Synergistic ternary deep eutectic solvents: An archetype for sustainable and eco-conscious Li and Co recovery from spent batteries

Hussein K. Amusa, Tarek Lemaoui, Ghaiath Almustafa, Ahmad Darwish, Fawzi Banat, Hassan A. Arafat, Inas M. AlNashef

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

The development of sustainable materials for energy is a critical challenge in the pursuit of a circular economy. This study presents an innovative approach for recycling lithium-ion batteries (LIBs) using a novel, sustainable deep eutectic solvent (DES) composed of glycine, ascorbic acid, and water. This natural, chloride-free ternary DES leverages the biocompatible and eco-friendly properties of its constituents, achieving exceptional leaching efficiency of 99.1 % for lithium and 97.9 % for cobalt under optimized conditions. A multifaceted methodology integrating advanced factorial design, kinetic modeling, and machine learning was employed to refine the process parameters and enhance leaching efficiency. The extraction kinetics were predominantly governed by endothermic surface reactions, characterized by activation energies of 81.5 kJ/mol for Co and 110.9 kJ/mol for Li. An ensemble neural network model accurately predicted the extraction with an R2 > 0.95, demonstrating the robustness of the computational approach. The DES exhibited excellent recyclability over five cycles, thereby emphasizing its potential for practical industrial applications in the field of sustainable materials management. This approach facilitated the selective recovery of high-purity lithium oxalate and cobalt oxalate, underscoring the efficiency and environmental benefits of the process. DFT calculations provided insights into the extraction mechanism, revealing the crucial role of hydrogen bonding and synergistic effects of the DES components. This pioneering study not only advances LIB recycling but also establishes a comprehensive, quantitatively validated framework, paving the way for future innovations in sustainable materials management and supporting global efforts towards a circular economy in energy storage.

Original languageBritish English
Article number156114
JournalChemical Engineering Journal
Volume499
DOIs
StatePublished - 1 Nov 2024

Keywords

  • Circular economy
  • Deep eutectic solvent
  • Density functional theory
  • Kinetic modeling
  • Lithium-ion battery recycling
  • Machine learning

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