Simple algorithm uses electron microscopy to predict lithium battery failure risk

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Simple algorithm paired with standard imaging tool could predict failure in lithium metal batteries
(A) Example image showing the total number of white pixels (Awhite) representative of the boundaries between Li particles, and the total number of pixels within each slice Atotal, divided into 16 slices (outlined in red) for the calculation of ID. Each of the 16 slices contains 16 pixels. (B–E) Synthetic SEM images of known PSDs used for ID calculation (30). (B and C) Lognormal particle size distribution, mean particle size of 0.12 and distribution shape parameter of 0.6. (D and E) Normal particle size distribution, mean particle size of 0.1 and distribution shape parameter of 0.025. These values are measured in arbitrary Blender units. Reproduced, Copyright 2016, Elsevier (30). Credit: Proceedings of the National Academy of Sciences (2025). DOI: 10.1073/pnas.2502518122

Researchers at the University of California San Diego have developed a simple yet powerful method to characterize lithium metal battery performance with the help of a widely used imaging tool: scanning electron microscopy. The advance could accelerate the development of safer, longer-lasting and more energy-dense batteries for electric vehicles and grid-scale energy storage.

The work was published in Proceedings of the National Academy of Sciences.

Lithium metal batteries have the potential to store twice as much energy as today’s lithium-ion batteries. That could double the range of electric cars and extend the runtime of laptops and phones. But to realize this potential, researchers must tackle a longstanding challenge: controlling lithium morphology, or how lithium deposits on the electrodes during charging and discharging.

When lithium deposits more uniformly, the battery can achieve longer cycle lifetimes. By contrast, when lithium deposits unevenly, it forms needle-like structures known as dendrites that can pierce a battery’s separator and cause the battery to short-circuit and fail.

Historically, researchers have largely determined the uniformity of lithium deposits by visually assessing microscope images. This practice has led to inconsistent analyses between labs, which has made it difficult to compare results across studies.

“What one battery group may define as uniform might be different from another group’s definition,” said study first author Jenny Nicolas, a materials science and engineering Ph.D. candidate at the UC San Diego Jacobs School of Engineering.

“The battery literature also uses so many different qualitative words to describe lithium morphology—words…



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