2022
DOI: 10.3389/fmats.2022.821817
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Machine Learning Assisted Design of Experiments for Solid State Electrolyte Lithium Aluminum Titanium Phosphate

Abstract: Lithium-ion batteries with solid electrolytes offer safety, higher energy density and higher long-term performance, which are promising alternatives to conventional liquid electrolyte batteries. Lithium aluminum titanium phosphate (LATP) is one potential solid electrolyte candidate due to its high Li-ion conductivity. To evaluate its performance, influences of the experimental factors on the materials design need to be investigated systematically. In this work, a materials design strategy based on machine lear… Show more

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Cited by 10 publications
(2 citation statements)
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“…[ 18 ] Recent studies in this area have generated a great deal of activity in materials design and discovery. [ 19,20 ]…”
Section: Introductionmentioning
confidence: 99%
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“…[ 18 ] Recent studies in this area have generated a great deal of activity in materials design and discovery. [ 19,20 ]…”
Section: Introductionmentioning
confidence: 99%
“…[18] Recent studies in this area have generated a great deal of activity in materials design and discovery. [19,20] Building LMMM property charts with a large number n of structural elements in a mesocell is a difficult task, since the required volume of calculations grows with increasing n according to a power-law, k n , where k is the number of different kinds of rods in the structure. This article aims to solve this formidable problem.…”
mentioning
confidence: 99%