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High Throughput Methodology for Synthesis, Screening, and Optimization of Solid State Lithium Ion Electrolytes

期刊

ACS COMBINATORIAL SCIENCE
卷 13, 期 4, 页码 375-381

出版社

AMER CHEMICAL SOC
DOI: 10.1021/co100075f

关键词

solid state electrolyte; thin film; neural network

资金

  1. Toyota Motor Corporation

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A study of the lithium ion conductor Li3xLa2/3-xTiO3 solid solution and the surrounding composition space was carried out using a high throughput physical vapor deposition system. An optimum total ionic conductivity value of 5.45 x 10(-4)S cm(-1) was obtained for the composition Li0.17La0.29Ti0.54 (Li(3x)La(2/3-x)TiO(3)x = 0.11). This optimum value was calculated using an artificial neural network model based on the empirical data. Due to the large scale of the data set produced and the complexity of synthesis, informatics tools were required to analyze the data. Partition analysis was carried out to determine the synthetic parameters of importance and their threshold values. Multivariate curve resolution and principal component analysis were applied to the diffraction data set. This analysis enabled the construction of phase distribution diagrams, illustrating both the phases obtained and the compositional zones in which they occur. The synthetic technique presented has significant advantages over other thin film and bulk methodologies, in terms of both the compositional range covered and the nature of the materials produced.

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