分子印迹聚合物
纳米技术
软件可移植性
材料科学
计算机科学
生化工程
化学
催化作用
生物化学
工程类
选择性
程序设计语言
作者
Ayushi Singhal,Mohd Abubakar Sadique,Neeraj Kumar,Shalu Yadav,Pushpesh Ranjan,Arpana Parihar,Raju Khan,Ajeet Kaushik
标识
DOI:10.1016/j.jece.2022.107703
摘要
Antibiotics are used extensively to avert or cure bacterial infections in humans, plants, and animals. The prevalent disbursement and superfluous usage of antibiotics led to environmental and health concerns globally. The scientific community shifts research from conventional to new and advanced analytical techniques that can detect antibiotics at very low concentrations. Timely and organized assessment of the emerging scientific advancements in the field of biosensing is vital to develop new advanced techniques for the detection of antibiotics. In this context, molecularly imprinted polymers (MIPs) can imitate enzymes, antibodies, and other biorecognition elements with high specificity, rich affinity, and robustness. Moreover, cheap, and simple synthesis strategies, along with reproducibility and stability emphasize the benefits of MIPS. Although MIPs have numerous advantages such as selective binding sites, high stability, and specificity, there are some bottlenecks like low conductivity and low electro-catalytic activity. To enhance their analytical performance and overcome these limitations, MIPs have been integrated with functional carbon nanomaterials (CNMs). The CNMs provide highly conductive, specific, and selective substrates for electrochemical antibiotic sensing. The CNMs decorated MIPs based electrochemical sensors possess numerous advantages including user-friendly, portability, point-of-care (POC) detection with highly sensitive, selective, and rapid outcomes. This review systematically explores the emergence of MIPs and CNMs based MIPs for electrochemical sensing of antibiotics along with the related challenges and future perspectives carefully and critically. The outcomes of this report pave the way for developing portable, cost-effective, easy to use and POC devices for the detection of antibiotics for environmental monitoring.
科研通智能强力驱动
Strongly Powered by AbleSci AI