مدل‌سازی جذب فلوراید و کاربرد طراحی Box-Behnken و روش شناسی سطح پاسخ در حذف آرسنیک (V) از محلول‌های آبی با استفاده از نانوآلومینا پوشش داده شده بر روی نانوتیوب کربنی چند جداره (MWCNTs)

Objective and Background: Fluoride is an element widely found in the earth crust. Advantages and disadvantages of fluoride in the human body are depended on its concentration. Long-term consumption of drinking water contaminated with arsenic can cause adverse health effects such as skin lesions and cancer in humans. The aim of this study was to study efficiency of nano alumina on multi walled carbon nano tube  for removal As(V) and fluoride from aqueous solution. Materials and Method: In this study, nano-scale crystalline alumina was synthesized on single walled carbon nanotube by sol-gel method for using as a sorbent for solid phase extraction of Fluorine ion and arsenic(V). Response surface methodology based on Box-Behnken was used to assess the effect of independent variables on the response function and prediction of the best response value. In this study, effect of different parameters, such as contact time (10 to 120 min), pH (3-9), adsorbent dosage (0.25-1.5 g/L) and initial concentration of fluoride (2-8 mg/L) on efficiency of process was investigated. The structure of nano-scale alumina on multi walled carbon nano tube was determined by XRD and SEM techniques. Moreover, Freundlich and Langmuir isotherm models were used to calculate equilibrium constant. Results: It was found that by increasing contact time and adsorbent dosage the rate of fluoride removal increased. However, by increasing pH and initial concentration the efficiency of fluoride removal decreased. High value for R2 (0.94) shows that removal of arsenic(V) can be described by this model. The Freundlich isotherm was the best fitted graph for experimental data with R2 more than 0.997. Conclusion: In this study, it was observed that efficiency of arsenic(V) and fluoride  removal was greatly increased by using nano-scale alumina on multi walled carbon nanotubes (MWCNTs).