Stanford scientists combine AI and atomic-scale images in pursuit of better batteries Posted on : Feb 23 - 2022

Today’s rechargeable batteries are a wonder, but far from perfect. Eventually, they all wear out, begetting expensive replacements and recycling.

“But what if batteries were indestructible?” asks William Chueh, an associate professor of materials science and engineering at Stanford University and senior author of a new paper detailing a first-of-its-kind analytical approach to building better batteries that could help speed that day. The study appears in the journal Nature Materials.

Chueh, lead author Haitao “Dean” Deng, PhD ’21, and collaborators at Lawrence Berkeley National Laboratory, MIT and other research institutions used artificial intelligence to analyze new kinds of atomic-scale microscopic images to understand exactly why batteries wear out. Eventually, they say, the revelations could lead to batteries that last much longer than today’s. Specifically, they looked at a particular type of lithium-ion batteries based on so-called LFP materials, which could lead to mass-market electric vehicles because it does not use chemicals with constrained supply chains.

Nanofractures

“Think of a battery as a ceramic coffee cup that expands and contracts when it heats up and cools off. Those changes eventually lead to flaws in the ceramic,” Chueh explained. “The materials in a rechargeable battery do the same each time you recharge it and then use up that electricity, leading to failure.”

In the battery, Chueh noted, it is not temperature that causes the fissures, but the mechanical strain the materials have on one another with each charge cycle.

“Unfortunately, we don’t know much about what’s happening at the nanoscale where atoms bond,” Chueh said. “These new high-resolution microscopy techniques allow us to see it and AI helps us understand what is happening. For the first time, we can visualize and measure these forces at the single nanometer scale.”

Chueh said that the performance of any given material is a function of both its chemistry and the physical interaction in the material at the atomistic scale, what he refers to as “chemo-mechanics.” What’s more, the smaller things get and the more diverse the atoms making up the material are, the harder it is to predict how the material will behave. Enter AI. View more