Pyrene-Modified Carbon Nanodot as Fluorescent Nanosensor for Nitroaniline Herbicide Detection and Smartphone-Assisted RGB Analysis using Hydrogel Detection Kits

Abstract

Nitroaniline herbicides are widely used to combat broadleaf weeds, yet their high toxicity and persistence raise serious environmental and health concerns. Effective and sensitive detection of these herbicides in complex matrices such as soil is therefore crucial. In this study, a novel pyrene-modified carbon nanodot (4) was developed and used as a fluorescent nanosensor for the sensitive detection of nitroaniline herbicides in soil samples. The chemical, thermal, and morphological characterization of 4 was conducted using FT-IR, UV-Vis, fluorescence spectroscopy, TEM, and particle size analysis. Detection conditions were optimized by evaluating parameters such as selectivity, photostability, sensor concentration, interaction time, and interference from competitive species. The detection limit (LOD) and quantification limit (LOQ) were found to be as low as 1.50 nmol L⁻¹ and 4.97 nmol L⁻¹, respectively, with linear responses observed at nanomolar levels and high correlation coefficients. The proposed fluorometric method was validated through spike tests and GC-MS analyses, and successfully applied to detect nitroaniline herbicides via a fluorescence “turn-off” response in soil samples. The sensing mechanism was attributed to a photoinduced electron transfer process between the herbicides and 4. The sensor demonstrated high sensitivity, selectivity, and rapid detection capability. Additionally, hydrogel detection kits were fabricated by immobilizing 4 in a gelatin matrix, with Red-Green-Blue (RGB) color changes monitored through a smartphone application.

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Article information

Article type
Paper
Submitted
07 Jun 2025
Accepted
07 Aug 2025
First published
08 Aug 2025

Analyst, 2025, Accepted Manuscript

Pyrene-Modified Carbon Nanodot as Fluorescent Nanosensor for Nitroaniline Herbicide Detection and Smartphone-Assisted RGB Analysis using Hydrogel Detection Kits

D. Özturk, V. ŞANKO, A. Khataee, E. Demirbaş, M. Durmuş, S. Yeşilot, Z. Kılıç, U. Demirbas, A. Şenocak and S. O. Tümay, Analyst, 2025, Accepted Manuscript , DOI: 10.1039/D5AN00624D

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