Unveiling the plating-stripping mechanism in aluminum batteries with imidazolium-based electrolytes: A hierarchical model based on experiments and ab initio simulations

Williams Agyei Appiah*, Anna Stark, Steen Lysgaard, Jonas Busk, Piotr Jankowski, Jin Hyun Chang, Arghya Bhowmik, Bernhard Gollas, Juan Maria Garcia-Lastra*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Aluminum batteries with imidazolium-based electrolytes present a promising avenue toward the post-lithium-ion battery era. A critical bottleneck is the development of reversible aluminum metal anodes, which is hindered by sluggish battery charge–discharge characteristics due to the reversible/irreversible side reactions on the anodic and cathodic sides. The indispensable discernment of the stripping-plating mechanisms at the electrode–electrolyte interface is not well explored due to the complexity of the various reactions occurring at the surface of the aluminum anode. Herein, a high-fidelity physics-based model is coupled with density functional theory to explain the stripping-plating mechanisms that occur on the surface of the aluminum anode at different current densities. Sensitivity analysis is performed on the experimentally validated physics-based model using a machine-learning Gaussian process regression model to identify the most significant parameters for the plating-stripping mechanism of aluminum. The electrodeposition of aluminum is controlled by both diffusion and kinetics and is limited by the kinetics of the electrochemical reactions at a high current density. This work highlights the assurance of combining models at different scales, machine learning algorithms, and experiments to analyze the behavior of complex electrochemical systems.
Original languageEnglish
Article number144995
JournalChemical Engineering Journal
Volume472
Number of pages10
ISSN1385-8947
DOIs
Publication statusPublished - 2023

Keywords

  • Aluminum batteries
  • Ionic liquid electrolytes
  • Physics-based model
  • Sensitivity analysis

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