Bazrafshan Edris, Mohammadi Leili, Zarei Amin Allah, Mosafer Jafar, Zafar Muhammad Nadeem, Dargahi Abdollah
Health Sciences Research Center, Torbat Heydariyeh University of Medical Sciences Torbat Heydariyeh 33787 95196 Iran.
Department of Environmental Health Engineering, Torbat Heydariyeh University of Medical Sciences Torbat Heydariyeh 33787 95196 Iran
RSC Adv. 2023 Aug 24;13(36):25408-25424. doi: 10.1039/d3ra03612j. eCollection 2023 Aug 21.
The present work was carried out to remove phenol from aqueous medium using a photocatalytic process with superparamagnetic iron oxide nanoparticles (FeO) called SPIONs. The photocatalytic process was optimized using a central composite design based on the response surface methodology. The effects of pH (3-7), UV/SPION nanoparticles ratio (1-3), contact time (30-90 minutes), and initial phenol concentration (20-80 mg L) on the photocatalytic process were investigated. The interaction of the process parameters and their optimal conditions were determined using CCD. The statistical data were analyzed using a one-way analysis of variance. We developed a quadratic model using a central composite design to indicate the photocatalyst impact on the decomposition of phenol. There was a close similarity between the empirical values gained for the phenol content and the predicted response values. Considering the design, optimum values of pH, phenol concentration, UV/SPION ratio, and contact time were determined to be 3, 80 mg L, 3, and 60 min, respectively; 94.9% of phenol was eliminated under the mentioned conditions. Since high values were obtained for the adjusted (0.9786) and determination coefficient ( = 0.9875), the response surface methodology can describe the phenol removal by the use of the photocatalytic process. According to the one-way analysis of variance results, the quadratic model obtained by RSM is statistically significant for removing phenol. The recyclability of 92% after four consecutive cycles indicates the excellent stability of the photocatalyst for practical applications. Our research findings indicate that it is possible to employ response surface methodology as a helpful tool to optimize and modify process parameters for maximizing phenol removal from aqueous solutions and photocatalytic processes using SPIONs.
本研究旨在采用一种光催化工艺，利用称为超顺磁性氧化铁纳米颗粒（FeO）即SPIONs从水介质中去除苯酚。基于响应面法的中心复合设计对光催化工艺进行了优化。研究了pH值（3 - 7）、紫外光/SPION纳米颗粒比例（1 - 3）、接触时间（30 - 90分钟）和初始苯酚浓度（20 - 80 mg/L）对光催化工艺的影响。使用中心复合设计确定了工艺参数之间的相互作用及其最佳条件。使用单因素方差分析对统计数据进行了分析。我们利用中心复合设计建立了一个二次模型，以表明光催化剂对苯酚分解的影响。苯酚含量的实测值与预测响应值之间有密切的相似性。考虑到该设计，确定pH值、苯酚浓度、紫外光/SPION比例和接触时间的最佳值分别为3、80 mg/L、3和60分钟；在上述条件下94.9%的苯酚被去除。由于调整后的R²（0.9786）和决定系数（R² = 0.9875）获得了较高的值，响应面法可以描述利用光催化工艺去除苯酚的情况。根据单因素方差分析结果，响应面法得到的二次模型对于去除苯酚具有统计学意义。连续四个循环后92%的可回收性表明该光催化剂在实际应用中具有优异的稳定性。我们的研究结果表明，采用响应面法作为一种有用的工具来优化和修改工艺参数，以最大限度地从水溶液中去除苯酚以及利用SPIONs进行光催化工艺是可行的。
