Raw experimental data and viscosity modeling for selective recovery of Li, Co, and Ni from spent NCA cathodes using H₃PO₄–ChCl deep eutectic solvent and WPI/nanocarbon membranes

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Authors: Paul Afreh, Zhiqin Qin, Lizhen Gao
Cited by: 0

Abstract

This dataset contains the raw experimental data and supporting modeling used in the study on the selective recovery of lithium, cobalt, and nickel from spent NCA cathode black mass using a phosphoric acid–choline chloride deep eutectic solvent (H₃PO₄–ChCl DES) integrated with WPI/nanocarbon composite membranes. The deposited files provide the underlying numerical data for leaching optimization, membrane separation, elemental balance, membrane desorption, solvent recycling, solvent reuse calculations, and site-specific binding energies, together with a dedicated viscosity-modeling dataset for the ChCl:H₃PO₄ (1:1) solvent system. The raw data file includes feed-concentration effects, a full factorial CCD matrix, orthogonal leaching experiments, elemental balance results, membrane regeneration by 0.5 M HCl, H₃PO₄–ChCl solvent recycling performance, cycle-wise PCho-DES reuse calculations, and DFT-derived binding energies for Li⁺, Co²⁺, and Ni²⁺. The viscosity-modeling file provides the Vogel–Fulcher–Tammann (VFT) framework used to describe the temperature dependence of solvent viscosity, together with temperature-resolved viscosity and metal-leaching data showing that viscosity decreased from 1189 mPa·s at 30 °C to 61 mPa·s at 90 °C, accompanied by markedly improved Li, Co, and Ni extraction. Keywords Spent lithium-ion batteries; NCA cathode; deep eutectic solvent; choline chloride; phosphoric acid; membrane separation; whey protein isolate; carbon nanotubes; carbon nano-onions; viscosity modeling; VFT equation; leaching; cobalt; nickel; lithium; solvent recycling;

Fields of Study & Subjects

Extraction and Separation Processes Ionic liquids properties and applications Recycling and Waste Management Techniques

Publication details

Journal / source
Mendeley Data
Publication date
16 March 2026
Language
EN
Document type
Dataset