Suppr超能文献

利用经验模型和人工神经网络对花生壳和杏仁壳在固定床柱中从水溶液中吸附去除Cr(VI)离子的比较研究

Comparative study of adsorptive removal of Cr(VI) ion from aqueous solution in fixed bed column by peanut shell and almond shell using empirical models and ANN.

作者信息

Banerjee Munmun, Bar Nirjhar, Basu Ranjan Kumar, Das Sudip Kumar

机构信息

Chemical Engineering Department, University of Calcutta, 92, APC Road, Kolkata, 700009, India.

出版信息

Environ Sci Pollut Res Int. 2017 Apr;24(11):10604-10620. doi: 10.1007/s11356-017-8582-8. Epub 2017 Mar 10.

Abstract

Cr(VI) is a toxic water pollutant, which causes cancer and mutation in living organisms. Adsorption has become the most preferred method for removal of Cr(VI) due to its high efficiency and low cost. Peanut and almond shells were used as adsorbents in downflow fixed bed continuous column operation for Cr(VI) removal. The experiments were carried out to scrutinise the adsorptive capacity of the peanut shells and almond shells, as well as to find out the effect of various operating parameters such as column bed depth (5-10 cm), influent flow rate (10-22 ml min) and influent Cr(VI) concentration (10-20 mg L) on the Cr(VI) removal. The fixed bed column operation for Cr(VI) adsorption the equilibrium was illustrated by Langmuir isotherm. Different well-known mathematical models were applied to the experimental data to identify the best-fitted model to explain the bed dynamics. Prediction of the bed dynamics by Yan et al. model was found to be satisfactory. Applicability of artificial neural network (ANN) modelling is also reported. An ANN modelling of multilayer perceptron with gradient descent and Levenberg-Marquardt algorithms have also been tried to predict the percentage removal of Cr(VI). This study indicates that these adsorbents have an excellent potential and are useful for water treatment particularly small- and medium-sized industries of third world countries. Almond shell represents better adsorptive capacity as breakthrough time and exhaustion time are longer in comparison to peanut shell.

摘要

六价铬是一种有毒的水污染物,会导致生物体患癌和发生突变。由于吸附法高效且低成本,它已成为去除六价铬最受欢迎的方法。在向下流动固定床连续柱操作中,使用花生壳和杏仁壳作为吸附剂来去除六价铬。进行这些实验是为了仔细研究花生壳和杏仁壳的吸附能力,以及找出各种操作参数,如柱床深度(5 - 10厘米)、进水流量(10 - 22毫升/分钟)和进水六价铬浓度(10 - 20毫克/升)对六价铬去除的影响。用于六价铬吸附的固定床柱操作的平衡由朗缪尔等温线说明。将不同的知名数学模型应用于实验数据,以确定最适合解释床层动态的模型。发现用Yan等人的模型预测床层动态是令人满意的。还报告了人工神经网络(ANN)建模的适用性。也尝试了使用具有梯度下降和列文伯格 - 马夸特算法的多层感知器的人工神经网络建模来预测六价铬的去除百分比。这项研究表明,这些吸附剂具有出色的潜力,对水处理尤其对第三世界国家的中小型工业很有用。与花生壳相比,杏仁壳的吸附能力更好,因为其穿透时间和耗尽时间更长。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验