Novel assessment of China's cobalt supply chain resilience based on DPSIR model and machine learning DOI
Wei Liu, Lu Chen,

Fanjie Luo

и другие.

Resources Conservation and Recycling, Год журнала: 2024, Номер 215, С. 108107 - 108107

Опубликована: Дек. 27, 2024

Язык: Английский

Facile preparation of MOFs composite nanofibers for the efficient separation of Co(II) from wastewater DOI
Yang Luo,

Xiaolong Zhu,

Guang Yang

и другие.

Journal of Water Process Engineering, Год журнала: 2025, Номер 70, С. 107056 - 107056

Опубликована: Янв. 22, 2025

Язык: Английский

Процитировано

0

Efficient and Green Recovery of Lithium from Spent Lithium-Ion Batteries Based on a Multipotential Field Membrane Process Intensification DOI

Zhengjun Peng,

Qichang Lu,

Zenghu Zhu

и другие.

ACS Sustainable Chemistry & Engineering, Год журнала: 2024, Номер 12(47), С. 17249 - 17262

Опубликована: Ноя. 12, 2024

Advancements in recycling technologies for spent lithium-ion batteries (LIBs) are moving toward environmentally friendly and lower carbon approaches. This study presents a novel method lithium extraction from LIBs based on multipotential field membrane coupling process involving nanofiltration (NF), reverse osmosis (RO), selective electrodialysis (SED). Lithium is extracted the leaching liquor of containing multiple ions by using NF. The combined effects Donnan steric hindrance dielectric exclusion determine retention rates each ion. Divalent such as Ni2+, Co2+, Mn2+ experience stronger repulsion during mass transfer process, resulting rejection all above 98%, which advantageous separation ions, recovery rate NF stage reached 96.02%. Considering characteristics liquor, acidic high chloride, DK selected its superior comprehensive performance three commercial membranes, with particular focus assessing long-term stability tolerance. Finally, coupled RO concentration SED processes to achieve efficient enrichment lithium. 15.23 g/L, Li2CO3 product main content 99.82% prepared, providing an LIBs.

Язык: Английский

Процитировано

1

Novel assessment of China's cobalt supply chain resilience based on DPSIR model and machine learning DOI
Wei Liu, Lu Chen,

Fanjie Luo

и другие.

Resources Conservation and Recycling, Год журнала: 2024, Номер 215, С. 108107 - 108107

Опубликована: Дек. 27, 2024

Язык: Английский

Процитировано

1