Determining the uncertainty in microstructural parameters extracted from tomographic data12. Issue 3 (11th January 2018)

• Record Type: Journal Article
• Authors: Pietsch, P.; Ebner, M.; Marone, F.; Stampanoni, M.; Wood, V.
• Is Part Of: Sustainable energy & fuels. Volume 2:Issue 3(2018)
• Page Start: 598
• Page End: 605
• Publication Date: 2018-01-11
• Subjects: Renewable energy sources -- Periodicals; Fuel cells -- Periodicals; Electric batteries -- Periodicals; Electrochemistry -- Periodicals; 660.297
• DOI: 10.1039/c7se00498b
• Languages: English
• ISSNs: 2398-4902

Abstract

Abstract : The procedure for binarization of X-ray tomographic data affects the quantitative analysis of microstructural parameters in lithium ion battery electrodes. Abstract : In the past few years, tomography has emerged as an indispensable tool to characterize and quantify the microstructural parameters of porous media, including lithium ion battery electrodes and separators, fuel cell parts, and supercapacitor electrodes, as well as electrolysis diaphragms. However, tomographic data often suffer from low image contrast between the pore space and the solid phase. As a result, data binarization is error-prone, which translates into uncertainties in the calculated parameters, such as porosity, tortuosity, or specific surface area. We systematically investigate this error propagation on a set of seven commercial negative lithium ion battery electrodes imaged with X-ray tomographic microscopy, and find that, for low porosity electrodes, the selection of binarization criteria can lead to uncertainties in the calculated tortuosity exceeding a factor of two. Our analysis shows that Otsu's interclass variance, which can be determined from a simple and computationally cheap analysis of the histogram of gray values, is a good predictive indicator of the expected uncertainty in the microstructural characteristics.