分子印迹聚合物
生化工程
环境友好型
纳米技术
计算机科学
绿色化学
组合化学
化学
工艺工程
材料科学
有机化学
分子
工程类
催化作用
选择性
超分子化学
生物
生态学
作者
Rafael Oliveira Martins,Ricardo Alves Bernardo,Lucas Santos Machado,Almir Custodio Batista,Lanaia Í. L. Maciel,Deborah V. A. de Aguiar,Flávio O. Sanches-Neto,João Victor Ataíde Oliveira,Rosineide C. Simas,Andréa Rodrigues Chaves
标识
DOI:10.1016/j.trac.2023.117285
摘要
Over the decades, molecularly imprinted polymers (MIPs) have been used to shed light on challenging and complex samples evaluation. Such a class of polymers functions as molecular receptors designed for precise target recognition, facilitated by the incorporation of binding sites that exhibit both chemical and steric complementarity to a template molecule employed in the synthesis process. MIPs have been reported as sorbent phases for miniaturized and integrated separation methods, and as modification substrates for ambient mass spectrometry methods (AMS) to overcome the analysis of complex sample matrices. However, most of the reported MIPs are originated from synthesis protocols that use a large number of toxic reagents and solvent volume, leading to some non-eco-friendly methodologies. Because of the global concern about green chemistry practice, the literature has pointed out the adaptation of traditional synthesis protocols, and the introduction of green synthesis strategies. Moreover, the use of computational modeling has been reported as a potential approach for reducing the need for experimental trial-and-error synthesis procedures, thus, minimizing material waste. Therefore, this review describes the application of green analytical approaches for MIPs obtention, including an overview of traditional, alternative synthesis methodologies, and the use of computational modeling for waste reduction. Furthermore, this review study also discusses some recent reports from the literature concerning the application of MIPs as sorbent phase in miniaturized integrated separation methods and as modification substrate for AMS methodologies, therefore, highlighting the potential combination between MIP and analytical methods in order to promote sustainable and eco-friendly approaches for different applications.
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