Synthesis of nanoadsorbent and modeling of dye removal from wastewater by adaptive neuro-fuzzy inference system

In this paper, CuMnO2 nanomaterial was synthesized and its dye removal ability was studied. The characteristics of the synthesized nanomaterial were investigated using Fourier transform infrared, scanning electron microscopy and X-ray diffraction. Adaptive neuro-fuzzy inference system (ANFIS) was applied for modeling of dye removal from colored wastewater. The effect of adsorbent dosage and dye concentration on dye removal was studied. Dye removal process followed pseudo-second-order model and Langmuir isotherm. Furthermore, good agreement between values of predicted and experimental dye removal percentage was observed. The results showed that ANFIS could effectively predict the behavior of the process.