium morphology.” This term describes how lithium deposits on the electrodes during charging and discharging cycles.
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Uniform deposits increase the battery’s lifespan. Irregular deposits can form dendrites—metallic spikes capable of piercing the internal separator, causing short circuits and failures.
This risk has been a barrier to making the use of this technology viable on a large scale.
For a long time, the analysis of uniformity was done solely based on visual observation of the images obtained by microscope.
The problem is that different research groups adopted subjective criteria, hindering comparisons and the collective advancement of discoveries.
A Common Language for Research
The study’s first author, Jenny Nicolas, recalls that in the scientific literature on batteries, there are various terms to describe lithium deposits, such as “robust,” “fuzzy,” “mustache-like,” or “globular.”
According to her, there was a need to create a standardized way to measure and communicate uniformity. This led the team to the Dispersion Index (DI), calculated from SEM images.
This tool provides detailed 2D images of the 3D surface of an electrode. From these, the algorithm transforms visual information into an objective numerical data.
How the Dispersion Index Works
The process begins with capturing the SEM image of the electrode. This image is converted into black and white pixels, where the white ones indicate active lithium deposits.
The algorithm divides the image into sections, counts the white pixels in each one, and calculates the dispersion score.
The closer the index is to zero, the more uniform the lithium distribution. Higher values indicate clustering and lower uniformity.
Tests and Results Obtained
To confirm accuracy, the researchers applied the method to over 2,000 computer-generated images. The scores obtained corresponded to the known data, validating the technique.
Furthermore, they observed that the index increased as the battery degraded. During this process, two signals stood out. The first was the increase in energy required to deposit lithium. The second was marked fluctuations in the DI just before failures, which could serve as an early warning for short circuits.
Accessibility and Impact
A favorable point is that SEM is already standard equipment in battery research, making the method highly accessible.
With it, researchers will have a consistent way to compare results and assess the evolution of a battery over time.
The findings were published in the journal Proceedings of the National Academy of Sciences and could mark a decisive step toward increasing the autonomy and durability of metal lithium batteries, especially in electric vehicles.
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