Simultaneous removal of three pollutants (diethyl phthalate, butylated hydroxy anisole and butylated hydroxy toluene) that appear in plastic industries’ wastewater was the aim of this study. These compounds have harmful effects on human health. The adsorbent, Sesamum indicum seeds’ waste, is a natural adsorbent which was obtained freely and abundantly from a local market after being oil-pressed. For performing the treatment process, the pretreated adsorbent was put in contact with a solution of the compounds of interest. The effect of variable parameters like the type of pretreatment solvent, pretreatment time, pH of solution, dosage of adsorbent, adsorption time and the concentration of solution containing the pollutants was investigated. The equilibrium isotherm data were analyzed too. Moreover, an artificial neural network model was progressed to anticipate the adsorption efficiency of the pollutants. The results indicated that the obtained data have a good predictive capability (R² = 0.9940). The optimum pretreatment organic solvent was found to be ethyl acetate, and the optimum pretreatment time was 10 min. Furthermore, when the adsorbent dosage and adsorption time increased, the adsorption efficiency enhanced and reached a constant limit. The optimum pH was found to be 9 and the decrease in pollutants’ concentration resulted in an increase in wastewater treatment efficiency. The isotherm data for all studied pollutants were fitted well with Langmuir isotherm.

中文翻译：

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通过在预处理的废料上的吸附过程，从水性介质中同时消除邻苯二甲酸二乙酯，丁基化羟基甲苯和丁基化羟基茴香醚；等温线研究和神经网络建模

本研究的目的是同时去除塑料行业废水中出现的三种污染物（邻苯二甲酸二乙酯，丁基化羟基茴香醚和丁基化羟基甲苯）。这些化合物对人体健康有害。吸附剂芝麻种子的废料是一种天然吸附剂，经压榨后可从当地市场免费大量获取。为了进行处理过程，使预处理的吸附剂与目标化合物的溶液接触。研究了预处理溶剂的种类，预处理时间，溶液的pH，吸附剂的用量，吸附时间和含污染物溶液的浓度等变量参数的影响。还分析了平衡等温线数据。此外，建立了人工神经网络模型以预测污染物的吸附效率。结果表明，所获得的数据具有良好的预测能力（R ² = 0.9940）。发现最佳的预处理有机溶剂为乙酸乙酯，并且最佳的预处理时间为10分钟。此外，当吸附剂剂量和吸附时间增加时，吸附效率提高并达到恒定极限。发现最佳pH为9，污染物浓度的降低导致废水处理效率的提高。所有研究的污染物的等温线数据都与Langmuir等温线拟合得很好。