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用人工神经网络预测铁修饰活性炭对甲基橙的去除。

Prediction of methyl orange removal by iron decorated activated carbon using an artificial neural network.

机构信息

Department of Polymer Science and Technology, University of Calcutta, Kolkata, India.

Department of Chemical Engineering, Jadavpur University, Kolkata, India.

出版信息

Environ Technol. 2021 Sep;42(21):3288-3303. doi: 10.1080/09593330.2020.1725648. Epub 2020 Feb 11.

DOI:10.1080/09593330.2020.1725648
PMID:32037982
Abstract

Date Stones were used as a bio-degradable waste source for preparing iron impregnated activated carbon. The prepared activated carbon-containing oxides of iron were characterized using SEM, XRD, FTIR, and BET. The specific surface area of the iron decorated activated carbon was 738.65 m/g. The XRD confirmed the presence of magnetite and hematite while the SEM images assured the presence of pores. The prepared activated carbon was used to remove methyl orange from wastewater. Genetic Algorithm was used to develop a model which could predict the removal efficiency of the dye. The ANN model was validated and the effect of different parameters like adsorbent dosage (0.1-1 g/L), initial dye concentration (2-20 mg/L), pH (2-11), time (10-55 min) and temperature (30-75°C) was estimated both experimentally and predicted using the model. The adsorption process follows the Freundlich isotherm and pseudo-second-order kinetic model. The values of 1/ and obtained from the Freundlich isotherm designate good adsorption capacity. Both experimental and model-predicted data agrees with the kinetic model. The adsorption rate is proportionate to the square of the number of vacant adsorption sites. From the thermodynamic study, the positive worth of Δ° indicates the energy-absorbing nature of the surface assimilation method and the process is endothermic in nature. The low values of each Δ° (-200 to 0 kJ/mol) and Δ° correspond to physical surface assimilation. A positive worth of Δ° reflects the inflated randomness at the solid-aqueous interface with some structural changes in adsorbate and adsorbent.

摘要

日期石被用作生物可降解废物源来制备铁浸渍活性炭。使用 SEM、XRD、FTIR 和 BET 对含氧化铁的活性炭进行了表征。铁修饰活性炭的比表面积为 738.65 m/g。XRD 证实了磁铁矿和赤铁矿的存在,而 SEM 图像则确保了孔隙的存在。制备的活性炭用于从废水中去除甲基橙。遗传算法用于开发可预测染料去除效率的模型。对 ANN 模型进行了验证,并通过实验和模型预测了不同参数(如吸附剂用量(0.1-1 g/L)、初始染料浓度(2-20 mg/L)、pH 值(2-11)、时间(10-55 min)和温度(30-75°C))的影响。吸附过程遵循 Freundlich 等温线和准二级动力学模型。从 Freundlich 等温线获得的 1/ 和 值表示良好的吸附能力。实验和模型预测数据均与动力学模型一致。吸附速率与空位吸附位的平方成正比。从热力学研究中可以看出,Δ°的正值表明表面同化方法的能量吸收性质,该过程本质上是吸热的。每个 Δ°(-200 到 0 kJ/mol)和 Δ°的低值反映了吸附质和吸附剂的物理表面同化。Δ°的正值反映了固-液界面上的随机膨胀增加,并伴有吸附物和吸附剂的某些结构变化。

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