Journal of Environmental Management, Journal Year: 2023, Volume and Issue: 347, P. 119103 - 119103
Published: Sept. 29, 2023
Language: Английский
Journal of Environmental Management, Journal Year: 2023, Volume and Issue: 347, P. 119103 - 119103
Published: Sept. 29, 2023
Language: Английский
Journal of Molecular Liquids, Journal Year: 2019, Volume and Issue: 296, P. 112075 - 112075
Published: Nov. 6, 2019
Language: Английский
Citations
215Separation and Purification Technology, Journal Year: 2021, Volume and Issue: 284, P. 120258 - 120258
Published: Dec. 7, 2021
Language: Английский
Citations
113Chemical Engineering Journal, Journal Year: 2022, Volume and Issue: 454, P. 140082 - 140082
Published: Oct. 30, 2022
Language: Английский
Citations
73Chemical Engineering Journal, Journal Year: 2023, Volume and Issue: 466, P. 143285 - 143285
Published: May 2, 2023
Language: Английский
Citations
70Chemical Engineering Journal, Journal Year: 2023, Volume and Issue: 473, P. 145421 - 145421
Published: Aug. 12, 2023
Language: Английский
Citations
65Diamond and Related Materials, Journal Year: 2023, Volume and Issue: 136, P. 109991 - 109991
Published: May 4, 2023
Language: Английский
Citations
47Desalination and Water Treatment, Journal Year: 2024, Volume and Issue: unknown, P. 100822 - 100822
Published: Oct. 1, 2024
Language: Английский
Citations
29Chemical Engineering Journal, Journal Year: 2024, Volume and Issue: 481, P. 148373 - 148373
Published: Jan. 2, 2024
Language: Английский
Citations
21Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: Jan. 23, 2025
This study focused on simulating the adsorption-based separation of Methylene Blue (MB) dye utilising Oryza sativa straw biomass (OSSB). Three distinct modelling approaches were employed: artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), and response surface methodology (RSM). To evaluate adsorbent's potential, assessments conducted using Fourier-transform infrared spectroscopy (FTIR) scanning electron microscopy (SEM). The evaluation RSM, ANN, ANFIS included quantification R2, mean squared error (MSE), root square (RMSE), absolute (MAE) metrics. regression coefficients from process demonstrated that RSM (R2 = 0.9216), ANN 0.8864), 0.9589) all accurately predicted MB adsorptive removal. However, comparative statistical analysis revealed model exhibited superior accuracy in data-based predictions compared to models. ideal pH for adsorption utilizing OSSB was established as 7. Additionally, favourable outcomes obtained with 60-minute contact durations, 20 mg adsorbent quantities, temperatures 30 °C. pseudo 2nd -order kinetic by confirmed. equilibrium data a fit Langmuir isotherm comparison Freundlich model. thermodynamic parameters, including (∆G -9.1489 kJ/mol), enthalpy change (∆H -1457.2 entropy (∆S -19.03 J mol−1 K−1) indicated onto is exothermic spontaneous under experimental conditions. research effectively showcased potential removal OSSB. generated parameter proved valuable design control process.
Language: Английский
Citations
2International Journal of Biological Macromolecules, Journal Year: 2020, Volume and Issue: 164, P. 694 - 706
Published: July 21, 2020
Language: Английский
Citations
105