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Bioremediation of Malachite Green from Contaminated Water by Three Microalgae: Neural Network Modeling

机译:三种微藻对污水中孔雀石绿的生物修复作用:神经网络建模

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摘要

Biological decolorization of the triphenylmethane dye, Malachite Green (MG), by three microalgae, Chlorella, Cosmarium and Euglena species was investigated. Results indicated that the decolorization was dependent on reaction time, initial dye concentration, algal concentration, pH and temperature. The reusability and efficiency of the algae in long term repetitive operations were also examined. Since all of the algae had reasonable reusability in repetitive decolorization operations, the process seems to be biodegradation. An artificial neural network (ANN) model was developed to predict the biological decolorization of MG solution. The findings indicated that the ANN provided reasonable predictive performance (R~2 = 0.98). The influence of each parameter on the variable studied was assessed, and reaction time and initial pH were found to be the most significant factors, followed by temperature, initial dye concentration and amount of algae. Simulations based on the developed ANN model can estimate the behavior of the biological decolorization process under different conditions.
机译:研究了三种微藻(小球藻,s和Euglena)对三苯甲烷染料孔雀绿(MG)的生物脱色。结果表明,脱色取决于反应时间,初始染料浓度,藻类浓度,pH和温度。还检查了藻类在长期重复操作中的可重复使用性和效率。由于所有藻类在重复脱色操作中都具有合理的可重复使用性,因此该过程似乎是生物降解。开发了人工神经网络(ANN)模型来预测MG溶液的生物脱色。结果表明,人工神经网络提供了合理的预测性能(R〜2 = 0.98)。评估了每个参数对所研究变量的影响,发现反应时间和初始pH是最重要的因素,其次是温度,初始染料浓度和藻类数量。基于已开发的ANN模型的仿真可以估计不同条件下生物脱色过程的行为。

著录项

  • 来源
    《Clean》 |2010年第1期|p.96-103|共8页
  • 作者单位

    Department of Applied Chemistry, University of Tabriz, Tabriz, Iran;

    Department of Applied Chemistry, University of Tabriz, Tabriz, Iran;

    Department of Applied Chemistry, University of Tabriz, Tabriz, Iran,Department of Biology, Faculty of Science, University of Tabriz, Tabriz, Iran;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    algae; bioremediation; decolorization; dyes; modeling;

    机译:藻类生物修复;脱色染料;造型;

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