Skip to main navigation Skip to search Skip to main content

Benchmarking conductivity predictions of the advanced electrolyte model (AEM) for aqueous systems

  • Adarsh Dave
  • , Kevin L. Gering
  • , Jared M. Mitchell
  • , Jay Whitacre
  • , Venkatasubramanian Viswanathan

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

High-concentration aqueous electrolytes have shown promise as candidates for a safer battery system. Ionic conductivity is a key property required in high performing electrolytes; the Advanced Electrolyte Model (AEM) has previously shown great accuracy in predicting ionic conductivity in highly-concentrated non-aqueous electrolytes. This work provides extensive experimental data for mixed and highly concentrated aqueous electrolyte systems, rapidly generated via a robotic electrolyte testing apparatus. These data demonstrate exceptional accuracy from AEM in predicting conductivity in aqueous systems, with the accuracy being maintained even in highly-concentrated and mixed-salt regimes. Sensitivity of the model to choice of a key solvation parameter, reference ligand-ion length, is explored. Walden analysis using transport properties predicted by the model for aqueous salts and mixed salt systems is also included, as well as predictions of cation transference number for salts and mixed salts. These predictions are explained in terms of AEM’s underlying chemical physics modeling.

Original languageEnglish
Article number013514
JournalJournal of the Electrochemical Society
Volume167
Issue number1
Early online dateOct 11 2019
DOIs
StatePublished - 2020

Fingerprint

Dive into the research topics of 'Benchmarking conductivity predictions of the advanced electrolyte model (AEM) for aqueous systems'. Together they form a unique fingerprint.

Cite this