A novel molecularly imprinted quartz crystal microbalance sensor for fenamiphos determination based on boron-sulphur co-doped ultra-thin graphitic carbon nitride-incorporated Cu-MOFs


Akıcı Ş. Y., Düzel A., Alptekin Ü. M., Bekerecioğlu S., Polat İ., Atar N., ...Daha Fazla

Analytical Methods, 2026 (SCI-Expanded, Scopus) identifier identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1039/d5ay02149a
  • Dergi Adı: Analytical Methods
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, MEDLINE
  • Ankara Üniversitesi Adresli: Evet

Özet

Fenamiphos (FEN), an organophosphorus insecticide, has been frequently used in recent years to control many nematode pests. Nonetheless, its serious adverse effects have currently raised concerns about human health and the ecological environmental safety. In the present study, a novel flow injection-type portable quartz crystal microbalance (QCM) sensor based on a boron and sulphur co-doped ultra-thin graphitic carbon nitride (g-C3N4)-incorporated Cu-MOF (BS-g-C3N4-CuMOF) nanocomposite was developed and used for FEN determination in apple juice samples. For this, the BS-g-C3N4-CuMOF nanocomposite was prepared via an in situ solvothermal procedure with high synthesis yields. Then, a molecularly imprinted QCM sensor based on the BS-g-C3N4-CuMOF nanocomposite was prepared using methacryloylamidoglutamic acid (MAGA) as a monomer and N,N′-azobisisobutyronitrile (AIBN) as an initiator via UV polymerization. This QCM sensor revealed a linearity of 1.0 × 10−9–2.0 × 10−8 mol L−1 with a limit of detection (LOD) of 3.3 × 10−10 mol L−1 for the FEN molecule, suggesting the successful development of the sensitive molecularly imprinted QCM sensor. The prepared sensitive molecularly imprinted QCM sensor was applied to an apple juice sample with high recovery. Moreover, the high selectivity of the molecularly imprinted QCM sensor was confirmed in the presence of competing agents in the apple juice sample, and the prepared QCM sensor was shown to detect FEN at least 5 times more selectively than the other competing agents. In addition, the proposed sensor was validated in correlation with standard high-end measurements like GC-MS, and there was no significant difference between the results of the proposed sensor and GC-MS method. The low relative standard deviation (RSD) value of 20 independent QCM signals also suggested the high reproducibility of the QCM sensor. Finally, its high repeatability and reusability are presented herein in detail.