Highly Selective Pyrene-Anchored Halloysite Nanotube for Fluorometric Determination of 2,4,6-Trinitrophenol in Environmental and Food Samples


Sanko V., Ömeroğlu İ., Şenocak A., TÜMAY S. O.

ACS Omega, no.8, pp.7949-7963, 2025 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Publication Date: 2025
  • Doi Number: 10.1021/acsomega.4c08857
  • Journal Name: ACS Omega
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Directory of Open Access Journals
  • Page Numbers: pp.7949-7963
  • Middle East Technical University Affiliated: No

Abstract

2,4,6-Trinitrophenol (TNP) is explosive, toxic, ecological, and a human health hazard and is resistant to degradation. It can cause symptoms such as headache, loss of appetite, dizziness, fever, nausea, diarrhea, and vomiting when inhaled. In this study, we aimed to develop a new halloysite nanotube anchored with pyrene moieties (HNT@Py) for the sensitive determination of TNP in soil, wastewater, and food samples using fully aqueous media. The HNT@Py was characterized structurally, morphologically, and thermally by using FTIR, UV-vis, XRD, TGA, fluorescence, SEM, and TEM analyses. The detection conditions for the assay were investigated and optimized, including competitive species, incubation time, sensor concentration, photostability, and selectivity. The limit of detection (LOD) and limit of quantification (LOQ) for TNP were found to be 14.00 nmol L-1 and 42.00 nmol L-1 in the linear response of 0.04 μmol L-1 and 0.60 μmol L-1 (R2 = 0.9962), respectively. Validation of the current method was performed using the spike/recovery test and HPLC analyses, and it was subsequently utilized to successfully detect TNP with fluorescence in soil, food, and water samples. According to the obtained results, the suggested assay is dependent on the “turn-off” emission of HNT@Py with the PET mechanism between electron-deficient NACs and the electron-rich pyrene moieties. The sensor was found to be easy to use, extremely sensitive, and reliable in rapidly identifying TNP in real samples, displaying excellent flexibility and resilience. Additionally, detection membranes with regular morphology were obtained by the electrospinning method using HNT@Py nanostructures dispersed in the PCL matrix, and RGB changes were determined via a smartphone application.