Experimental and Artificial Neuron Network Insights into the Removal of Organic Dyes from Wastewater Using a Clay/Gum Arabic Nanocomposite †
Abstract
1. Introduction
2. Materials and Methods
2.1. Synthesis of Clay/Gum Arabic Nanocomposite
2.2. Batch Adsorption Experiments
2.3. Kinetic Studies
2.4. Adsorption Isotherm Models
2.5. Artificial Neural Networks (ANN)
2.6. Reusability of CG/NC
2.7. Zeta Potential (ZP)
2.8. Instrumentation
3. Results and Discussion
3.1. Characterization
3.1.1. Fourier Transform Infrared Spectroscopy (FTIR)
3.1.2. Scanning Electron Microscopy (SEM-EDX)
3.1.3. Brunauer–Emmett–Teller (BET) Analysis
3.1.4. X-Ray Powder Diffraction (XRD)
3.2. Artificial Neural Network (ANN)
3.3. Adsorption Studies
3.3.1. Effect of Dosage of CG/MC
3.3.2. Effect of pH
3.3.3. Zeta Potential
3.3.4. Effect of Contact Time
3.3.5. Effect of Initial Concentration
3.3.6. Effect of Temperature
3.4. Optimizing the ANN Model
3.5. Thermodynamic Factors
3.6. Adsorption Isotherm Models
3.6.1. Langmuir Isotherm Model
3.6.2. Freundlich Isotherm Model
3.6.3. Temkin Isotherm Model
Langmuir Isotherm | |||
qmax (mg/g) | KL (L/g) | R2 | |
MB | 66.7 | 0.159 | 0.991 |
CV | 52.9 | 0.298 | 0.981 |
Freundlich Isotherm | |||
N | Kf (mg/g)/(mg/L) | R2 | |
MB | 1.89 | 10.1 | 0.975 |
CV | 2.76 | 16.5 | 0.880 |
Temkin Isotherm | |||
A(L/g) | B | R2 | |
MB | 2.5 | 12.08 | 0.929 |
CV | 2.6 | 28.55 | 0.975 |
3.7. Results of the Kinetic Studies
3.7.1. The Pseudo-First-Order
3.7.2. The Pseudo-Second-Order
3.7.3. The Intra-Particle Diffusion Model
Pseudo-First-Order | |||
qe (mg/g) | k1 (min−1) | R2 | |
MB | 5.694 | 0.000137 | 0.701 |
CV | 4.028 | 0.00035 | 0.323 |
Pseudo-second-order | |||
qe (mg/g) | k2 (mg/g.min) | R2 | |
MB | 5.694 | 1.1876 | 0.997 |
CV | 4.028 | 1.9537 | 0.999 |
Intra-particle diffusion | |||
kid (mg/g.min) | I | R2 | |
MB | 6.228 | 39.725 | 0.671 |
CV | 4.111 | 12.827 | 0.511 |
Elovich | |||
α | β | R2 | |
MB | 3.40 × 1029 | 10.98 | 0.704 |
CV | 3.16 × 106 | 5.89 | 0.849 |
3.7.4. The Elovich Model
3.8. Results of the CG/NC Reusability
3.9. Comparison with Other Adsorbents
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Sample | Surface Area (m2/g) |
---|---|
Clay | 14.34 |
Gum arabic | 0.3835 |
CG/NC | 46.91 |
Initial Concentration (mg/L) | Dosage CG/NC (g) | pH | Contact Time (min) | Temperature (°C) | R (%) Predicted | R (%) Experimentally | |
---|---|---|---|---|---|---|---|
MB | 50.00 | 0.30 | 7.00 | 7.00 | 24.00 | 99.15 | 97.31 |
CV | 47.90 | 0.29 | 7.00 | 3.80 | 50.00 | 99.00 | 96.40 |
MB | |||
T, K | ΔG° (kJ/mol) | ΔS° (J/mol) | ΔH° (kJ/mol) |
298 | −3.991 | ||
308 | −4.356 | 88.01 | 13.13 |
318 | −5.266 | ||
328 | −5.631 | ||
CV | |||
T, K | ΔG° (kJ/mol) | ΔS° (J/mol) | ΔH° (kJ/mol) |
298 | −2.288 | ||
308 | −2.187 | 26.51 | −3.50 |
318 | −2.191 | ||
328 | −2.150 |
Adsorbent | Adsorbate | Isotherm Model | Optimum pH | Kinetic Model | Enthalpy | qmax (mg/g) | Adsorbent Mass (g L−1) | Ref. |
---|---|---|---|---|---|---|---|---|
(RT) | MB | Langmuir | 6–7 | Second order | - | 147 | 12.5 | [47] |
(Fe3O4/Mt) | MB | Langmuir | 7.37 | Second order | - | 106.38 | 12.5 | [11] |
(IRKC) | MB | Langmuir-Freundlich | 8 | First order | - | 240.4 | 10.0 | [38] |
PANI-NiFe2O4 | MB | Langmuir | 9 | Second order | - | 6.65 | 80.0 | [10] |
(WHS) | MB | Langmuir | 7 | Second order | endothermic | 21.50 | 20.0 | [6] |
(LCF) | CV | Langmuir-Freundlich | 7 | First order | exothermic | 34.12 | 5.0 | [48] |
Khulays natural bentonite | CV | Langmuir-Freundlich | 5.3 | Second order | endothermic | 263 | 5.0 | [49] |
(NAJL) | CV | Langmuir | 9 | First order | exothermic | 315.2 | 1.0 | [18] |
(OLP) | CV | Langmuir | 7.5 | Second order | - | 181.1 | 4.0 | [50] |
(AS) | CV | Langmuir | 6 | Second order | endothermic | 12.2 | 10.0 | [17] |
CG/NC | MB | Langmuir | 7 | Second order | endothermic | 66.7 | 4.0 | this study |
CG/NC | CV | Langmuir | 7 | Second order | exothermic | 52.9 | 6.0 | this study |
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Alqahtani, M.F.; Ali, I.H.; Siddeeg, S.M.; Maiz, F.; Eltahir, S.B.; Alarfaji, S.S. Experimental and Artificial Neuron Network Insights into the Removal of Organic Dyes from Wastewater Using a Clay/Gum Arabic Nanocomposite. Nanomaterials 2025, 15, 857. https://doi.org/10.3390/nano15110857
Alqahtani MF, Ali IH, Siddeeg SM, Maiz F, Eltahir SB, Alarfaji SS. Experimental and Artificial Neuron Network Insights into the Removal of Organic Dyes from Wastewater Using a Clay/Gum Arabic Nanocomposite. Nanomaterials. 2025; 15(11):857. https://doi.org/10.3390/nano15110857
Chicago/Turabian StyleAlqahtani, Malak F., Ismat H. Ali, Saifeldin M. Siddeeg, Fethi Maiz, Sawsan B. Eltahir, and Saleh S. Alarfaji. 2025. "Experimental and Artificial Neuron Network Insights into the Removal of Organic Dyes from Wastewater Using a Clay/Gum Arabic Nanocomposite" Nanomaterials 15, no. 11: 857. https://doi.org/10.3390/nano15110857
APA StyleAlqahtani, M. F., Ali, I. H., Siddeeg, S. M., Maiz, F., Eltahir, S. B., & Alarfaji, S. S. (2025). Experimental and Artificial Neuron Network Insights into the Removal of Organic Dyes from Wastewater Using a Clay/Gum Arabic Nanocomposite. Nanomaterials, 15(11), 857. https://doi.org/10.3390/nano15110857