Kohzadi Shadi, Marzban Nader, Zandsalimi Yahya, Godini Kazem, Amini Nader, Harikaranahalli Puttaiah Shivaraju, Lee Seung-Mok, Zandi Shiva, Ebrahimi Roya, Maleki Afshin
Environmental Health Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran.
Student Research Committee, Kurdistan University of Medical Sciences, Sanandaj, Iran.
Heliyon. 2023 Oct 20;9(11):e21258. doi: 10.1016/j.heliyon.2023.e21258. eCollection 2023 Nov.
This study investigated the efficiency of hydrochar derived from hydrothermal fulvification of wheat straw in adsorbing malachite green (MG) dye. The characterizations of the hydrochar samples were determined using various analytical techniques like SEM, EDX, FTIR, X-ray spectroscopy, BET surface area analysis, ICP-OES for the determination of inorganic elements, elemental analysis through ultimate analysis, and HPLC for the content of sugars, organic acids, and aromatics. Adsorption experiments demonstrated that hydrochar exhibited superior removal efficiency compared to feedstock. The removal efficiency of 91 % was obtained when a hydrochar dosage of 2 g L was used for 20 mg L of dye concentration in a period of 90 min. The results showed that the study data followed the Freundlich isotherms as well as the pseudo-second order kinetic model. Moreover, the determined activation energy of 7.9 kJ mol indicated that the MG adsorption was a physical and endothermic process that increased at elevated temperatures. The study also employed an artificial neural network (ANN), a machine learning approach that achieved remarkable R (0.98 and 0.99) for training and validation dataset, indicating high accuracy in simulating MG adsorption by hydrochar. The model's sensitivity analysis demonstrated that the adsorbent dosage exerted the most substantial influence on the adsorption process, with MG concentration, pH, and time following in decreasing order of impact.
本研究考察了小麦秸秆水热富里化制备的水炭对孔雀石绿（MG）染料的吸附效率。采用扫描电子显微镜（SEM）、能谱仪（EDX）、傅里叶变换红外光谱仪（FTIR）、X射线光谱仪、比表面积分析仪（BET）、电感耦合等离子体发射光谱仪（ICP - OES）测定无机元素、元素分析仪进行元素分析以及高效液相色谱仪（HPLC）测定糖、有机酸和芳烃含量等多种分析技术对水炭样品进行表征。吸附实验表明，与原料相比，水炭表现出更高的去除效率。当染料浓度为20 mg/L，水炭投加量为2 g/L，吸附时间为90 min时，去除率可达91%。结果表明，研究数据符合Freundlich等温线以及准二级动力学模型。此外，测定的活化能为7.9 kJ/mol，表明MG吸附是一个物理吸热过程，且在温度升高时吸附量增加。该研究还采用了人工神经网络（ANN）这一机器学习方法，其对训练数据集和验证数据集的决定系数R分别达到了0.98和0.99，表明在模拟水炭对MG的吸附方面具有较高的准确性。模型的敏感性分析表明，吸附剂投加量对吸附过程影响最大，其次是MG浓度、pH值和时间，影响程度依次降低。
