Simulation the adsorption capacity of polyvinyl alcohol/carboxymethyl cellulose based hydrogels towards methylene blue in aqueous solutions using cascade correlation neural network (CCNN) technique
Simulation the adsorption capacity of polyvinyl alcohol/carboxymethyl cellulose based hydrogels towards methylene blue in aqueous solutions using cascade correlation neural network (CCNN) technique
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DOI：
10.1016/j.jclepro.2022.130509
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发表时间：
2022-01-20
影响因子：
11.1
通讯作者：
Aminzadehsarikhanbeglou, Elnaz
中科院分区：
文献类型：
--
作者：
Alibak, Ali Hosin;Khodarahmi, Mohsen;Aminzadehsarikhanbeglou, Elnaz
几乎所有的工业都会产生大量的染料污染废水。含有高剂量亚甲基蓝（MB）的饮用水对人类、环境和生态系统构成威胁。因此，在废水排放到环境中之前，需要去除MB分子。吸附是从水和废水中去除染料的最熟知的方法。本研究的重点是生物基水凝胶去除MB的智能模拟。事实上，级联相关神经网络（CCNN）采用模拟MB分子的吸附机制的生物基（聚乙烯醇/羧甲基纤维素）水凝胶增强的氧化石墨烯纳米颗粒和膨润土。Levenberg-Marquardt算法训练CCNN以估计作为吸附剂类型、温度、初始染料浓度、pH和接触时间的函数的MB摄取的水凝胶容量。试验和错误分析证明，一个隐藏层包含六个神经元的CCNN是最可靠的模型为给定的问题。该模型预测了从文献中收集的实验数据，具有良好的一致性（即，RMSE = 2.00，AARD = 2.4%，R-2 = 0.9980）。实验测量和建模结果证实，在30-40 ℃下，MB的摄取通过增加温度、接触时间、pH值和初始染料浓度而增强。在50 ℃下增加大染料离子的迁移率会降低所有生物吸附剂的吸附能力。此外，具有膨润土/GO纳米颗粒的增强生物基水凝胶是对亚甲基蓝吸收的最佳吸附剂。
Almost all industries produce a large quantity of dye-contaminated wastewater. Wastewaters containing a high dosage of methylene blue (MB) are a menace for human beings, the environment, and the ecosystem. Thus, the MB molecules are needed to be removed before wastewater discharge to the environment. Adsorption is the most well-known process for dye removal from water and wastewater. This study focuses on the intelligent simulation of the MB removal by the bio-based hydrogel. Indeed, the cascade correlation neural network (CCNN) employs to simulate the adsorption mechanism of MB molecules by the bio-based (polyvinyl alcohol/carboxymethyl cellulose) hydrogel reinforced by graphene oxide nanoparticles and bentonite. The Levenberg-Marquardt algorithm trains the CCNN to estimate the hydrogel capacity for MB uptake as a function of adsorbent type, temperature, initial dye concentration, pH, and contact time. Trial-and-error analyses justified that the CCNN with one hidden layer containing six neurons is the most reliable model for the given problem. This model predicts the collected experimental data from the literature with excellent agreement (i.e., RMSE = 2.00, AARD = 2.4%, and R-2 = 0.9980). Experimental measurements and modeling findings approved that MB uptake at 30-40 C intensifies by increasing temperature, contact time, pH, and initial dye concentration. Increasing the mobility of the large dye ions at 50 C reduces the adsorption capacity of all bio-adsorbents. Furthermore, the reinforced bio-based hydrogel with bentonite/GO nanoparticles is the best adsorbent for the methylene blue uptake.