Department of Chemical Engineering Faculty, Shahreza Branch, Islamic Azad University, P.O.Box 311-86145, Shahreza, Iran.
Nanoparticle Process Technology, Faculty of Engineering, University of Duisburg-Essen, Duisburg, Germany.
J Environ Manage. 2019 Feb 15;232:342-353. doi: 10.1016/j.jenvman.2018.11.047. Epub 2018 Nov 27.
In the current study, the prediction efficiency of lead adsorption by highly functional nanocomposite adsorbent of hydroxyapatite (HAp)/chitosan using ANFIS system was investigated. In this regard, the nanocomposite was applied in order to investigate the lead adsorption capacity. The operational conditions were pH (2-6), contact time between lead ions and adsorbent (15-360 min), shaker velocity (80-400 rpm), temperature (25-55 °C), amount of adsorbent (0.01-1.5 g), lead initial concentration (0-5000 ppm) and HAp concentration (10-75%). The effect of each parameter was investigated, and then the ANFIS was employed to model the adsorption process using the obtained experimental results. The ANFIS modeled the results with total average error and total average of absolute error less than 0.0646% and 4.2428%, respectively, for training data. Moreover, the coefficient of determination for training data and testing data were found to be 0.9999 and 0.9823, respectively. In addition, granular chitosan and HAp nanoparticles adsorption capabilities were compared with nanocomposite of HAp (20%wt)/chitosan adsorbent. It was found that nanocomposite adsorbent had a higher adsorption capability than other adsorbents.
在本研究中，使用自适应神经模糊推理系统（ANFIS）研究了羟磷灰石（HAp）/壳聚糖的高功能纳米复合材料吸附剂对铅吸附的预测效率。为此，应用纳米复合材料来研究铅的吸附容量。研究了操作条件对铅吸附的影响，包括 pH 值（2-6）、铅离子与吸附剂的接触时间（15-360 分钟）、摇床速度（80-400 转/分钟）、温度（25-55°C）、吸附剂用量（0.01-1.5 克）、铅初始浓度（0-5000 ppm）和 HAp 浓度（10-75%）。研究了每个参数的影响，然后使用获得的实验结果，通过 ANFIS 来模拟吸附过程。ANFIS 对模型结果的总平均误差和总平均绝对误差的建模效果较好，分别小于 0.0646%和 4.2428%，用于训练数据。此外，发现训练数据和测试数据的决定系数分别为 0.9999 和 0.9823。此外，还比较了颗粒状壳聚糖和 HAp 纳米粒子的吸附能力与 HAp（20%wt）/壳聚糖纳米复合材料吸附剂的吸附能力。结果表明，纳米复合材料吸附剂比其他吸附剂具有更高的吸附能力。
