College of Chemistry, Shahrood University of Technology, Shahrood, P.O. Box 36155-316, Iran.
College of Chemistry, Shahrood University of Technology, Shahrood, P.O. Box 36155-316, Iran.
Spectrochim Acta A Mol Biomol Spectrosc. 2017 Jan 15;171:268-279. doi: 10.1016/j.saa.2016.07.049. Epub 2016 Aug 3.
The performance of the Nano-magnetite FeO impregnated onto walnut shell (FeO-WNS), which possessed the adsorption features of walnut shell and the magnetic property of FeO, was investigated for the elimination of the methyl violet and Rhodamine 6G from contaminated aqueous solutions. The effects of different experimental variables on the removal efficiency of the cited dyes were examined. Then these variables were used as the inputs to generate linear and non-linear models such as the multiple linear regression, random forest, and artificial neural network to predict the removal efficiency of these dye species at different experimental conditions. The validation studies of these models were performed using the test set, which was not present in the modeling procedure. It was found that ANN had a higher ability to predict the adsorption process under different experimental conditions, and could be applied for the development of an automated dye wastewater removal plant. Also the maximum adsorption capacity (q) indicated that the q value for FeO-WNS for removal of cationic dyes was comparable or better than that for some reported adsorbents. Also it should be cited that exhausted FeO-WNS was regenerated using dishwashing liquid, and reused for removal of the cited dye species from aqueous solutions.
用纳米磁铁矿 FeO 浸渍核桃壳(FeO-WNS)的性能,具有核桃壳的吸附特性和 FeO 的磁性,被用于从受污染的水溶液中去除甲基紫和罗丹明 6G。考察了不同实验变量对被引用染料去除效率的影响。然后,这些变量被用作输入,以生成线性和非线性模型,如多元线性回归、随机森林和人工神经网络,以预测在不同实验条件下这些染料的去除效率。这些模型的验证研究是使用建模过程中未出现的测试集进行的。结果表明,ANN 具有更高的能力来预测不同实验条件下的吸附过程,可用于开发自动化染料废水去除装置。此外,最大吸附容量(q)表明,FeO-WNS 对阳离子染料的去除的 q 值与一些报道的吸附剂相当或更好。还应该指出的是,用过的 FeO-WNS 使用洗碗液再生,并重新用于从水溶液中去除引用的染料。