摘要
为了研究固定床吸附刚果红的条件及模型,采用银耳和羊肚菌共发酵玉米秸秆制备吸附剂MTs。通过红外光谱、扫描电镜、比表面积及孔径分析对MTs进行表征。通过单因素试验和Box-Behnken方案设计,考察上样速度、pH值和NaCl质量浓度3个因素对饱和吸附量和穿透曲线的影响。基于人工神经网络建立固定床吸附模型。结果表明MTs由表面粗糙且有孔洞的秸秆和白腐菌丝共同组成,有羟基、氨基和羰基等活性官能团。MTs的平均孔径为36.5 nm,比表面积为8.36 m^(2)/g,孔容积为0.15 cm^(3)/g。上样速度和pH值对饱和吸附量的影响显著(p<0.05),NaCl质量浓度对饱和吸附量的影响极显著(p<0.01)。获得较优条件是上样速度0.78 mL/min, pH值7.98,NaCl质量浓度1.15 g/L,该条件下饱和吸附量达到281.2 mg。建立的模型可以模拟刚果红在MTs固定床的动态吸附过程,穿透曲线的试验值与模型拟合值的相关系数r> 0.95,差异不显著(p> 0.05)。研究结果可为吸附法处理刚果红染料废水提供一定参考。
Conditions and models of Congo red adsorption in a fixed bed were investigated in the present study. Adsorbent MTs were prepared by co-fermentation of Morchella sp. and Tremella fuciformis with corn straw. The physical and chemical properties of the MTs were analyzed by infrared spectroscopy, scanning electron microscopy and specific surface area and pore size analyzer, respectively. Effects of flow velocity, pH, and NaCl concentration on saturated adsorption capacity and breakthrough curve were investigated by single factor test and Box-Behnken design, respectively. The artificial neural network was used to establish an adsorption model of the fixed bed. The model was adopted to simulate the breakthrough curve of the fixed bed. Results show that MTs are composed of straw with a rough surface and holes and mycelia of white-rot fungi. MTs have hydroxyl groups, amino groups, carbonyl groups, and other active functional groups which could adsorb Congo red dye. The mean pore diameter, specific surface area, and pore volume of MTs are 36.5 nm, 8.36 m^(2)/g, and 0.15 cm^(3)/g, respectively. Flow velocity and pH were significant on saturation adsorption capacity of the fixed bed, and the p-value of the analysis of variance was less than 0.05. The NaCl concentration was very significant on the saturation adsorption capacity, and the p-value of the analysis of variance was less than 0.01. The optimal conditions were flow velocity of 0.78 mL/min, pH value of 7.98, NaCl concentration of 1.15 g/L, respectively. Under these conditions, the saturated adsorption capacity of the fixed bed achieved 281.2 mg. The model which was established by an artificial neural network could simulate the dynamic adsorption process of Congo red in the fixed bed. Correlation coefficients of the experimental value and the model fitting value were more than 0.95. There was no significant difference between the experimental value and the model fitting value, and the p-value of the t-test was more than 0.05. The results provide some references for th
作者
李慧星
许彬
张菲
陈旭升
罗建成
LI Hui-xing;XU Bin;ZHANG Fei;CHEN Xu-sheng;LUO Jian-cheng(Henan Key Laboratory of Industrial Microbial Resources and Fermentation Technology,Nanyang Institute of Technology,Nanyang 473004,Henan,China;School of Biological and Chemical Engineering,Nanyang Institute of Technology,Nanyang 473004,Henan,China;School of Bioengineering,Jiangnan University,Wuxi 214122,Jiangsu,China)
出处
《安全与环境学报》
CAS
CSCD
北大核心
2022年第1期443-450,共8页
Journal of Safety and Environment
基金
河南省自然科学基金项目(182300410151)
河南省工业微生物资源与发酵技术重点实验室开放课题(HIMFT20200206)
2020年度南阳理工学院交叉科学研究项目(南理工院文[2020]72号)。
关键词
环境工程学
固定床
人工神经网络
玉米秸秆
刚果红
environmental engineering
fixed bed
artificial neural network
corn straw
Congo red
