Zhang Wei, Li Qian, Cong Jingxiang, Wei Bofeng, Wang Shaoyan
School of chemical engineering, University of science and technology, Liaoning, Anshan 114051, China.
Liaoning Provincial Key Laboratory of Fine Separation Technique, University of Science and Technology, Anshan 114051, China.
Polymers (Basel). 2018 Feb 22;10(2):216. doi: 10.3390/polym10020216.
In this article, the molecularly imprinted polymers (MIPs) of ginsenoside Re (Re) were synthesized by suspension polymerization with Re as the template molecule, methacrylic acid (MAA) as the functional monomers, and ethyl glycol dimethacrylate (EGDMA) as the crosslinker. The MIPs were characterized by Fourier transform infrared spectroscopy (FTIR), Field emission scanning electron microscopy (FESEM), and surface porosity detector, and the selective adsorption and specific recognition of MIPs were analyzed using the theory of kinetics and thermodynamics. The experimental results showed that compared with non-imprinted polymers (NIPs), MIPs had a larger specific surface area and special pore structure and that different from the model of NIPs, the static adsorption isotherm of MIPs for Re was in good agreement with the model based on the two adsorption properties of MIPs. The curves of the adsorption dynamics and the lines of kinetic correlation indicate that there was a fast and selective adsorption equilibrium for Re because of the affinity of MIPs to the template rather than its analogue of ginsenoside Rg1 (Rg1). The study of thermodynamics indicate that the adsorption was controlled by enthalpy and that MIPs had higher enthalpy and entropy than NIPs, which contributed to the specific recognition of MIPs.
在本文中，以人参皂苷Re（Re）为模板分子、甲基丙烯酸（MAA）为功能单体、乙二醇二甲基丙烯酸酯（EGDMA）为交联剂，通过悬浮聚合法合成了人参皂苷Re的分子印迹聚合物（MIPs）。采用傅里叶变换红外光谱（FTIR）、场发射扫描电子显微镜（FESEM）和表面孔隙率检测器对MIPs进行了表征，并运用动力学和热力学理论分析了MIPs的选择性吸附和特异性识别。实验结果表明，与非印迹聚合物（NIPs）相比，MIPs具有更大的比表面积和特殊的孔结构，且与NIPs模型不同，MIPs对Re的静态吸附等温线与基于MIPs两种吸附特性的模型吻合良好。吸附动力学曲线和动力学相关线表明，由于MIPs对模板的亲和力而非其类似物人参皂苷Rg1（Rg1），MIPs对Re存在快速且选择性的吸附平衡。热力学研究表明，吸附受焓控制，且MIPs的焓和熵高于NIPs，这有助于MIPs的特异性识别。
