Literature DB >> 27250238

Visualization of Steady-State Ionic Concentration Profiles Formed in Electrolytes during Li-Ion Battery Operation and Determination of Mass-Transport Properties by in Situ Magnetic Resonance Imaging.

Sergey A Krachkovskiy1, J David Bazak1, Peter Werhun1, Bruce J Balcom2, Ion C Halalay3, Gillian R Goward1.   

Abstract

Accurate modeling of Li-ion batteries performance, particularly during the transient conditions experienced in automotive applications, requires knowledge of electrolyte transport properties (ionic conductivity κ, salt diffusivity D, and lithium ion transference number t(+)) over a wide range of salt concentrations and temperatures. While specific conductivity data can be easily obtained with modern computerized instrumentation, this is not the case for D and t(+). A combination of NMR and MRI techniques was used to solve the problem. The main advantage of such an approach over classical electrochemical methods is its ability to provide spatially resolved details regarding the chemical and dynamic features of charged species in solution, hence the ability to present a more accurate characterization of processes in an electrolyte under operational conditions. We demonstrate herein data on ion transport properties (D and t(+)) of concentrated LiPF6 solutions in a binary ethylene carbonate (EC)-dimethyl carbonate (DMC) 1:1 v/v solvent mixture, obtained by the proposed technique. The buildup of steady-state (time-invariant) ion concentration profiles during galvanostatic experiments with graphite-lithium metal cells containing the electrolyte was monitored by pure phase-encoding single point imaging MRI. We then derived the salt diffusivity and Li(+) transference number over the salt concentration range 0.78-1.27 M from a pseudo-3D combined PFG-NMR and MRI technique. The results obtained with our novel methodology agree with those obtained by electrochemical methods, but in contrast to them, the concentration dependences of salt diffusivity and Li(+) transference number were obtained simultaneously within the single in situ experiment.

Entities:  

Year:  2016        PMID: 27250238     DOI: 10.1021/jacs.6b04226

Source DB:  PubMed          Journal:  J Am Chem Soc        ISSN: 0002-7863            Impact factor:   15.419


  4 in total

1.  Fish ecotyping based on machine learning and inferred network analysis of chemical and physical properties.

Authors:  Feifei Wei; Kengo Ito; Kenji Sakata; Taiga Asakura; Yasuhiro Date; Jun Kikuchi
Journal:  Sci Rep       Date:  2021-02-12       Impact factor: 4.379

2.  Composite Graphite-Epoxy Electrodes for In Situ Electrochemistry Coupling with High Resolution NMR.

Authors:  Pollyana Ferreira da Silva; Bruna Ferreira Gomes; Carlos Manuel Silva Lobo; Marcelo Carmo; Christina Roth; Luiz Alberto Colnago
Journal:  ACS Omega       Date:  2022-01-31

3.  Rechargeable lithium-ion cell state of charge and defect detection by in-situ inside-out magnetic resonance imaging.

Authors:  Andrew J Ilott; Mohaddese Mohammadi; Christopher M Schauerman; Matthew J Ganter; Alexej Jerschow
Journal:  Nat Commun       Date:  2018-05-03       Impact factor: 14.919

Review 4.  Application of Magnetic Resonance Techniques to the In Situ Characterization of Li-Ion Batteries: A Review.

Authors:  Sergey Krachkovskiy; Michel L Trudeau; Karim Zaghib
Journal:  Materials (Basel)       Date:  2020-04-04       Impact factor: 3.623

  4 in total

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