Abstract Dibutyl phthalate (DBP) is a prevalent endocrine-disrupting plasticizer known for its high bioaccumulation potential, posing substantial environmental and public health risks. To address the demand for efficient DBP detection, molecularly imprinted polymer (MIP) nanospheres were synthesized via precipitation polymerization using methacrylic acid (MAA) as the optimal functional monomer. Monodisperse MIP nanospheres with uniform morphology were successfully prepared under systematically optimized conditions (75 mL acetonitrile, 60 °C, 24 h), as verified by scanning electron microscopy (SEM). Fourier-transform infrared (FT-IR) spectroscopy confirmed successful DBP imprinting through specific monomer-template interactions. The synthesized MIP nanospheres were subsequently incorporated into electrospun polyacrylonitrile (PAN) nanofibers, yielding molecularly imprinted nanofibers (MINFs) with an optimized diameter of 480 ± 15 nm under carefully controlled electrospinning conditions. (PAN concentration 15 wt%, applied voltage +16/–2.5 kV, solution flow rate 0.8 mL/h). The DBP adsorption capacity of the optimized MINFs reached 16.79 mg/g, which was 2.1-fold higher than that of non-imprinted nanofibers (NINFs). Furthermore, the composite Fibers exhibited significantly enhanced adsorption selectivity for DBP compared with structural analogs, showing 1.36-fold and 2.01-fold increases over diisobutyl phthalate (DIBP) and dioctyl phthalate (DOP), respectively. This work establishes an effective and scalable approach combining molecular imprinting and electrospinning techniques, offering advanced material platforms for rapid on-site detection and selective removal of environmental contaminants.
Jun ZhuGuanghua ZhangTing ShangWei Xiong
Yinan ZengMin ZhangKefu PengZu ManLu’an GuoWenping LiuShilei XiePeng LiuDong XieShoushan WangFaliang Cheng
Jinjie YouHua LiuRongrong ZhangQiao-Fen PanAili SunZeming ZhangXizhi Shi
Jinjie YouHua LiuRongrong ZhangQiao-Fen PanAili SunZeming ZhangXizhi Shi
Zhaohui ZhangLijuan LuoRong CaiHongjun Chen