STUDY OF THE SORPTION OF AMMONIUM CATIONS ON A FIBROUS CARBOXYLIC SORBENT

IF 0.2 Q4 CHEMISTRY, MULTIDISCIPLINARY Periodico Tche Quimica Pub Date : 2021-07-28 DOI:10.52571/ptq.v18.n38.2021.16_peregudov_pgs_224_241.pdf
Y. Peregudov, E. Gorbunova, Behzod Aminovich Obidov, Ks Kim, S. I. Niftaliev
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Abstract

Background: Wastewater from the mineral fertilizer production, agribusiness containing ammonium ions causes significant harm to fish farming; therefore, it must be purified before discharge. Ion-exchange sorption is a promising method for isolating ammonium cations. The object of the study was a chemisorption fiber VION KN-1, which has developed surface and high sorption rate. Purpose: To study the sorption kinetics of ammonium cations from aqueous solutions on VION KN-1; to train an ANN to predict the degree of recovery of ammonium ions from wastewater using Statistica Neural Networks Version 13. Methods: The ammonium ion concentration in the solution was established by direct potentiometry. Sorption isotherms were constructed using the method of variable concentrations. To determine the limiting stage, the obtained kinetic dependencies were represented in the coordinates of the Boyd-Adamson equations for internal/external diffusion. Results and Discussion: During sorption from solutions with different ammonium nitrogen contents, the values of distribution coefficients (Kd) are at the level of 2.3ꞏ103 cm3/g, which significantly exceeds this parameter for granular ionites. Experimental sorption data were verified using Freundlich (R2 = 0.9224) and Langmuir (R2 = 0.9996) isotherms. The maximum degree of recovery (over 96 %) was achieved by passing a solution with a concentration of 11.3 mmol/dm3. Using an array of experimental data, the MLP-3-5-1 neural network was trained. The coefficient of determination R2 = 0.999420 obtained for the training sample characterizes high network performance. Conclusions: The Langmuir equation better describes the process of NH4+ sorption on a fibrous sorbent. It is reasonable to use VION KN-1 at the fine treatment stage. Ammonium ion desorption from the fiber was performed by acid solution. The resulting solutions of ammonium salts can be used as liquid fertilizers. The trained neural networks can be used to predict the degree of recovery of ammonium ions by sorbent VION KN-1.
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纤维状羧酸吸附剂吸附铵离子的研究
背景:矿物肥料生产、农业综合企业废水中含有铵离子,对鱼类养殖造成重大危害;因此,必须在排放前对其进行净化。离子交换吸附是一种很有前途的铵离子分离方法。研究对象是一种表面发达、吸附率高的化学吸附纤维VION KN-1。目的:研究铵离子在VION KN-1上的吸附动力学;使用Statistica神经网络版本13来训练ANN以预测废水中铵离子的回收程度。方法:采用直接电位法测定溶液中铵离子的浓度。采用变浓度法构建了吸附等温线。为了确定极限阶段,所获得的动力学依赖关系用Boyd-Adamson方程的坐标表示,用于内部/外部扩散。结果和讨论:在从具有不同铵态氮含量的溶液中吸附过程中,分布系数(Kd)的值处于2.3的水平ꞏ103cm3/g,这显著超过了颗粒离子的该参数。使用Freundlich(R2=0.9224)和Langmuir(R2=0.9996)等温线验证了实验吸附数据。通过使浓度为11.3mmol/dm3的溶液通过,实现了最大回收率(超过96%)。利用一系列实验数据,对MLP-3-5-1神经网络进行了训练。对于训练样本获得的确定系数R2=0.999420表征了高网络性能。结论:Langmuir方程较好地描述了NH4+在纤维吸附剂上的吸附过程。在精细处理阶段使用VION KN-1是合理的。铵离子从纤维上的解吸是通过酸溶液进行的。得到的铵盐溶液可以用作液体肥料。训练的神经网络可用于预测吸附剂VION KN-1对铵离子的回收程度。
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Periodico Tche Quimica
Periodico Tche Quimica CHEMISTRY, MULTIDISCIPLINARY-
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期刊介绍: The Journal publishes original research papers, review articles, short communications (scientific publications), book reviews, forum articles, announcements or letters as well as interviews. Researchers from all countries are invited to publish on its pages.
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