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首页> 外文期刊>Water Practice and Technology >Reactive orange 12 dye adsorption onto magnetically separable CaFe_2O_4 nanoparticles synthesized by simple chemical route: kinetic, isotherm and neural network modeling
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Reactive orange 12 dye adsorption onto magnetically separable CaFe_2O_4 nanoparticles synthesized by simple chemical route: kinetic, isotherm and neural network modeling

机译:反应性橙12染料吸附到通过简单化学路线合成的磁性可分离的CaFe_2O_4纳米颗粒:动力学,等温线和神经网络建模

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Industrial wastewaters laden with toxic dyes are required to be treated prior to their disposal in view of their adverse effect on human health and aquatic ecosystem. Thus in this research, CaFe2O4 nanoparticles were prepared and used as adsorbent for elimination of reactive orange 12 dye (RO12) from aqueous medium. The CaFe2O4 nanoparticles exhibit specific surface area of similar to 230 m(2)/g and average pore diameter of similar to 2.5 nm. Maximum RO12 removal of 77% was observed at solution pH 2.0 with uptake capacity of 276.92 mg/g. The electrostatic interaction between CaFe2O4 nanoparticles and RO12 was the main driving force behind this adsorption. The kinetic modeling reveal that this adsorption process obeyed the pseudo-second-order kinetic model accurately (R-2: 0.988-0.994) indicating the chemisorption behavior. The adsorption experimental data firmly followed the Langmuir isotherm model (R-2: 0.997), confirming the monolayer adsorption. Thermodynamic study suggests that the adsorption process is spontaneous (Delta G(0) = -8.76 to -3.19 kJ/mol) and exothermic in nature (Delta H-0 = -71.86 kJ). A neural network model (optimum topology of 4-7-1) was developed for precise forecasting of RO12 removal (%). The developed model with very high correlation coefficient (0.986) and very low mean squared error (0.00185) was successful for accurate prediction of experimental data.
机译:鉴于对人类健康和水生生态系统的不利影响,需要在处理前服用有毒染料的工业废水。因此,在该研究中,制备CaFe2O4纳米颗粒并用作消除来自水性介质的反应性橙12染料(RO12)的吸附剂。 CaFe2O4纳米粒子表现出类似于230μm(2)/ g的比表面积和与2.5nm相似的平均孔径。在溶液pH 2.0下观察到最大RO12去除77%,摄取容量为276.92mg / g。 CaFe2O4纳米颗粒和RO12之间的静电相互作用是这种吸附背后的主要驱动力。动力学建模表明,该吸附过程准确地遵守了伪二阶动力学模型(R-2:0.988-0.994),表明了化学吸附行为。吸附实验数据牢固地跟随Langmuir等温线(R-2:0.997),确认单层吸附。热力学研究表明,吸附过程是自发的(Delta G(0)= -8.76至-3.19 kJ / mol),本质上放热(Delta H-0 = -71.86 kJ)。开发了一种神经网络模型(4-7-1的最佳拓扑),用于精确预测RO12去除(%)。具有非常高的相关系数(0.986)和非常低的平均平方误差(0.00185)的开发模型是成功的,以准确预测实验数据。

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