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利用羧酸改性桑树叶增强阴离子染料在水溶液中的吸附去除效率:人工神经网络建模、等温线和动力学评价。

Enhancement of adsorptive removal efficiency of an anionic dye from aqueous solutions using carboxylic acid-modified mulberry leaves: Artificial neural network modeling, isotherm, and kinetics evaluation.

机构信息

Faculty of Sciences, Department of Chemistry, Karadeniz Technical University, 61080 Trabzon, Türkiye E-mail:

Faculty of Sciences, Department of Chemistry, Karadeniz Technical University, 61080 Trabzon, Türkiye.

出版信息

J Water Health. 2023 Jul;21(7):869-883. doi: 10.2166/wh.2023.025.

Abstract

Natural mulberry leaves and carboxylic acid-modified mulberry (Morus alba L.) leaves were used for the first time to scrutinize the effects of modification on the retention efficiency of an anionic dye (Remazol Brilliant Blue R (RBBR)) from aqueous solutions to suggest an economical and promising adsorbent for the treatment of dye-contaminated water. The characterization of the adsorbents was accomplished through common techniques including SEM, FTIR, and pH determination. Several parameters studied in batch experiments pointed out that the initial pH of 2.0 and the contact time of 240 min were optimum conditions for all the developed RBBR uptake processes. An artificial neural network (ANN) model was applied to formulate a forecast model for the uptake efficiency of RBBR. The experimental data were assessed by different kinetic and isotherm models to explain the mechanism of the developed processes in more detail. Maximum monolayer adsorption capacities of natural mulberry leaves and acetic acid-, citric acid-, and oxalic acid-modified mulberry leaves were determined as 64.5, 95.2, 84.8, and 91.7 mg g, respectively, by the Langmuir isotherm model. These results demonstrated that the modification with carboxylic acids significantly increases the anionic dye adsorption capacity of the mulberry leaves.

摘要

首次采用天然桑叶和羧酸改性桑叶(桑椹)来研究修饰对阴离子染料(丽春红 Brilliant Blue R(RBBR))在水溶液中的保留效率的影响,以期为处理受染料污染的水提供一种经济且有前景的吸附剂。通过 SEM、FTIR 和 pH 值测定等常用技术对吸附剂进行了表征。批量实验中研究的多个参数表明,初始 pH 值为 2.0 和接触时间为 240 min 是所有开发的 RBBR 吸收过程的最佳条件。应用人工神经网络(ANN)模型来构建 RBBR 吸收效率的预测模型。通过不同的动力学和等温线模型对实验数据进行评估,以更详细地解释所开发过程的机理。通过 Langmuir 等温线模型确定天然桑叶和乙酸、柠檬酸和草酸改性桑叶的最大单层吸附容量分别为 64.5、95.2、84.8 和 91.7 mg/g。这些结果表明,羧酸改性显著提高了桑叶对阴离子染料的吸附能力。

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