左君, 严丽君, 杨秀琴, 程跃. 响应曲面法优化超细氧化亚铜光催化降解对硝基苯酚[J]. 工程科学学报, 2010, 32(8): 1045-1052. DOI: 10.13374/j.issn1001-053x.2010.08.029
引用本文: 左君, 严丽君, 杨秀琴, 程跃. 响应曲面法优化超细氧化亚铜光催化降解对硝基苯酚[J]. 工程科学学报, 2010, 32(8): 1045-1052. DOI: 10.13374/j.issn1001-053x.2010.08.029
ZUO Jun, YAN Li-jun, YANG Xiu-qin, CHENG Yue. Photocatalytic degradation optimization of p-nitrophenol liquid by using ultrafine cuprous oxide with response surface methodology[J]. Chinese Journal of Engineering, 2010, 32(8): 1045-1052. DOI: 10.13374/j.issn1001-053x.2010.08.029
Citation: ZUO Jun, YAN Li-jun, YANG Xiu-qin, CHENG Yue. Photocatalytic degradation optimization of p-nitrophenol liquid by using ultrafine cuprous oxide with response surface methodology[J]. Chinese Journal of Engineering, 2010, 32(8): 1045-1052. DOI: 10.13374/j.issn1001-053x.2010.08.029

响应曲面法优化超细氧化亚铜光催化降解对硝基苯酚

Photocatalytic degradation optimization of p-nitrophenol liquid by using ultrafine cuprous oxide with response surface methodology

  • 摘要: 制备出P-型半导体超细氧化亚铜,并将其应用于光催化降解对硝基苯酚,通过单因素实验确定主要影响因素和水平后,利用响应曲面法(RSM)对超细氧化亚铜的光催化降解的主要影响因素进行优化.通过分析实验结果,建立了超细氧化亚铜光催化降解对硝基苯酚的二次多项数学模型,预测处理最佳实验条件为:对硝基苯酚溶液的质量浓度为30mg·L-1,H2O2滴加量为0.28mL,pH3.64,氧化亚铜投加量为0.11g.在最佳条件下进行验证实验,发现真实脱色率与预测脱色率具有良好一致性,相对误差仅为3.02%.

     

    Abstract: P-type semiconductor uhrafine cuprous oxide was prepared and used for the photocatalytic degradation of p-nitrophenol liquid. The main influence factors and levels were ascertained by single factor experiments, and response surface methodology (RSM) was used in optimizing the main influence factors of photocatalytic degradation. Through analyzing the results of response surface methodology experiments, a quadratic polynomial model of photocatalytic degradation for p-nitrophenol by using uhrafine cuprous oxide was obtained. The optimum conditions are the following: the mass concentration of p-nitrophenol solution is 30 mg·L-1, the volume of H2O2 is 0.28 mL, the pH value is 3.6d, and the amount of Cu2O is 0.11 g. Experiments were carried out under the predicted optimum conditions, the relative error between actual and predicted values is 3.02%, and the actual decolorization efficiency is in good agreement with the predicted decolorization efficiency.

     

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