Fixed-Bed Adsorption of Gallium and Indium from EoL CIGS Leachates on Extractant-Mesoporous Carbon: Integrated Experimental Simulation Approach

Although the exponential increase in photovoltaic installations does contribute to mitigating climate change, it has posed the problem of photovoltaic (PV) residue. As PV panels contain strategic metals, their recovery has become a priority. This paper therefore employs a mesoporous carbon impregnated with P507 extractant as adsorbent to selectively recover gallium and indium from solutions simulating the leachate of end-of-life CIGS (Copper Indium Gallium Selenide) cells in a fixed-bed. The previous batch results obtained in our lab show that both metals can be selectively separated by simply adjusting the initial pH, with large adsorption capacities (44.97 mg/g for gallium and 34.24 mg/g for indium). The obtained breakthrough curves were fitted to the Thomas, Yan, Yoon, and HSDM (Homogeneous Surface Diffusion Model) models using a simulation program developed in Python 3.12 obtaining good results in all cases (R2 > 0.9). The estimated parameters were used to predict the experimental breakthrough curve for a different experiment that had not been used for parameter estimation, being the best predictive results the obtained with the HSDM. This is logical, given that unlike the other three models, it is mechanistic.

Authors

Institutions

Publication Details

Journal
Surfaces
Published
2025-08-22
DOI
https://doi.org/10.3390/surfaces8030059
Primary Topic
Extraction and Separation Processes
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fixed-Bed Adsorption of Gallium and Indium from EoL CIGS Leachates on Extractant-Mesoporous Carbon: Integrated Experimental Simulation Approach

A. Rodrı́guez, A. Adán, Rubén Miranda, Eduardo Díez et al.
Surfaces
Extraction and Separation Processes
article

Fixed-Bed Adsorption of Gallium and Indium from EoL CIGS Leachates on Extractant-Mesoporous Carbon: Integrated Experimental Simulation Approach

A. Rodrı́guez, A. Adán, Rubén Miranda, Eduardo Díez, Víctor Ramos, Arturo Jiménez
article en

Abstract

Although the exponential increase in photovoltaic installations does contribute to mitigating climate change, it has posed the problem of photovoltaic (PV) residue. As PV panels contain strategic metals, their recovery has become a priority. This paper therefore employs a mesoporous carbon impregnated with P507 extractant as adsorbent to selectively recover gallium and indium from solutions simulating the leachate of end-of-life CIGS (Copper Indium Gallium Selenide) cells in a fixed-bed. The previous batch results obtained in our lab show that both metals can be selectively separated by simply adjusting the initial pH, with large adsorption capacities (44.97 mg/g for gallium and 34.24 mg/g for indium). The obtained breakthrough curves were fitted to the Thomas, Yan, Yoon, and HSDM (Homogeneous Surface Diffusion Model) models using a simulation program developed in Python 3.12 obtaining good results in all cases (R2 > 0.9). The estimated parameters were used to predict the experimental breakthrough curve for a different experiment that had not been used for parameter estimation, being the best predictive results the obtained with the HSDM. This is logical, given that unlike the other three models, it is mechanistic.

SurfacesVol. 8(3)
Universidad Complutense de Madrid (ES)
Comunidad de Madrid, European Commission, Consejería de Sanidad, Comunidad de Madrid, Agencia Estatal de Investigación
Openalex Percentile: Top 78%
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.