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

机译:自适应神经模糊推理系统合成纳米吸附剂并建立废水脱色模型

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摘要

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.
机译:本文合成了CuMnO2纳米材料,研究了其对染料的去除能力。利用傅里叶变换红外,扫描电子显微镜和X射线衍射研究了合成的纳米材料的特性。自适应神经模糊推理系统(ANFIS)用于建模从有色废水中去除染料。研究了吸附剂用量和染料浓度对染料去除的影响。染料去除过程遵循伪二级模型和Langmuir等温线。此外,在预测的和实验的染料去除百分比的值之间观察到良好的一致性。结果表明,ANFIS可以有效地预测过程的行为。

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