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Nano-magnetic walnut shell-rice husk for Cd(II) sorption: design and optimization using artificial intelligence and design expert

机译:用于Cd(II)吸附的纳米磁性核桃壳-稻壳:使用人工智能和设计专家进行设计和优化

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摘要

This study attempted to investigate the use of nanomagnetic activated carbon prepared from walnut shell and rice husk wastes for removal of Cd(II) from aqueous solution via application of ANN and design expert as adsorbent preparation design and optimization tools. The novel adsorbent was characterized using SEM, FTIR, EDS and BET. The result from 2-level factorial design expert revealed 78.58% Cd(II) sorption efficiency could be achieved for adsorbent prepared at optimum calcination temperature, calcination time, SS-RH mixing ratio and magnetite loading of 859.20 °C, 2.32 h, 2.54 and 5.56 wt% respectively. Sensitivity analysis by both proposed methodologies revealed calcination temperature as most influential factor in adsorbent preparation. Average relative errors and R2 values of 1.2931% and 4.806%; and 0.9967 and 0.9055 obtained respectively for developed ANN model with 4-9-1 architecture and 2-level factorial design expert revealed ANN model as better prediction and optimization tool for Cd(II) sorption using NM-WS-RH-AC. Laboratory analysis revealed presence of –OH, –NH and COO groups on adsorbent surface; presence of Cd(II) after adsorption; change in adsorbent textural and morphological structure after Cd(II) adsorption; and increase in its surface area and average pore diameter due to magnetization. Average relatively stable desorption strength of 62.74% towards Cd(II) was exhibited by adsorbent for four consecutive cycles using 0.1M HNO3. Prepared adsorbent is effective in removing Cd(II) from solution than commercial activated carbon with economically viable regeneration attribute.
机译:这项研究试图通过使用人工神经网络和设计专家作为吸附剂的设计和优化工具,研究利用核桃壳和稻壳废料制备的纳米磁性活性炭从水溶液中去除Cd(II)。使用SEM,FTIR,EDS和BET对新型吸附剂进行了表征。 2级析因设计专家的结果表明,在最佳煅烧温度,煅烧时间,SS-RH混合比和磁铁矿负载为859.20°C,2.32 h,2.54和0.54的条件下,制备的吸附剂可达到78.58%的Cd(II)吸附效率。分别为5.56重量%。两种拟议方法的敏感性分析均表明煅烧温度是吸附剂制备中最重要的影响因素。平均相对误差和R 2 值分别为1.2931%和4.806%;分别从开发的具有4-9-1架构的ANN模型和2级析因设计专家获得的0.9967和0.9055中得出,ANN模型是使用NM-WS-RH-AC吸附Cd(II)的更好的预测和优化工具。实验室分析表明,吸附剂表面存在–OH,–NH和COO -基团。吸附后存在Cd(II); Cd(II)吸附后吸附剂质地和形态结构的变化;并由于磁化而增加其表面积和平均孔径。使用0.1M HNO3的吸附剂连续四个循环显示出对Cd(II)的平均相对稳定的解吸强度为62.74%。所制备的吸附剂比具有经济上可行的再生特性的市售活性炭更能有效地从溶液中去除Cd(II)。

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