Adsorptive uptake of thymol blue from aqueous medium using calcined snail shells: equilibrium, kinetic, thermodynamic, neuro-fuzzy and DFT studies.
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| Title: | Adsorptive uptake of thymol blue from aqueous medium using calcined snail shells: equilibrium, kinetic, thermodynamic, neuro-fuzzy and DFT studies. |
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| Authors: | Gold, Victoria Faith1 (AUTHOR), Bamisaye, Abayomi1 (AUTHOR) abayomibamisaye@gmail.com, Adesina, Morenike Oluwabunmi1,2,3 (AUTHOR), Adegoke, Kayode Adesina4 (AUTHOR) kwharyourday@gmail.com, Ige, Ayodeji Rapheal5 (AUTHOR), Adeleke, Oluwatobi6 (AUTHOR), Bamidele, Muyideen Olaitan1,7 (AUTHOR), Alli, Yakubu Adekunle8,9 (AUTHOR), Oyebamiji, Abel Kolawole10 (AUTHOR), Ogunlaja, Olumuyiwa O.1,2 (AUTHOR) ogunlaja.olumuyiwa@lcu.edu.ng |
| Source: | Journal of Dispersion Science & Technology. 2025, Vol. 46 Issue 11, p1747-1763. 17p. |
| Subjects: | Snail shells, Machine learning, Thymol, Thermodynamics, Physisorption, Fuzzy neural networks, Environmental remediation, Aqueous solutions |
| Abstract: | The spontaneous discharge of pollutants or toxicants into the ecosystem as a result of various anthropogenic activities is alarming, this necessitates a drastic cheap, and eco-friendly clean-up approach. Out of all the methods, adsorption has proven to be the most effective. The batch adsorptive removal of Thymol Blue (TB) dye from aqueous solutions is examined in this study utilizing calcined snail shells (CalSS). With the aid of SEM, EDS, XRD, and FTIR, the synthesized adsorbent was examined for different physicochemical characteristics. A machine learning model namely Adaptive Neuro-Fuzzy Inference System (ANFIS) was developed to assess the TB adsorption process while taking into account the important adsorption parameters contact time, temperature, pH, adsorbent dosage, then initial adsorbate concentration. Adsorbent pHpzc was also evaluated. EDX and FTIR confirm the formation of CaO with sharp peaks at 547 cm−1 and C–O and O–H are present. SEM and XRD show an irregularly shaped highly crystalline adsorbent material having a typical particle size of 65 ± 2.81 nm and lattice parameter value of 8.611617 Å. The pHpzc value is 11.04, indicating basic surface characteristics. The pH of 3.0, an adsorbent dose of 10 mg and the highest achievable adsorption efficiency were measured to be 98.75% at 20 °C. The findings from the study fit nicely onto Brouser Sotolongo with q BS = 259.4887 mg/g and R2 = 0.9888. The pseudosecond order model (PSOM) recorded the least error value of 0.3336 and R2 = 0.9952. This indicates chemisorption and multilayer adsorption processes. The thermodynamic parameters ΔH° and ΔG° demonstrate the exothermic and spontaneous nature of the adsorption process. The ANFIS model for the TB sequestration was evaluated using relevant statistical metrics, giving Root Mean Square Error (RMSE) value of 1.4644, Mean Absolute Deviation (MAD) value of 0.576, Mean Absolute Error (MAE) value of 1.2974 and Mean Absolute Percentage Error (MAPE) value of 1.5141. This outcome revealed that the ANFIS model and experimental findings are in good agreement. The efficacy of calcined snail shell in removing Thymol Blue dye from aqueous solution was also examined using in-silico technique which was in accordance to the value of the calculated descriptors obtained from the adsorbent as well as the calculated binding affinity. The elimination of TB-polluted wastewater using calcined snail shells is demonstrated in this study to be a successful and environmentally benign process. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | The spontaneous discharge of pollutants or toxicants into the ecosystem as a result of various anthropogenic activities is alarming, this necessitates a drastic cheap, and eco-friendly clean-up approach. Out of all the methods, adsorption has proven to be the most effective. The batch adsorptive removal of Thymol Blue (TB) dye from aqueous solutions is examined in this study utilizing calcined snail shells (CalSS). With the aid of SEM, EDS, XRD, and FTIR, the synthesized adsorbent was examined for different physicochemical characteristics. A machine learning model namely Adaptive Neuro-Fuzzy Inference System (ANFIS) was developed to assess the TB adsorption process while taking into account the important adsorption parameters contact time, temperature, pH, adsorbent dosage, then initial adsorbate concentration. Adsorbent pHpzc was also evaluated. EDX and FTIR confirm the formation of CaO with sharp peaks at 547 cm−1 and C–O and O–H are present. SEM and XRD show an irregularly shaped highly crystalline adsorbent material having a typical particle size of 65 ± 2.81 nm and lattice parameter value of 8.611617 Å. The pHpzc value is 11.04, indicating basic surface characteristics. The pH of 3.0, an adsorbent dose of 10 mg and the highest achievable adsorption efficiency were measured to be 98.75% at 20 °C. The findings from the study fit nicely onto Brouser Sotolongo with q BS = 259.4887 mg/g and R2 = 0.9888. The pseudosecond order model (PSOM) recorded the least error value of 0.3336 and R2 = 0.9952. This indicates chemisorption and multilayer adsorption processes. The thermodynamic parameters ΔH° and ΔG° demonstrate the exothermic and spontaneous nature of the adsorption process. The ANFIS model for the TB sequestration was evaluated using relevant statistical metrics, giving Root Mean Square Error (RMSE) value of 1.4644, Mean Absolute Deviation (MAD) value of 0.576, Mean Absolute Error (MAE) value of 1.2974 and Mean Absolute Percentage Error (MAPE) value of 1.5141. This outcome revealed that the ANFIS model and experimental findings are in good agreement. The efficacy of calcined snail shell in removing Thymol Blue dye from aqueous solution was also examined using in-silico technique which was in accordance to the value of the calculated descriptors obtained from the adsorbent as well as the calculated binding affinity. The elimination of TB-polluted wastewater using calcined snail shells is demonstrated in this study to be a successful and environmentally benign process. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 01932691 |
| DOI: | 10.1080/01932691.2024.2339458 |
