Abstract：
In the present study, biosynthesized ZnO nanoparticles in food wastewater extract (FWEZnO NPs) was used in the photocatalytic degradation of real samples of printing ink wastewater. FWEZnO NPs were prepared using green synthesis methods using a composite food waste sample (2 kg) consisted of rice 30%, bread 20 %, fruits 10 %, chicken 10 %, lamb 10%, and vegetable 20%. The photocatalysis process was optimized using response surface methodology (RSM) as a function of time (15-180 min), pH 2-10 and FWEZnO NP (20-120 mg/100 mL), while the print ink effluent after each treatment process was evaluated using UV-Vis-spectrophotometer. The behaviour of printing ink wastewater samples for photocatalytic degradation and responses for independent factors were simulated using feed-forward neural network (FFNN). FWEZnO NPs having 62.48 % of the purity with size between 18 and 25 nm semicrystalline nature. The main functional groups were -CH, CH2, and -OH, while lipid, carbon-hydrogen stretching, and amino acids were the main component in FWEZnO NP, which contributed to the adsorption of ink in the initial stage of photocatalysis. The optimal conditions for printing ink wastewater were recorded after 17 min, at pH 9 and with 20 mg/100 mL of FWEZnO NPs, at which the decolorization was 85.62 vs. 82.13% of the predicted and actual results, respectively, with R2 of 0.7777. The most significant factor in the photocatalytic degradation was time and FWEZnO NPs. The FFNN models revealed that FWEZnO NPs exhibit consistency in the next generation of data (large-scale application) with an low errors (R2 0.8693 with accuracy of 82.89%). The findings showing a small amount of catalyst is needed for effective breakdown of dyes in real samples of printing ink wastewater.
摘要：
在本研究中,生物合成的ZnO纳米颗粒在食品废水提取物（FWEZnONPs）用于光催化降解实际样品的印刷油墨废水。使用绿色合成方法，使用由大米组成的复合食物垃圾样品（2kg），面包20%,水果10%,鸡肉10%,羔羊10%，蔬菜20%使用响应面方法（RSM）作为时间（15-180分钟）的函数来优化光催化过程，pH2-10和FWEZnONP（20-120mg/100mL），同时使用UV-Vis-分光光度计评估每个处理过程后的印刷油墨流出物。使用前馈神经网络（FFNN）模拟了油墨废水样品的光催化降解行为和对独立因素的响应。FWEZnONP具有62.48%的纯度,尺寸在18和25nm之间的半结晶性质。主要官能团是-CH，CH2和-OH,而脂质，碳-氢拉伸，氨基酸是FWEZnONP的主要成分，这有助于光催化初期油墨的吸附。17分钟后记录了印刷油墨废水的最佳条件，在pH9和20mg/100mL的FWEZnONPs下，其中脱色为85.62vs.预测结果和实际结果的82.13%，分别,R2为0.7777。光催化降解的最重要因素是时间和FWEZnONPs。FFNN模型显示，FWEZnONP在下一代数据（大规模应用）中具有较低的误差（R20.8693，精度为82.89％）。结果表明，需要少量的催化剂才能有效分解印刷油墨废水的实际样品中的染料。
