Metilen Mavisinin Sulu Çözeltilerden Diospyros Kaki L. Kabuğuna Adsorpsiyonu: İzoterm ve Yapay Sinir Ağı Modellemesi

Yıl 2025, Cilt: 15 Sayı: 1, 134 - 146, 01.03.2025

Züleyha Reçber

https://doi.org/10.21597/jist.1563250

Öz

Bu çalışmada; metilen mavisi boyar maddesinin sulu çözeltilerden giderimi için Diospyros kaki L. kabuğunun adsorpsiyon potansiyeli incelenmiştir. Temas süresi, pH, adsorbent miktarı, başlangıç boya konsantrasyonu, sıcaklık ve karıştırma hızının boya giderim verimi üzerindeki etkileri araştırılmıştır. Adsorpsiyon 60 dakikada dengeye ulaşmıştır. Adsorbent miktarı arttıkça boya giderim verimi artarken adsorpsiyon kapasitesi düşmüştür. Başlangıç pH’sının sistem performansı üzerinde etkin bir parametre olduğu gözlemlenmiş ve en yüksek boyar madde giderim verimi pH 8’de elde edilmiştir. Adsorpsiyon mekanizmasını belirlemek için Langmuir ve Freundlich izoterm modelleri kullanılmış ve Freundlich izoterm modelinin deneysel verilere daha uygun olduğu tespit edilmiştir. 1 g/L adsorbent miktarı, 250 rpm karıştırma hızı, 100 mg/L başlangıç boyar madde konsantrasyonu, 25 ºC sıcaklık ve 6.68 pH’da 120 dakikalık temas süresinde %85.14’lük giderim verimine ulaşılmıştır. Sulu çözeltiden metilen mavi giderimini tahmin etmek için yapay sinir ağı modeli geliştirilmiştir. Xgboost algoritması ile en küçük ortalama kare hata (MSE) ve en büyük belirleme katsayısı (R2) değerleri sırasıyla 6.99 ve 0.99969 olarak belirlenmiştir. Sonuçlar Diospyros kaki L. kabuğunun metilen mavisi boyar maddesinin sulu çözeltilerden giderimi için etkili bir adsorbent olarak kullanılabileceğini ve yapay sinir ağının makul bir tahmin performansı sağladığını, geliştirilen yapay sinir ağı modeline dayalı simülasyonlar, farklı koşullar altında renk giderim sürecinin davranışını tahmin edebileceğini göstermiştir.

Anahtar Kelimeler

Adsorpsiyon, Boya giderimi, Yapay sinir ağı, Diospyros kaki L

Adsorption of Methylene Blue from Aqueous Solutions onto Diospyros Kaki L. Bark : Isotherm and Artificial Neural Network Modeling

Öz

In this study; adsorption potential of Diospyros kaki L. bark for removal of methylene blue dye from aqueous solutions was investigated. The effects of contact time, pH, adsorbent amount, initial dye concentration, temperature and stirring speed on dye removal efficiency were investigated and optimized. Adsorption reached equilibrium in 60 minute. While dye removal efficiency increased as adsorbent amount increased, adsorption capacity decreased. It was observed that initial pH was an effective parameter on system performance and the highest dye removal efficiency was obtained at pH 10. Langmuir and freundlich isotherm models were used to determine the adsorption mechanism and it was found that the Freundlich model was more suitable for the experimental data. 85.14% removal efficiency was achieved at 1 g/L adsorbent amount, 250 rpm stirring speed, 100 mg/L initial dye concentration, 25 ºC temperature and 6.8 pH in 120 min contact time. An artificial neural network model was developed to predict methylene blue removal from aqueous solution. The smallest mean square error (MSE) and the maximum coefficient of determination (R2) values were determined as 6.99 and 0.99969 by the Xgboost algorithm, respectively. The results showed that Diospyros kaki L. bark can be used as an effective adsorbent for methylene blue removal from aqueous solutions and the artificial neural network provided reasonable prediction performance, and simulations based on the developed artificial neural network model could predict the behavior of the color removal process under different conditions.

Anahtar Kelimeler

Adsorption, Dye removal, Artificial neuron network, Diospyros kaki L.

Kaynakça

• Ahmad A., Rafatullah M., Sulaiman O., Ibrahim M. H., and Hashim R. (2009) Scavenging behaviour of meranti sawdust in the removal of methylene blue from aqueous solution, Journal of Hazardous Materials, 170 (1), 357–365,
• Alam, M. Z., Bari, M. N., & Kawsari, S. (2022). Statistical optimization of Methylene Blue dye removal from a synthetic textile wastewater using indigenous adsorbents. Environmental and Sustainability Indicators, 14, 100176.
• Azari, A., Nabizadeh, R., Mahvi, A. H., Nasseri, S. (2023). Magnetic multi-walled carbon nanotubes-loaded alginate for treatment of industrial dye manufacturing effluent: adsorption modelling and process optimisation by central composite face-central design. International Journal of Environmental Analytical Chemistry, 103(7), 1509-1529.
• Bhatti, H. N., Safa, Y., Yakout, S. M., Shair, O.H., Iqbal, M., Nazir, A. (2020). Efficient removal of dyes using carboxymethyl cellulose/alginate/polyvinyl alcohol/rice husk composite: adsorption/desorption, kinetics and recycling studies. International Journal of Biological Macromolecules, 150, 861-870.
• Bingül, Z. (2021). The use of waste green tea leaves for crystal viyole adsorption: kinetic, equilibrium and thermodynamics studies. Journal of the Institute of Science and Technology, 11(4), 2645-2659.
• Bingul, Z., Adar, E. (2023). Usability of spent Salvia officinalis as a low-cost adsorbent in the removal of toxic dyes: waste assessment and circular economy. International Journal of Environmental Analytical Chemistry, 103(18), 6130-6145.
• Bingul, Z., Gurbuz, H., Aslan, A., Ercisli, S. (2016). Biosorption of zinc (ii) from aqueous solutions by nonliving lichen biomass of xanthoria parietina (l.) th. fr. Environmental Engineering & Management Journal (EEMJ), 15(12).
• Chikri, R., Elhadiri, N., Benchanaa, M., El Maguana, Y. (2020). Efficiency of sawdust as low‐cost adsorbent for dyes removal. Journal of Chemistry, (1), 8813420.
• Çimen Mesutoğlu, Ö. (2024). The use of artificial neural network for modelling adsorption of Congo red onto activated hazelnut shell. Environmental Monitoring and Assessment, 196(7), 630.
• De Farias Silva, C. E., da Gama, B. M. V., da Silva Gonçalves, A. H., Medeiros, J. A., de Souza Abud, A. K. (2020). Basic-dye adsorption in albedo residue: Effect of pH, contact time, temperature, dye concentration, biomass dosage, rotation and ionic strength. Journal of King Saud University-Engineering Sciences, 32(6), 351-359.
• De Gisi, S., Lofrano, G., Grassi, M., Notarnicola, M. (2016). Characteristics and adsorption capacities of low-cost sorbents for wastewater treatment: A review. Sustainable Materials and Technologies, 9, 10-40.
• El-Bindary, M. A., El-Desouky, M. G., El-Bindary, A. A. (2022). Adsorption of industrial dye from aqueous solutions onto thermally treated green adsorbent: A complete batch system evaluation. Journal of Molecular Liquids, 346, 117082.
• Ghaedi, A. M., Vafaei, A. (2017). Applications of artificial neural networks for adsorption removal of dyes from aqueous solution: A review. Advances in Colloid and Interface Science, 245, 20-39.
• Ibrahim, M., Haider, A., Lim, J. W., Mainali, B., Aslam, M., Kumar, M., Shahid, M.K. (2024). Artificial neural network modeling for the prediction, estimation, and treatment of diverse wastewaters: A comprehensive review and future perspective. Chemosphere, 142860.
• İrdemez, Ş., Özyay, G., Torun, F. E., Kul, S., Bingül, Z. (2021). Comparison of bomaplex blue CR-L removal by adsorption using raw and activated pumpkin seed shells. Ecological Chemistry and Engineering S, 29(2), 199-216.
• İrdemez, Ş., Yeşılyurt, D., Ekmekyapar Torun, F. (2022). Investigation of Manganese Ion Removal from Waters Using Sewage Sludge Ash. Iran. J. Chem. Chem. Eng. Research Article Vol, 41(9).
• Javed, A., Islam, M., Al-Ghamdi, Y. O., Iqbal, M., Aljohani, M., Sohni, S., Shah, S. S. A., Khan, S. A. (2024). Synthesis of oxidized carboxymethyl cellulose-chitosan and its composite films with SiC and SiC@ SiO2 nanoparticles for methylene blue dye adsorption. International Journal of Biological Macromolecules, 256, 128363.
• Karlaftis, M. G., Vlahogianni, E. I. (2011). Statistical methods versus neural networks in transportation research: Differences, similarities and some insights. Transportation Research Part C: Emerging Technologies, 19(3), 387-399.
• Kul, S. (2021). Removal of Cu (II) from aqueous solutions using modified sewage sludge ash. International Journal of Environmental Science and Technology, 18(12), 3795-3806.
• Kyzas, G.Z., Bikiaris, D.N., Mitropoulos, A.C. (2017). Chitosan adsorbents for dye removal: a review. Polymer International, 66(12), 1800-1811.
• Li, D., Sun, L., Yang, L., Liu, J., Shi, L., Zhuo, L., Ye T., Wang, S. (2024). Adsorption behavior and mechanism of modified Pinus massoniana pollen microcarriers for extremely efficient and rapid adsorption of cationic methylene blue dye. Journal of Hazardous Materials, 465, 133308.
• Li, Y., Du, Q., Liu, T., Peng, X., Wang, J., Sun, J., Wang, Y., Wu, S., Wang, Z., Xia, Y., Xia, L. (2013). Comparative study of methylene blue dye adsorption onto activated carbon, graphene oxide, and carbon nanotubes. Chemical Engineering Research and Design, 91(2), 361-368.
• Musa, M. A., Chowdhury, S., Biswas, S., Alam, S. N., Parvin, S., Sattar, M. A. (2024). Removal of aqueous methylene blue dye over Vallisneria Natans biosorbent using artificial neural network and statistical response surface methodology analysis. Journal of Molecular Liquids, 393, 123624.
• Qian, J., Shen, M., Wang, P., Wang, C., Li, K., Liu, J., Lu, B., Tian, X. (2017). Perfluorooctane sulfonate adsorption on powder activated carbon: effect of phosphate (P) competition, pH, and temperature. Chemosphere, 182, 215-222.
• Reynel-Ávila, H. E., Aguayo-Villarreal, I. A., Diaz-Muñoz, L. L., Moreno-Pérez, J., Sánchez-Ruiz, F. J., Rojas-Mayorga, C. K., Mendoza-Castillo, D. I., Bonilla-Petriciolet, A. (2022). A review of the modeling of adsorption of organic and inorganic pollutants from water using artificial neural networks. Adsorption Science & Technology, 2022, 9384871.
• Rida, K., Bouraoui, S., Hadnine, S. (2013). Adsorption of methylene blue from aqueous solution by kaolin and zeolite. Applied Clay Science, 83, 99-105.
• Saxena, M., Sharma, N., Saxena, R. (2020). Highly efficient and rapid removal of a toxic dye: adsorption kinetics, isotherm, and mechanism studies on functionalized multiwalled carbon nanotubes. Surfaces and Interfaces, 21, 100639.
• Teğin, İ., Demirel, M. F., Alacabey, İ., Yabalak, E. (2024). Investigation of the effectiveness of waste nut shell–based hydrochars in water treatment: a model study for the adsorption of methylene blue. Biomass Conversion and Biorefinery, 14(9), 10399-10412.
• Türkoğlu, S., Kepekçi, R. A., Keskinkan, O. (2023). Diospyros kaki L. kabukları sulu ekstraktı kullanılarak çinko oksit nanopartiküllerinin yeşil sentezi ve karakterizasyonu. Çukurova Üniversitesi Mühendislik Fakültesi Dergisi, 38(3), 603-611.
• Umesh, A. S., Puttaiahgowda, Y. M., Thottathil, S. (2024). Enhanced adsorption: reviewing the potential of reinforcing polymers and hydrogels with nanomaterials for methylene blue dye removal. Surfaces and Interfaces, 104670.
• Wang, X., Chen, A., Chen, B., Wang, L. (2020). Adsorption of phenol and bisphenol A on river sediments: Effects of particle size, humic acid, pH and temperature. Ecotoxicology and Environmental Safety, 204, 111093.
• Wazir, M. B., Daud, M., Ali, F., Al-Harthi, M. A. (2020). Dendrimer assisted dye-removal: A critical review of adsorption and catalytic degradation for wastewater treatment. Journal of Molecular Liquids, 315, 113775.
• Yildiz, E., Yilmaz, A., Gurbuz, O., Alibas, I. (2024). Effect of drying methods and pre-treatments on bioactive potential of persimmon (Diospyros kaki L.). Journal of Food Measurement and Characterization, 18(3), 2014-2029.