Faculty of Chemistry, TNU-University of Sciences, Tan Thinh Ward, Thai Nguyen, 250000, Vietnam.
Faculty of Forestry and Wood Technology, Mendel University in Brno, Zemedelska 1, 61300, Brno, Czech Republic.
Environ Sci Pollut Res Int. 2021 Feb;28(8):9133-9145. doi: 10.1007/s11356-020-10633-2. Epub 2020 Oct 31.
This work aims to synthesize akaganeite nanoparticles (AKNPs) by using microwave and use them to adsorb Congo red dye (CR) from the aqueous solution. The AKNPs with an average particle size of about 50 nm in width and 100 nm in length could be fabricated in 20 min. The effects of pH, CR initial concentration, adsorption time, and adsorbent dosage on the adsorption process were investigated and the artificial neural network (ANN) was used to analyze the adsorption data. The various ANN structures were examined in training the data to find the optimal model. The structure with training function, TRAINLM; adaptation learning function, LARNGDM; transfer function, LOGSIG (in hidden layer) and PURELIN (in output layer); and 10 neutrons in hidden layer having the highest correlation (R = 0.996) and the lowest MSE (4.405) is the optimal ANN structure. The consistency between the experimental data and the data predicted by the ANN model showed that the behavior of the adsorption process of CR onto AKNPs under different conditions can be estimated by the ANN model. The adsorption kinetics was studied by fitting the data into pseudo-first-order, pseudo-second-order, Elovich, and intraparticle diffusion models. The results showed that the adsorption kinetics obeyed the pseudo-second-order model and governed by several steps. The adsorption isotherms at the different temperatures were studied by fitting the data to Langmuir, Freundlich, and Temkin isotherm models. The R obtained from the Langmuir model was above 0.9 and the highest value in three of four temperatures, suggesting that the adsorption isotherms were the best fit to the Langmuir model and the maximum adsorption capacity was estimated to be more than 150 mg/g. Thermodynamic studies suggested that the adsorption of CR onto AKNPs was a spontaneous and endothermic process and physicochemical adsorption. The obtained results indicated the potential application of microwave-synthesize AKNPs for removing organic dyes from aqueous solutions.
这项工作旨在通过微波合成纤铁矿纳米粒子（AKNPs），并利用其从水溶液中吸附刚果红染料（CR）。在 20 分钟内可以制备出平均粒径约为 50nm 宽和 100nm 长的 AKNPs。考察了 pH 值、CR 初始浓度、吸附时间和吸附剂用量对吸附过程的影响，并采用人工神经网络（ANN）对吸附数据进行分析。检查了各种 ANN 结构以训练数据，以找到最佳模型。具有训练函数 TRAINLM、适应学习函数 LARNGDM、传递函数 LOGSIG（在隐藏层）和 PURELIN（在输出层）以及 10 个隐藏层神经元的结构具有最高相关性（R=0.996）和最低均方误差（4.405），是最佳的 ANN 结构。实验数据与 ANN 模型预测数据之间的一致性表明，在不同条件下，CR 吸附到 AKNPs 的吸附过程行为可以通过 ANN 模型来估计。通过将数据拟合到伪一级、伪二级、Elovich 和内扩散模型来研究吸附动力学。结果表明，吸附动力学符合伪二级模型，并由几个步骤控制。通过将数据拟合到 Langmuir、Freundlich 和 Temkin 等温线模型来研究不同温度下的吸附等温线。Langmuir 模型的 R 值大于 0.9，并且在四个温度中的三个温度中具有最高值，表明吸附等温线最符合 Langmuir 模型，最大吸附容量估计超过 150mg/g。热力学研究表明，CR 吸附到 AKNPs 是一个自发和吸热的过程，是物理化学吸附。所得结果表明，微波合成 AKNPs 具有从水溶液中去除有机染料的潜在应用。
