Sorption of ammonium by fibrous sorbent VION KN-1

S. I. Niftaliev, E. M. Gorbunova, A. V. Timkova, K. B. Kim, V. N. Danilov
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Abstract

The results of studies of the sorption extraction of ammonium ions from aqueous media by the fibrous sorbent VION KN-1 are presented. Weak acid ion exchange fiber. It has been established that the limiting step in the process of ammonium ion sorption is internal diffusion. The kinetic parameters of the sorption process are calculated, with the identification of a decrease in the half-sorption time and an increase in the internal diffusion coefficient. The applicability of the Langmuir and Freindlich models for describing the experimental isotherms of ammonium ion sorption by fiber has been studied. Certain constants and parameters. Through the appearance of regression coefficients, R2 showed that the Langmuir model better explores experimental data on the sorption of ammonium ions by a fibrous sorbent. A study of sorption in media was carried out. According to the curves of the dependence of the degree of extraction on the concentration and on the depth of the missed solution, it was found that with a decrease in concentration in the dynamic sorption mechanism, the reduction characteristics do not decrease, which makes their use reduced in the purification of dilute solutions containing ammonium ions. At a low concentration of ammonium ions in the initial solution, the degree of extraction is more than 93%. To predict the extraction of ammonium ions from wastewater, an increased concentration of neural packages of STATISTICA application programs was used. The input parameters for studying the neural network were chosen: the concentration of ammonium ions, the volume of the solution passed through the sorbent layer, and the weight of the sample of fibers. The output parameter is the degree of extraction of ammonium ions. The trained MPL-3-5-1 neural network has high coefficients of determination for the training, test and control samples, which gives a high estimate of the network performance and can predict the degree of extraction of ammonium ions by the fibrous sorbent VION KN-1..
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纤维吸附剂VION KN-1对铵的吸附
本文介绍了纤维吸附剂VION KN-1吸附萃取水中铵离子的研究结果。弱酸离子交换纤维。确定了铵离子吸附过程的限制步骤是内扩散。计算了吸附过程的动力学参数,发现半吸附时间缩短,内扩散系数增大。研究了Langmuir模型和Freindlich模型描述纤维吸附铵离子实验等温线的适用性。某些常量和参数。通过回归系数的出现,R2表明Langmuir模型较好地探究了纤维状吸附剂吸附铵离子的实验数据。对介质中的吸附进行了研究。根据萃取度随浓度和漏液深度的变化曲线,发现在动态吸附机制中,随着浓度的降低,还原特性不降低,这使得其在含铵离子的稀溶液的提纯中使用减少。初始溶液中铵离子浓度较低时,萃取度可达93%以上。为了预测废水中铵离子的提取,使用了STATISTICA应用程序中增加浓度的神经包。研究神经网络的输入参数为:铵离子浓度、通过吸附层的溶液体积和纤维样品的质量。输出参数为铵离子的萃取度。训练后的MPL-3-5-1神经网络对训练样本、测试样本和控制样本具有较高的确定系数,可以对网络性能给出较高的估计,并可以预测纤维状吸附剂VION KN-1对铵离子的提取程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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70
审稿时长
8 weeks
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