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Consumer Electronics,Technology,Battery

December 09, 2019   •   3 minute read

Building a Better Battery With Machine Learning

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Designing the best molecular building blocks for battery components is like trying to create a recipe for a new kind of cake, when you have billions of potential ingredients. The challenge involves determining which ingredients work best together—or, more simply, produce an edible (or, in the case of batteries, a safe) product. But even with state-of-the-art supercomputers, scientists cannot precisely model the chemical characteristics of every molecule that could prove to be the basis of a next-generation battery material.

Associated Environmental Systems, supports battery development worldwide.  Being able to test coin cells in the lab and then swap out the coin holder for cylindrical holders with a simple click makes scaling a smooth transition.  Click here to see more about AES' innovative solutions.

https://phys.org/news/2019-11-battery-machine.html

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