Sensitive Coatings Based on Molecular-Imprinted Polymers for Triazine Pesticides’ Detection

Author:

Latif Usman12ORCID,Yaqub Sadaf1,Dickert Franz L.1ORCID

Affiliation:

1. Department of Analytical Chemistry, University of Vienna, Waehringer Str. 38, A-1090 Vienna, Austria

2. Interdisciplinary Research Centre in Biomedical Materials, COMSATS University Islamabad-Lahore Campus, Lahore 54600, Pakistan

Abstract

Triazine pesticide (atrazine and its derivatives) detection sensors have been developed to thoroughly check for the presence of these chemicals and ultimately prevent their exposure to humans. Sensitive coatings were designed by utilizing molecular imprinting technology, which aims to create artificial receptors for the detection of chlorotriazine pesticides with gravimetric transducers. Initially, imprinted polymers were developed, using acrylate and methacrylate monomers containing hydrophilic and hydrophobic side chains, specifically for atrazine, which shares a basic heterocyclic triazine structure with its structural analogs. By adjusting the ratio of the acid to the cross-linker and introducing acrylate ester as a copolymer, optimal non-covalent interactions were achieved with the hydrophobic core of triazine molecules and their amino groups. A maximum sensor response of 546 Hz (frequency shift/layer height equal to 87.36) was observed for a sensitive coating composed of 46% methacrylic acid and 54% ethylene glycol dimethacrylate, with a demonstrated layer height of 250 nm (6.25 kHz). The molecularly imprinted copolymer demonstrated fully reversible sensor responses, not only for atrazine but also for its metabolites, like des-ethyl atrazine, and structural analogs, such as propazine and terbuthylazine. The efficiency of modified molecularly imprinted polymers for targeted analytes was tested by combining them with a universally applicable quartz crystal microbalance transducer. The stable selectivity pattern of the developed sensor provides an excellent basis for a pattern recognition procedure.

Funder

University of Vienna

Publisher

MDPI AG

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