Optimization of adsorptive removal of α-toluic acid by CaO2 nanoparticles using response surface methodology

Sapana S. Madan, Kailas L. Wasewar, C. Ravi Kumar
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引用次数: 13

Abstract

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, (R2) 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.

响应面法优化氧化钙纳米颗粒吸附去除α-甲酸的工艺
采用响应面法(RSM)对过氧化钙(CaO2)纳米颗粒吸附去除α-甲酸的工艺参数进行了优化。采用化学沉淀法合成了CaO2纳米颗粒,并通过透射电子显微镜(TEM)和高分辨率透射电子显微镜(HRTEM)对其进行了分析,结果表明CaO2纳米颗粒的尺寸范围为5 ~ 15 nm。采用CaO2纳米颗粒对水溶液中α-甲苯进行了批量吸附实验。在此基础上,建立了基于实验的中心复合设计(CCD),研究了吸附剂用量、α-甲苯初始浓度和接触时间对α-甲苯脱除效率(响应)的交互作用,并对工艺进行了优化。进行方差分析(ANOVA)以确定个体的显著性和变量对反应的交互影响。模型预测响应与实验响应吻合较好,决定系数(R2)为0.92。其中,吸附剂用量和α-甲酸初始浓度的交互作用比对接触时间的影响更大。结果表明,吸附剂用量为0.03 g, α-甲苯初始浓度为7.06 g/L,接触时间为34 min。预测去除率为99.50%。在此条件下进行的实验表明,α-甲苯的去除率可达98.05%,证实了模型预测的充分性。
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