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Optimization of adsorptive removal of α-toluic acid by CaO 2 nanoparticles using response surface methodology

机译:响应面法优化CaO 2纳米颗粒对α-甲苯甲酸的吸附去除

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The present work addresses the optimization of process parameters for adsorptive removal of α-toluic acid by calcium peroxide (CaO2) nanoparticles using response surface methodology (RSM). CaO2 nanoparticles were synthesized by chemical precipitation method and confirmed by Transmission electron microscopy (TEM) and high-resolution TEM (HRTEM) analysis which shows the CaO2 nanoparticles size range of 5–15?nm. A series of batch adsorption experiments were performed using CaO2 nanoparticles to remove α-toluic acid from the aqueous solution. Further, an experimental based central composite design (CCD) was developed to study the interactive effect of CaO2 adsorbent dosage, initial concentration of α-toluic acid, and contact time on α-toluic acid removal efficiency (response) and optimization of the process. Analysis of variance (ANOVA) was performed to determine the significance of the individual and the interactive effects of variables on the response. The model predicted response showed a good agreement with the experimental response, and the coefficient of determination, ( R 2) was 0.92. Among the variables, the interactive effect of adsorbent dosage and the initial α-toluic acid concentration was found to have more influence on the response than the contact time. Numerical optimization of process by RSM showed the optimal adsorbent dosage, initial concentration of α-toluic acid, and contact time as 0.03?g, 7.06?g/L, and 34?min respectively. The predicted removal efficiency was 99.50%. The experiments performed under these conditions showed α-toluic acid removal efficiency up to 98.05%, which confirmed the adequacy of the model prediction.
机译:目前的工作解决了使用响应表面方法(RSM)通过过氧化钙(CaO 2 )纳米颗粒吸附去除α-甲苯甲酸的工艺参数的优化。通过化学沉淀法合成CaO 2 纳米粒子,并通过透射电镜(TEM)和高分辨率TEM(HRTEM)分析证实,CaO 2 纳米粒子的粒径范围5-15纳米。用CaO 2 纳米颗粒进行了一系列间歇吸附实验,以从水溶液中去除α-甲苯甲酸。此外,还开发了基于实验的中央复合设计(CCD),以研究CaO 2 吸附剂剂量,α-甲苯甲酸的初始浓度以及接触时间对α-甲苯甲酸去除效率的交互作用(响应)和流程优化。进行方差分析(ANOVA)以确定个体的重要性以及变量对响应的交互作用。模型预测响应与实验响应吻合良好,测定系数R 2 为0.92。在变量中,吸附剂剂量和初始α-甲苯甲酸浓度的相互作用影响被发现比接触时间对反应的影响更大。 RSM对工艺的数值优化表明,最佳吸附剂剂量,α-甲苯甲酸的初始浓度和接触时间分别为0.03?g,7.06?g / L和34?min。预计去除效率为99.50%。在这些条件下进行的实验表明,α-甲苯甲酸的去除效率高达98.05%,这证实了模型预测的充分性。

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