Imidazole-Based Deep Eutectic Solvents as Efficient Leaching Media for Recycling of Spent Lithium-Ion Batteries

Abstract Accelerated deployment of electric vehicles as a countermeasure against global warming has increased demand for lithium-ion batteries (LIBs). These LIBs contain numerous critical metals, and the importance of recycling technologies for LIBs has grown. In conventional hydrometallurgical LIB recycling, highly concentrated inorganic acids are used in the leaching step, raising environmental concerns associated with the generation of large volumes of acidic wastewater. Here, deep eutectic solvents (DESs) were prepared as alternatives to inorganic acids using a 4,4,4-trifluorobutanedione-functionalized compound as the hydrogen-bond donor and an imidazole-containing compound as the hydrogen-bond acceptor. The prepared DESs were applied as leaching media for spent LIB black mass (i.e., shredded electrode powder), and efficient leaching of Li, Ni, Mn, and Co was achieved. Furthermore, stripping (back-extraction) from the DES phase demonstrated that the recovered metals could be separated into three fractions: a Li solution, a mixed Ni–Mn–Co solution, and a Cu solution. These results suggest that the proposed DES-based separation process can serve as a leaching medium to replace conventional acid leaching in LIB recycling and may contribute to the development of environmentally benign recycling processes.

Authors

Institutions

Publication Details

Journal
ACS Sustainable Resource Management
Published
2026-08-03
DOI
https://doi.org/10.1021/acssusresmgt.6c00266
Primary Topic
Extraction and Separation Processes
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Imidazole-Based Deep Eutectic Solvents as Efficient Leaching Media for Recycling of Spent Lithium-Ion Batteries

Masahiro Goto, Mayu Kamisono, Karin Hamada
ACS Sustainable Resource Management
Extraction and Separation Processes
article

Imidazole-Based Deep Eutectic Solvents as Efficient Leaching Media for Recycling of Spent Lithium-Ion Batteries

Masahiro Goto, Mayu Kamisono, Karin Hamada
article en

Abstract

Abstract Accelerated deployment of electric vehicles as a countermeasure against global warming has increased demand for lithium-ion batteries (LIBs). These LIBs contain numerous critical metals, and the importance of recycling technologies for LIBs has grown. In conventional hydrometallurgical LIB recycling, highly concentrated inorganic acids are used in the leaching step, raising environmental concerns associated with the generation of large volumes of acidic wastewater. Here, deep eutectic solvents (DESs) were prepared as alternatives to inorganic acids using a 4,4,4-trifluorobutanedione-functionalized compound as the hydrogen-bond donor and an imidazole-containing compound as the hydrogen-bond acceptor. The prepared DESs were applied as leaching media for spent LIB black mass (i.e., shredded electrode powder), and efficient leaching of Li, Ni, Mn, and Co was achieved. Furthermore, stripping (back-extraction) from the DES phase demonstrated that the recovered metals could be separated into three fractions: a Li solution, a mixed Ni–Mn–Co solution, and a Cu solution. These results suggest that the proposed DES-based separation process can serve as a leaching medium to replace conventional acid leaching in LIB recycling and may contribute to the development of environmentally benign recycling processes.

ACS Sustainable Resource Management
Kyushu University (JP)
Clean water and sanitation
Openalex Percentile: Top 17%
Extraction and Separation Processes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.