Pyrolyzed mesoporous activated carbon preparation from natural rubber common effluent biosludge: Characterization, isotherms, kinetics, thermodynamics, and ANN modeling during phenol adsorption

被引:10
作者
Roy, Dipanjan [1 ]
Roy, Biplab [1 ]
Manna, Ajay Kumar [1 ]
机构
[1] Natl Inst Technol, Dept Chem Engn, Agartala 799046, Tripura, India
关键词
Rubber sludge; Phenol; Adsorption; Error analysis; ANN modeling; AQUEOUS-SOLUTIONS; CHAR EQUILIBRIUM; METHYLENE-BLUE; SEWAGE-SLUDGE; REMOVAL; WATER; BIOCHAR;
D O I
10.1016/j.gsd.2023.101020
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In the current research, a natural rubber common effluent biosludge (NRCEBS) was utilized for the first time to prepare activated carbon (NRCEAC) as a prominent adsorbent for removing phenol from aqueous solutions. FTIR, XRD, EDS, FESEM, BET, and AAS were used to characterize both NRCEBS and NRCEAC. As per BET results, the prepared adsorbent (NRCEAC) has a specific surface area of 52.52 m2/g. Batch adsorption studies were performed by varying initial concentration (10-60 mg/L), pH (1-12), NRCEAC dosage (2-25 g/L), temperature (20-50 degrees C), and adsorption time (15-300 min). The optimal value of adsorption operating parameters including pH, initial concentration, adsorbent dosage, and contact time were identified to be 6, 10 mg/L, 20 g/L, and 300 min, respectively. The highest phenol removal efficiency was reported to be around 86%. In addition, the maximum adsorption capacity of NRCEAC was estimated to be 1.142 mg/g. The adsorption outcomes were evaluated through the implementation of different kinetic, isotherm, and thermodynamic models. Nonlinear plotting and statistical analysis showed that pseudo-second-order kinetic model and Liu isotherm are the best fitted with the experimental kinetic and equilibrium data. Weber-Morris diffusion model suggested that both intra-particle and external diffusions contribute to the adsorption mech-anism. Findings of thermodynamic study exhibited the endothermic, spontaneous, and random nature of adsorption. Finally, artificial neural network (ANN) modeling has been successfully applied to predict the phenol removal effi-ciency using 5-8-1 arrangement. The findings (R2 = 0.9972 and MSE = 2.131) obtained from ANN model showed good alignment between predicted response with experimental data. The study suggests that the inexpensive, natural bio-adsorbent (NRCEAC) is suitable for phenol remediation in refineries and other associated chemical industries.
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页数:15
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