Pharmaceuticals and personal care products (PPCPs) are emerging pollutants and have received increasing attention in recent years. The regeneration of conventional adsorption materials used to remove PPCPs involves the desorption of secondary organic pollution, which is harmful and problematic. In this work, the impact of pH-responsive magnetic Janus particle catalysts on PPCPs’ performance of high-efficiency adsorption and degradation was studied. Magnetic core-shell Fe₃O₄@SiO₂ nanoparticles were prepared via the STÖBER method. Polylactic acid (PLA) was grafted using a template method, and the polymerization of pH-responsive monomer 2-(diethylamino)ethyl methacrylate (DEAEMA) was initiated to obtain the pH-responsive magnetic Janus particles (Janus-Fe-P). SEM (scanning electron microscopy), particle size analysis, TEM (transmission electron microscopy), and N₂ adsorption-desorption tests were used to characterize the morphology, magnetic property, and pH-responsive performance of the Janus-F-P. The Janus-F-P was used in the adsorptions of two kinds of representative PPCPs, i.e., hydrophilic (antipyrine) and hydrophobic (tiamulin), under neutral conditions. Commercially available NORIT CN activated carbon was used for comparison, and the adsorption results showed that the adsorption efficiency of Janus particles was higher than that of activated carbon. Therefore, Janus-F-P could be used to efficiently catalyze the degradation of adsorbed PPCPs in the Fenton/hydroxylamine system. The removal rate of PPCPs was above 85 % after repeated use (5 times).

药品和个人护理产品 (PPCP) 是新兴的污染物，近年来受到越来越多的关注。用于去除PPCPs的常规吸附材料的再生涉及二次有机污染的解吸，这是有害且有问题的。在这项工作中，研究了pH响应磁性Janus粒子催化剂对PPCPs高效吸附和降解性能的影响。磁性核壳Fe ₃ O ₄ @SiO ₂纳米粒子是通过 STÖBER 方法制备的。采用模板法接枝聚乳酸（PLA），引发pH响应单体甲基丙烯酸2-（二乙氨基）乙酯（DEAEMA）聚合，得到pH响应磁性Janus粒子（Janus-Fe-P）。SEM（扫描电子显微镜）、粒度分析、TEM（透射电子显微镜）和 N ₂吸附-解吸测试用于表征 Janus-FP 的形态、磁性和 pH 响应性能。Janus-FP 用于在中性条件下吸附两种代表性的 PPCP，即亲水性（安替比林）和疏水性（泰妙菌素）。使用市售的NORIT CN活性炭进行对比，吸附结果表明Janus颗粒的吸附效率高于活性炭。因此，Janus-FP 可用于有效催化 Fenton/羟胺体系中吸附的 PPCPs 的降解。重复使用（5次）后，PPCPs的去除率在85%以上。