This review highlights advancements in electrochemical and photoelectrochemical sensors for atrazine, pointing to their sensitive detection and rapid monitoring capabilities.
Atrazine, used in large quantities of the triazine class of herbicides, is recognized for its difficulty in degradation, high mobility, and significant environmental residue, classifying it among the environmental hormone-like substances. Its propensity to generate highly toxic metabolites and its potential carcinogenicity underscore the imperative need for sensitive and selective detection methods in environmental matrices. Traditional analytical techniques offer high sensitivity and selectivity but are often limited by their time-consuming nature, high costs, and operational complexity. These traditional methods, while effective, are not always suitable for rapid, on-site monitoring. In contrast, sensors based on various nanomaterials and sensing strategies for electrochemical and photoelectrochemical detection have emerged as promising alternatives. These sensors are distinguished by their sensitive responses, rapid detection capabilities, real-time monitoring, and portable design, which facilitate the swift and precise identification of environmental contaminants. This review focuses on key nanomaterials and sensing strategies, including immunosensors, aptasensors, molecular imprinting sensors, and self-powered sensors, all of which hold significant promise for enhancing the performance of atrazine detection sensors. This review comprehensively compiles the prevalent detection methodologies for atrazine over the past half-decade, delving into their foundational principles, recognition mechanisms, categorization, and a critical evaluation of their merits and demerits. It also encapsulates the advancements in the detection of atrazine residues and offers an in-depth analysis of the materials, recognition elements, and sensing strategies that are frequently employed. Furthermore, the review provides an outlook on emerging trends and prospective directions in novel sensor development.
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Wang et al. (2025) studied this question.
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