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从水溶液中吸附铬 (VI)及其人工神经网络建模。

Biosorption of chromium (VI) from aqueous solutions and ANN modelling.

机构信息

National Institute of Technology Agartala, Agartala, India.

Department of Chemical Engineering, University of Calcutta, Calcutta, India.

出版信息

Environ Sci Pollut Res Int. 2017 Aug;24(23):18817-18835. doi: 10.1007/s11356-017-9325-6. Epub 2017 Jun 16.

DOI:10.1007/s11356-017-9325-6
PMID:28623504
Abstract

The use of sustainable, green and biodegradable natural wastes for Cr(VI) detoxification from the contaminated wastewater is considered as a challenging issue. The present research is aimed to assess the effectiveness of seven different natural biomaterials, such as jackfruit leaf, mango leaf, onion peel, garlic peel, bamboo leaf, acid treated rubber leaf and coconut shell powder, for Cr(VI) eradication from aqueous solution by biosorption process. Characterizations were conducted using SEM, BET and FTIR spectroscopy. The effects of operating parameters, viz., pH, initial Cr(VI) ion concentration, adsorbent dosages, contact time and temperature on metal removal efficiency, were studied. The biosorption mechanism was described by the pseudo-second-order model and Langmuir isotherm model. The biosorption process was exothermic, spontaneous and chemical (except garlic peel) in nature. The sequence of adsorption capacity was mango leaf > jackfruit leaf > acid treated rubber leaf > onion peel > bamboo leaf > garlic peel > coconut shell with maximum Langmuir adsorption capacity of 35.7 mg g for mango leaf. The treated effluent can be reused. Desorption study suggested effective reuse of the adsorbents up to three cycles, and safe disposal method of the used adsorbents suggested biodegradability and sustainability of the process by reapplication of the spent adsorbent and ultimately leading towards zero wastages. The performances of the adsorbents were verified with wastewater from electroplating industry. The scale-up study reported for industrial applications. ANN modelling using multilayer perception with gradient descent (GD) and Levenberg-Marquart (LM) algorithm had been successfully used for prediction of Cr(VI) removal efficiency. The study explores the undiscovered potential of the natural waste materials for sustainable existence of small and medium sector industries, especially in the third world countries by protecting the environment by eco-innovation.

摘要

利用可持续、绿色和可生物降解的天然废物来从受污染废水中解毒六价铬(Cr(VI))被认为是一个具有挑战性的问题。本研究旨在评估七种不同天然生物材料(如菠萝蜜叶、芒果叶、洋葱皮、大蒜皮、竹叶、酸处理橡胶叶和椰子壳粉)通过生物吸附过程从水溶液中去除 Cr(VI)的有效性。通过 SEM、BET 和 FTIR 光谱进行了表征。研究了操作参数(即 pH、初始 Cr(VI)离子浓度、吸附剂剂量、接触时间和温度)对金属去除效率的影响。生物吸附机制由准二级模型和 Langmuir 等温线模型描述。生物吸附过程是放热、自发和化学的(除了大蒜皮)。吸附容量的顺序为芒果叶>菠萝蜜叶>酸处理橡胶叶>洋葱皮>竹叶>大蒜皮>椰子壳,芒果叶的最大 Langmuir 吸附容量为 35.7mg/g。处理后的废水可再利用。解吸研究表明,吸附剂可有效重复使用三到三个循环,建议采用生物降解和可持续性的方法处理用过的吸附剂,通过重新使用用过的吸附剂最终实现零浪费。通过电镀工业废水验证了吸附剂的性能。该研究报告了可扩展的研究,可用于工业应用。使用多层感知器(MLP)和梯度下降(GD)和列文伯格-马夸尔特(LM)算法的人工神经网络(ANN)建模成功用于预测 Cr(VI)去除效率。该研究通过生态创新保护环境,探索了天然废物在可持续中小规模行业(特别是在第三世界国家)中的未被发现的潜力。

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