Modelling and optimization of copper removal from water using carbon nanotubes with RSM and ANN

Yıl 2024, Cilt: 26 Sayı: 1, 124 - 138, 19.01.2024

Elif Çalgan Elif Ozmetin

https://doi.org/10.25092/baunfbed.1330185

Öz

In this study, it was aimed to remove heavy metal copper from aqueous solutions by using MWCNT-OH, which is a multi-walled carbon nanotube. Modelling and optimization were performed using the Response Surface Method (RSM) and Artificial Neural Networks (ANN). Model equations were derived by both methods. ANOVA analyses were performed with RSM to determine the significance of the parameters on removal efficiency and adsorption capacity. Contour graphs showing the binary parameter interactions were obtained. Optimization was carried out to obtain the maximum removal efficiency and maximum adsorption capacity using both RSM and ANN. Using RSM and ANN, the maximum copper removal efficiencies were obtained at 45.1% and 39.1%, while the maximum adsorption capacities were found to be 16.7 mg/g and 17.12 mg/g, respectively. In addition, test experiments and modelling methods were compared, revealing that the modelling capability of ANN was superior to that of RSM.

Anahtar Kelimeler

Copper, carbon nanotubes, adsorption, response surface methodology, artificial neural networks

Karbon nanotüpler kullanılarak sulardan bakır gideriminin YYY ve YSA ile modelleme ve optimizasyonu

Öz

Bu çalışmada çok duvarlı karbon nanotüplerden olan MWCNT-OH kullanılarak ağır metallerden bakırın sulu çözeltilerden giderimi hedeflenmiştir. Çalışmada modelleme ve optimizasyon için Yanıt Yüzey Yöntemi (YYY) ile Yapay Sinir Ağları (YSA) kullanılmıştır. Her iki yöntemle model denklemleri türetilmiştir. YYY ile ANOVA analizi yapılarak parametrelerin giderim verimi ve adsorpsiyon kapasitesi üzerindeki anlamlılıklarını belirlenmiştir. İkili parametre etkileşimlerinin görüldüğü contour grafikler elde edilmiştir. YYY ve YSA ile maksimum giderim verimi ve maksimum adsorpsiyon kapasitesini elde etmek amacıyla optimizasyon yapılmıştır. RSM ve YSA kullanılarak, maksimum bakır giderim verimleri %45,1 ve %39,1 olarak elde edilirken, maksimum adsorpsiyon kapasiteleri sırasıyla 16,7 mg/g ve 17,12 mg/g olarak bulunmuştur. Ayrıca test deneyleri ile modelleme yöntemleri karşılaştırılmıştır. YSA’nın modelleme kabiliyetinin YYY’ye göre daha iyi olduğu görülmüştür.

Anahtar Kelimeler

Bakır, karbon nanotüpler, adsorpsiyon, yanıt yüzey metodolojisi, yapay sinir ağları

Kaynakça

• Calgan, E., Fonksiyonalize çok duvarlı karbon nanotüpler kullanılarak sulu çözeltilerden metil viyolet ve bakır giderimi, PhD thesis, Balikesir University, Graduate School of Natural and Applied Sciences, Balıkesir, (2023).
• Darweesh M.A., Elgendy M.Y., Ayad M.I., Ahmed A.M., Elsayed N.M.K., Hammad W.A., Adsorption isotherm, kinetic, and optimization studies for copper (II) removal from aqueous solutions by banana leaves and derived activated carbon, South African Journal of Chemical Engineering, 40, 10–20, (2022).
• Gündoğan R., Acemioğlu B., Alma M.H., Copper (II) adsorption from aqueous solution by herbaceous peat, Journal of colloid and interface science, 269, 2, 303–309, (2004).
• Isaac R., Siddiqui S., Adsorption of divalent copper from aqueous solution by magnesium chloride co-doped Cicer arietinum husk biochar: Isotherm, kinetics, thermodynamic studies and response surface methodology, Bioresource Technology Reports, 18, 101004, (2022).
• Bilal M., Shah J.A., Ashfaq T., Gardazi S.M.H., Tahir A.A., Pervez A. et al., Waste biomass adsorbents for copper removal from industrial wastewater-a review ,Journal of hazardous materials, 263, 322–333, (2013).
• Chen Q., Yao Y., Li X., Lu J., Zhou J., Huang Z., Comparison of heavy metal removals from aqueous solutions by chemical precipitation and characteristics of precipitates, Journal of water process engineering, 26, 289–300, (2018).
• Benalia M.C., Youcef L., Bouaziz M.G., Achour S., Menasra H., Removal of heavy metals from industrial wastewater by chemical precipitation: mechanisms and sludge characterization, Arabian Journal for Science and Engineerin Engineering, 47, 5, 5587–5599, (2022).
• Veli S., Pekey B., Removal of copper from aqueous solution by ion exchange resins, Fresenius Environmental Bulletin, 13, (2004).
• Rengaraj S., Kim Y., Joo C.K., Choi K., Yi J., Batch adsorptive removal of copper ions in aqueous solutions by ion exchange resins: 1200H and IRN97H, Korean Journal of Chemical Engineering, 21, 187–194, (2004).
• Menzel K., Barros L., Garcia A., Ruby-Figueroa R., Estay H., Metal sulfide precipitation coupled with membrane filtration process for recovering copper from acid mine drainage, Separation and Purification Technology, 270, 118721, (2021).
• Blöcher C., Dorda J., Mavrov V., Chmiel H., Lazaridis N.K., Matis K.A., Hybrid flotation—membrane filtration process for the removal of heavy metal ions from wastewater, Water Research, 37, 16, 4018–4026, (2003).
• Zouboulis A.I., Lazaridis N.K., Matis K.A., Removal of toxic metal ions from aqueous systems by biosorptive flotation, Journal of Chemical Technology & Biotechnology: International Research in Process, Environmental & Clean Technology, 77, 8, 958–964, (2002).
• Hunsom M., Pruksathorn K., Damronglerd S., Vergnes H., Duverneuil P., Electrochemical treatment of heavy metals (Cu2+, Cr6+, Ni2+) from industrial effluent and modeling of copper reduction, Water research, 39, 4, 610–616, (2005).
• Gomes J.A., Islam K., Islam M.R., Irwin G., Bernazzani P., Cocke D., Utilization of Electrochemical Techniques for Copper Removal, Speciation, and Analysis in Aqueous Systems, ECS Transactions, 28, 18, 59, (2010).
• Yeh R.S., Wang Y.Y., Wan C.C., Removal of Cu2+ EDTA compounds via electrochemical process with coagulation, Water Research, 29, 2, 597–599, (1995).
• Skotta A., Jmiai A., Elhayaoui W., El-Asri A., Tamimi M., Assabbane A., et al. Suspended matter and heavy metals (Cu and Zn) removal from water by coagulation/flocculation process using a new Bio-flocculant: Lepidium sativum, Journal of the Taiwan Institute of Chemical Engineers, 145,104792, (2023).
• Al-Saydeh S.A., El-Naas M.H., Zaidi S.J., Copper removal from industrial wastewater: A comprehensive review, Journal of industrial and engineering chemistry, 56, 35-44, (2017).
• Abbas A., Al-Amer A.M., Laoui T., Al-Marri M.J., Nasser M.S., Khraisheh M., et al. Heavy metal removal from aqueous solution by advanced carbon nanotubes: critical review of adsorption applications, Separation and Purification Technology, 157, 141–161, (2016).
• Wu F-C., Tseng R-L., High adsorption capacity NaOH-activated carbon for dye removal from aqueous solution, Journal of hazardous materials, 152, 3, 1256–1267, (2008).
• Shadbad M.J., Mohebbi A., Soltani A., Mercury (II) removal from aqueous solutions by adsorption on multi-walled carbon nanotubes, Korean Journal of Chemical Engineering, 28, 4, 1029–1034, (2011).
• Li Y-H., Wang S., Wei J., Zhang X., Xu C., Luan Z. et al. Lead adsorption on carbon nanotubes, Chemical physics letters, 357, 3-4, 263-266, (2002).
• Kandah M.I., Meunier J-L., Removal of nickel ions from water by multi-walled carbon nanotubes, Journal of hazardous materials, 146, 283-288, (2007).
• Mubarak N.M., Alicia R.F., Abdullah E.C., Sahu J.N., Haslija A.B.A., Tan J., Statistical optimization and kinetic studies on removal of Zn2+ using functionalized carbon nanotubes and magnetic biochar, Journal of Environmental Chemical Engineering, 1, 3, 486–495, (2013).
• Cendrowski K., Kukułka W., Wierzbicka J., Mijowska E., The river water influence on cationic and anionic dyes collection by nickel foam with carbonized metal-organic frameworks and carbon nanotubes, Journal of Alloys and Compounds, 876, 160093, (2021).
• Ge Y., Li Z., Xiao D., Xiong P., Ye N., Sulfonated multi-walled carbon nanotubes for the removal of copper (II) from aqueous solutions, Journal of Industrial and Engineering Chemistry, 20, 4, 1765–1771, (2014).
• Yu X-Y., Luo T., Zhang Y-X., Jia Y., Zhu B-J., Fu X-C., et al., Adsorption of lead (II) on O2-plasma-oxidized multiwalled carbon nanotubes: thermodynamics, kinetics, and desorption, ACS Applied Materials & Interfaces, 3, 7, 2585–2593, (2011).
• Abdulgader M., Yu Q.J., Zinatizadeh A.A., Williams P., Rahimi Z., Application of response surface methodology (RSM) for process analysis and optimization of milk processing wastewater treatment using multistage flexible fiber biofilm reactor, Journal of Environmental Chemical Engineering, 8, 3, 103797, (2020).
• Ozmetin E., Calgan E., Suzen Y., Korkmaz M., Ozmetin C., Optimisation of Textile Industry Wastewater Treatment Using Bigadic Zeolite (Clinoptilolite) by Response Surface Methodology, Journal Of Envıronmental Protectıon and Ecology, 18, 3, 1127–1136, (2017).
• Himmetoğlu, E. M., Boylu ardıç (Juniperus excelsa) meyvelerinden süperkritik karbondioksit ekstraksiyonu ile ilaç etken maddelerinin özütlenmesi, Master thesis, Gazi University, Graduate School of Natural and Applied Sciences, Ankara, (2020).
• Çalgan E., Ozmetin E., Optimization of hardness removal using response surface methodology from wastewater containing high boron by Bigadic clinoptilolite, Desalination and Water Treatment, 172, 281-291, (2019).
• Onu C.E., Nwabanne J.T., Ohale P.E., Asadu C.O., Comparative analysis of RSM, ANN and ANFIS and the mechanistic modeling in eriochrome black-T dye adsorption using modified clay, South African Journal of Chemical Engineering, 36, 24–42, (2021).
• Çalgan H., Yaman R., İlten E., Demirtaş M., Fırçasız DA motorunun hız kontrolünde PI katsayılarının Pareto tabanlı çok amaçlı optimizasyonu, Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 20, 2, 330–346, (2018).
• Hassen E.B., Asmare A.M., Predictive performance modeling of Habesha brewery wastewater treatment plant using artificial neural networks, Chemical Int, 5, 1, 87, (2019).
• Jana D.K., Bhunia P., Adhikary S. Das., Bej B., Optimization of effluents using artificial neural network and support vector regression in detergent industrial wastewater treatment, Cleaner Chemical Engineering, 3, 100039, (2022).