Günlük Hayatta Kullanılan Bazı Bitkilerin Biyosorbent Kapasitelerinin İncelenmesi ve Optimizasyonu

Yıl 2024, Cilt: 36 Sayı: 1, 49 - 60, 28.03.2024

Sibel Arslan , Nurşah Kütük

https://doi.org/10.35234/fumbd.1359709

Öz

Bu çalışmada, biyosorpsiyon ile suyun arıtılmasında kullanılmak üzere günlük hayatta baharat olarak kullanılan ve içecek olarak tüketilen adaçayı, papatya ve tarhun yaprakları farklı biyosorbentler olarak ele alınmıştır. Aynı zamanda, başlangıç boya konsantrasyonu (10-200 mg/L), sıcaklık (20-50 ⁰C) ve temas süresi (0-120 dk) parametrelerinin biyosorpsiyon kapasitesi üzerindeki etkileri araştırılmıştır. Biyosorpsiyon süreçlerinde Freundlich izotermi ve yalancı ikinci mertebe (Pseudo Second Order, PSO) reaksiyon kinetiğinin takip edildiği belirlenmiştir. Çalışmada ayrıca süreç, çok ağaçlı evrimsel hesaplama tabanlı otomatik programlama (Automatic Programming, AP) yöntemleri kullanılarak modellenmiştir. Yöntemler, başlangıç boya konsantrasyonu, sıcaklık ve temas süresini değişken olarak kullandılar. Simülasyon sonuçlarına göre bu yöntemler süreçlerin doğrusal olmayan matematiksel modellerini her bir biyosorbent için 0.99’a varan R^2 değerleri ile elde etmişlerdir. Biyosorpsiyon kapasitesini doğru bir şekilde tahmin etmek için en doğru modelleri sağlayan bu çalışma, deneysel ve AP yöntemleri ile su arıtımı alanına önemli bir katkı sağlayacaktır.

Anahtar Kelimeler

Biyosorbent, bitki, boya, otomatik programlama yöntemleri, genetik programlama

Investigation and Optimization of Biosorbent Capacities of Some Plants Used in Daily Life

Öz

In this study, sage, chamomile, and tarragon leaves, which are used as spices and consumed as beverages in daily life, were considered as different biosorbents that can be used in water purification by biosorption. At the same time, the effects of the parameters of initial dye concentration (10-200 mg/L), temperature (20-50 ⁰C) and contact time (0-120 min) on biosorption capacity were investigated. The biosorption processes were found to follow Freundlich isotherm and pseudo-second order (PSO) reaction kinetics. In the study, the process was also modeled using multi-tree evolutionary computation based automatic programming (AP) methods. The methods used initial dye concentration, temperature, and contact time as variables. According to the simulation results, these methods obtained nonlinear mathematical models of the processes with R^2 values as high as 0.99 for each biosorbent. By providing the most accurate models to accurately predict biosorption capacity, this study will make a significant contribution to the field of water treatment using experimental and AP methods.

Anahtar Kelimeler

Biosorbent, plant, dye, automatic programming methods, genetic programming

Kaynakça

• Zafar, L., Khan, A., Kamran, U., Park, S. J., Bhatti, H. N. (2022). Eucalyptus (camaldulensis) bark-based composites for efficient Basic Blue 41 dye biosorption from aqueous stream: Kinetics, isothermal, and thermodynamic studies. Surfaces and Interfaces, 31, 101897.
• Nielsen, B. V., Maneein, S., Anghan, J. D., Anghan, R. M., Al Farid, M. M., Milledge, J. J. (2022). Biosorption potential of Sargassum for removal of aqueous dye solutions. Applied sciences, 12(9), 4173.
• Azari, A., Noorisepehr, M., Dehghanifard, E., Karimyan, K., Hashemi, S. Y., Kalhori, E. M., Norouzi, R., Agarwal, S., Gupta, V. K. (2019). Experimental design, modeling and mechanism of cationic dyes biosorption on to magnetic chitosan-lutaraldehyde composite. International journal of biological macromolecules, 131, 633-645.
• Bouzikri, S., Ouasfi, N., Benzidia, N., Salhi, A., Bakkas, S., Khamliche, L. (2020). Marine alga “Bifurcaria bifurcata”: biosorption of Reactive Blue 19 and methylene blue from aqueous solutions. Environmental Science and Pollution Research, 27, 33636-33648.
• Shukor, H., Yaser, A. Z., Shoparwe, N. F., Mohd Zaini Makhtar, M., Mokhtar, N. (2022). Biosorption study of methylene blue (MB) and brilliant red remazol (BRR) by Coconut Dregs. International Journal of Chemical Engineering, 2022, 1-11.
• Hevira, L., Zilfa, Rahmayeni, Ighalo, J. O., Zein, R. (2020). Biosorption of indigo carmine from aqueous solution by Terminalia catappa shell. Journal of Environmental Chemical Engineering, 8(5), 104290.
• El Amri, R., Elkacmi, R., & Boudouch, O. (2023). Removal of Methyl Orange from Water Using Microalgae: Effect of Operating Parameters, Equilibrium, Kinetic and Thermodynamic Studies. Chemistry Africa, 1-12.
• Kazemi, M., & Barati, R. (2022). Application of dimensional analysis and multi-gene genetic programming to predict the performance of tunnel boring machines. Applied Soft Computing, 124, 108997.
• Hale, W. T., Safikou, E., & Bollas, G. M. (2022). Inference of faults through symbolic regression of system data. Computers & Chemical Engineering, 157, 107619.
• Boudardara, F., & GÖRKEMLİ, B., (2020). Solving artificial ant problem using two artificial bee colony programming versions. Applied Intelligence, vol.50, no.11, 3695-3717.
• Sattar, M., Majid, A., Kausar, N., Bilal, M., & Kashif, M. (2022). Lung cancer prediction using multi-gene genetic programming by selecting automatic features from amino acid sequences. Computational Biology and Chemistry, 98, 107638.
• Arslan, S., & Koca, K., (2023). Investigating the best automatic programming method in predicting the aerodynamic characteristics of wind turbine blade. Engineering Applications of Artificial Intelligence, vol.123, 106210-106225.
• Arslan, S., & Ozturk , C., (2019). Multi Hive Artificial Bee Colony Programming for high dimensional symbolic regression with feature selection. Applied Soft Computing, vol.78, 515-527.
• Nguyen, Q. H., Ly, H. B., Ho, L. S., Al-Ansari, N., Le, H. V., Tran, V. Q., ... & Pham, B. T. (2021). Influence of data splitting on performance of machine learning models in prediction of shear strength of soil. Mathematical Problems in Engineering, 2021, 1-15.
• Rápó, E., Aradi, L. E., Szabó, Á., Posta, K., Szép, R., & Tonk, S. (2020). Adsorption of remazol brilliant violet-5R textile dye from aqueous solutions by using eggshell waste biosorbent. Scientific reports, 10(1), 8385.
• Holliday, M. C., Parsons, D. R., & Zein, S. H. (2022). Agricultural pea waste as a low-cost pollutant biosorbent for methylene blue removal: adsorption kinetics, isotherm and thermodynamic studies. Biomass Conversion and Biorefinery, 1-15.
• Shahab, M. R., Yaseen, H. M., Manzoor, Q., Saleem, A., Sajid, A., Malik, Q. M., & Ahmed, S. (2023). Adsorption of methyl orange and chromium (VI) using Momordica charantia L. leaves: a dual functional material for environmental remediation. Journal of the Iranian Chemical Society, 20(3), 577-590.
• Rambabu, K., Bharath, G., Banat, F., Show, P. L. (2020). Biosorption performance of date palm empty fruit bunch wastes for toxic hexavalent chromium removal. Environmental research, 187, 109694.
• Tran, H. N., You, S. J., & Chao, H. P. (2016). Thermodynamic parameters of cadmium adsorption onto orange peel calculated from various methods: A comparison study. Journal of Environmental Chemical Engineering, 4(3), 2671-2682.
• Sah, M. K., Edbey, K., EL-Hashani, A., Almshety, S., Mauro, L., Alomar, T. S., AlMasoud N., Bhattarai, A. (2022). Exploring the biosorption of methylene blue dye onto agricultural products: A critical review. Separations, 9(9), 256.
• Dall’Agnol, P., Libardi, N., da Silva, E. C., da Costa, R. H. R. (2022). Biosorption of Phosphorus Using Alginate-Like Exopolymers: investigation of removal mechanism, kinetic and thermodynamic properties. Journal of Polymers and the Environment, 1-12.
• Zaghloul, A., Benhiti, R., Ichou, A. A., Carja, G., Soudani, A., Zerbet, M., ... & Chiban, M. (2021). Characterization and application of MgAl layered double hydroxide for methyl orange removal from aqueous solution. Materials Today: Proceedings, 37, 3793-3797.
• Robati, D., Mirza, B., Rajabi, M., Moradi, O., Tyagi, I., Agarwal, S., & Gupta, V. K. (2016). Removal of hazardous dyes-BR 12 and methyl orange using graphene oxide as an adsorbent from aqueous phase. Chemical Engineering Journal, 284, 687-697.
• Piepho, H. P. (2019). A coefficient of determination (R2) for generalized linear mixed models. Biometrical Journal, 61(4), 860-872.
• Lee, D. K., In, J., & Lee, S. (2015). Standard deviation and standard error of the mean. Korean journal of anesthesiology, 68(3), 220-223.
• Arslan, S., & Kütük, N., (2023). Symbolic regression with feature selection of dye biosorption from an aqueous solution using pumpkin seed husk using evolutionary computation-based automatic programming methods. Expert Systems with Applications, vol.231, 120676.