Arak University Colloid & Nanoscience Journal 2980-9215 3 3 2025 11 01 Application of nanocomposite-based nanosensors for rapid detection of heavy metal contamination in aquaculture: a review 639 651 731481 10.66224/CNJ.3.3.639 EN Hassan Saydi Department of Chemistry, Sa. C., Islamic Azad University, Sanandaj, Iran Alireza Mobarhan Fard Department of Fisheries, Sa. C., Islamic Azad University, Sanandaj, Iran. 0000-0003-3030-6839 Journal Article 2025 06 09 Heavy metal contamination in aquaculture systems poses significant risks to aquatic organisms and human consumers. Although traditional techniques such as atomic absorption spectroscopy and inductively coupled plasma mass spectrometry deliver high sensitivity, they are costly, time-intensive, and reliant on complex laboratory infrastructure. Recent nanotechnology advances have produced nanocomposite-based nanosensors offering high sensitivity, rapid response, portability, and on-site, real-time detection of multiple heavy metal ions. By integrating nanomaterials—graphene, carbon nanotubes, metal–organic frameworks, and metal nanoparticles—these nanosensors achieve enhanced electrical conductivity, large surface area, chemical stability, and selective binding sites for trace-level detection of Pb, Cd, Hg, and As in aquaculture waters. This review examines developments since 2022 in fabrication methods and sensing mechanisms (electrochemical, optical, and piezoelectric), evaluating performance metrics including detection limits down to ppb, response times under 60 s, high selectivity, and operational stability. Specifically, electrochemical sensors achieve LODs ≤ 1 ppb, optical devices enable multiplexed ion analysis, and piezoelectric platforms show robustness in high-organic matrices. Field trials demonstrate recoveries of 90–110% but reveal persistent issues with sensor fouling, matrix interferences, compliance with regulatory standards, and device miniaturization. Emerging solutions such as antifouling surface coatings, inline calibration, and wireless data transfer are discussed. Finally, integration with artificial intelligence (AI) enables predictive analytics and automated decisions in smart aquaculture platforms. By identifying current limitations and future directions, this review highlights the transformative potential of nanocomposite-based nanosensors to provide robust, sensitive, and sustainable solutions for heavy metal monitoring and food safety in modern aquaculture. https://cnj.araku.ac.ir/article_731481_d7812d3ea56e8b099e7c4cdbd6076ddc.pdf