Department of Chemistry, Faculty of Science, University of Guilan, P.O. Box: 19141, Rasht, Iran.
Applied Chemistry Department, Faculty of Gas and Petroleum (Gachsaran), Yasouj University, Gachsaran 75813-56001, Iran.
Chemosphere. 2022 Dec;308(Pt 1):136007. doi: 10.1016/j.chemosphere.2022.136007. Epub 2022 Aug 19.
Tetracycline (TC), as the second produced and used antibiotic worldwide, is difficult to be entirely metabolized not only in the body, but also in the treatment processes of water and/or wastewater. Therefore, special attention needs to be paid on defining or developing new options for removing such contaminant. Herein, a reduced graphene oxide (GO) was integrated with Ni-Al layered double hydroxide (LDH) as well poly acrylic acid (LDH-rGO-PAA) and examined to reduce TC -as a model antibiotic-in water media under different operational parameters of TC initial concentration, pH, NC dose, and time. The governed behaviour in the adsorption process was investigated using three model methods of response surface methodology (RSM), artificial neural networks (ANN), and general regression neural network (GRNN) after confirming the physico-chemical properties of LDH-rGO-PAA nanocomposite (NC) using different techniques. The LDH-rGO-PAA NC displayed a good performance as either removal efficiency (R = 94.87 ± 0.25%) or adsorption capacity (q = 887.5 mg/g) with the respective values of 110 mg/L, 6.3, 20 mg, and 18.50 min for the mentioned factors (TC initial concentration, pH, NC dose, and time, respectively), which was higher than that of reported for the similar adsorbents until now.
四环素（TC）是全球第二大生产和使用的抗生素，不仅在体内难以完全代谢，在水和/或废水的处理过程中也是如此。因此，需要特别注意定义或开发新的选择来去除这种污染物。在此，将还原氧化石墨烯（GO）与镍-铝层状双氢氧化物（LDH）以及聚丙烯酸（LDH-rGO-PAA）结合在一起，并研究了其在不同操作参数（TC 初始浓度、pH 值、NC 剂量和时间）下在水介质中去除 TC（作为模型抗生素）的性能。在确认 LDH-rGO-PAA 纳米复合材料（NC）的物理化学性质后，使用响应面法（RSM）、人工神经网络（ANN）和广义回归神经网络（GRNN）这三种模型方法研究了吸附过程的控制行为。该 LDH-rGO-PAA NC 表现出良好的性能，去除效率（R=94.87±0.25%）或吸附容量（q=887.5mg/g），其相应值分别为 110mg/L、6.3、20mg 和 18.50min，这些值高于迄今为止报道的类似吸附剂的值。
