A New Method for Determining the Concentration of Electrolyte Components in Lithium-Ion Cells, Using Fourier Transform Infrared Spectroscopy and Machine Learning. Issue 2 (1st January 2018)

• Record Type: Journal Article
• Authors: Ellis, L. D.; Buteau, S.; Hames, Samuel G.; Thompson, L. M.; Hall, D. S.; Dahn, J. R.
• Is Part Of: Journal of the Electrochemical Society. Volume 165:Issue 2(2018)
• Page Start: A256
• Page End: A262
• Publication Date: 2018-01-01
• Subjects: Electrolyte Analysis -- Fourier-Transform Infrared Spectroscopy -- Machine Learning; Electrochemistry -- Periodicals; 541.3705
• DOI: 10.1149/2.0861802jes
• Languages: English
• ISSNs: 0013-4651

Abstract

Abstract : A new method is introduced for determining unknown concentrations of major components in typical lithium-ion battery electrolytes. The method is quick, cheap, and accurate. Machine learning techniques are used to match features of the Fourier transform infrared (FTIR) spectrum of an unknown electrolyte to the same features of a database of FTIR spectra with known compositions. With this method, LiPF6 concentrations can be determined with similar accuracy and precision as an inductively coupled plasma optical emission spectrometry (ICP-OES) method. The ratios of organic carbonate solvent species can be determined with more rapidity than gas chromatography (GC). This FTIR method is faster and less expensive than GC and ICP-OES, and has the added benefit of being able to determine LiPF6 concentration and solvent fractions simultaneously. Application of this tool can facilitate electrolyte analysis of aged lithium-ion cells, and will help elucidate mechanisms for cell degradation.