Targeted preparation of graphene-like biochar for efficient tetracycline adsorption: Performance, mechanism, and machine-learning applications

s To address the challenges posed by the high preparation costs and toxicity of chemical reagents involved in graphene production, this research proposes a novel graphene-like biochar development process. Utilising biomass as the raw material, the process uses FeCl 3 and ZnCl 2 as catalysts to promote the formation of graphitised structures in biochar through pyrolysis. Further, the adsorption performance of tetracycline (TC) is investigated to understand the mechanism of action of the graphene-like structure. A range of analytical techniques is employed for this purpose, including SEM-EDS, TEM, BET, AFM, XRD, Raman spectroscopy, FT-IR, and XPS. The adsorption processes were analysed using adsorption kinetics, adsorption isotherms, and thermodynamic models. The experimental data were analysed using machine-learning models, including Gradient Boosting Decision Tree (GBDT), Support Vector Regression (SVR), Random Forest (RF), and Extreme Gradient Boosting (XGB). In addition, feature importance and bidirectional partial dependence analysis were utilised to assess the relative contributions of material preparation conditions, experimental conditions, and material properties to the outcomes of adsorption. The graphene-like biochar prepared from sugarcane bagasse at an optimal pyrolysis temperature of 850°C (850B) exhibited the best adsorption performance for TC, with a maximum adsorption capacity of 1293.97 mg·g −1 . It was found that the primary driving forces for adsorption are π-π interactions and cation-π bonding between the biochar and TC molecules. The results of the machine-learning analysis indicate that the SVR model achieved the highest prediction accuracy for both the training and test sets. In addition, feature importance analysis showed that the π-π ratio and BET surface area were the most important factors influencing the adsorption of TC by biochar. This study on graphene-like biochar contributes to the development of a more resource-efficient and environmentally friendly approach, promoting the comprehensive utilisation of waste and exploring new paths for the coordinated development of agricultural production and environmental protection.

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Publication Details

Journal
Industrial Crops and Products
Published
2026-06-29
DOI
https://doi.org/10.1016/j.indcrop.2026.123780
Primary Topic
Adsorption and biosorption for pollutant removal
Type
article
Field-Weighted Citation Impact
0.00

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article

Targeted preparation of graphene-like biochar for efficient tetracycline adsorption: Performance, mechanism, and machine-learning applications

Qin Shi, Honghui Pan, Z Y Li, Wen Tan et al.
Industrial Crops and Products
Adsorption and biosorption for pollutant removal
article

Targeted preparation of graphene-like biochar for efficient tetracycline adsorption: Performance, mechanism, and machine-learning applications

Qin Shi, Honghui Pan, Z Y Li, Wen Tan, Sinuo Gong, Yuxin Liu, Chuanqi Zhao, Shiyong Huang
article en

Abstract

s To address the challenges posed by the high preparation costs and toxicity of chemical reagents involved in graphene production, this research proposes a novel graphene-like biochar development process. Utilising biomass as the raw material, the process uses FeCl 3 and ZnCl 2 as catalysts to promote the formation of graphitised structures in biochar through pyrolysis. Further, the adsorption performance of tetracycline (TC) is investigated to understand the mechanism of action of the graphene-like structure. A range of analytical techniques is employed for this purpose, including SEM-EDS, TEM, BET, AFM, XRD, Raman spectroscopy, FT-IR, and XPS. The adsorption processes were analysed using adsorption kinetics, adsorption isotherms, and thermodynamic models. The experimental data were analysed using machine-learning models, including Gradient Boosting Decision Tree (GBDT), Support Vector Regression (SVR), Random Forest (RF), and Extreme Gradient Boosting (XGB). In addition, feature importance and bidirectional partial dependence analysis were utilised to assess the relative contributions of material preparation conditions, experimental conditions, and material properties to the outcomes of adsorption. The graphene-like biochar prepared from sugarcane bagasse at an optimal pyrolysis temperature of 850°C (850B) exhibited the best adsorption performance for TC, with a maximum adsorption capacity of 1293.97 mg·g −1 . It was found that the primary driving forces for adsorption are π-π interactions and cation-π bonding between the biochar and TC molecules. The results of the machine-learning analysis indicate that the SVR model achieved the highest prediction accuracy for both the training and test sets. In addition, feature importance analysis showed that the π-π ratio and BET surface area were the most important factors influencing the adsorption of TC by biochar. This study on graphene-like biochar contributes to the development of a more resource-efficient and environmentally friendly approach, promoting the comprehensive utilisation of waste and exploring new paths for the coordinated development of agricultural production and environmental protection.

Industrial Crops and ProductsVol. 249
Minzu University of China (CN), Guangxi Research Institute of Chemical Industry (CN), Shenyang Academy of Environmental Sciences (China) (CN)
Science and Technology Department of Guangxi Zhuang Autonomous
Openalex Percentile: Top 14%
Adsorption and biosorption for pollutant removal
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