Magnetic Nanoparticles Molecularly Imprinted Polymers: A Review

Nursyahera Azreen Ramin,Muggundha Raoov Ramachandran,Noorashikin Md Saleh, Zalilah Murni Mat Ali,Saliza Asman

Current Nanoscience(2023)

引用 4|浏览2
暂无评分
摘要
The molecularly imprinted polymers (MIPs) technology, which has been around since the 1970s, has grown in popularity in recent decades. MIPs have shown to be a useful approach for determining target molecules in complicated matrices containing other structurally similar and related chemicals. Despite MIPs having intrinsic polymer features such as stability, robustness, and low-cost production, traditional MIPs have a number of drawbacks. Surface molecular imprinting appears to be an alternative approach that can address some of the drawbacks of traditional MIP by anchoring shells to the surface of matrix carriers such as nanoparticles. The incorporation of nanoparticles into the polymeric structure of MIPs can improve their properties or provide novel capabilities. Magnetic nanoparticles have been widely explored for their separation and extraction capability. Magnetic components in MIP can help develop a regulated rebinding process, allowing magnetic separation to substitute centrifugation and filtration stages in a simple, cost-effective strategy. Polymers are created directly on the surface of a magnetic substrate to create a unique material termed magnetic molecularly imprinted polymer (MMIP). These materials have been widely used to extract molecules from complex matrices in a variety of applications, especially in environmental, food, and biological studies. This paper seeks to summarize and discuss the nanoparticle synthesis and magnetic nanoparticle combination in the MIP preparation. The novel applications of MMIP in environmental, food and biological analyses are also discussed in this paper.
更多
查看译文
关键词
Magnetic nanoparticles,surface imprinted polymer,molecularly imprinted polymers,environmental analysis,food analysis,centrifugation,filtration
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要