Multilayer surface plasmon resonance biosensor incorporating ZnO quantum dots and black phosphorus for food toxin detection
The importance of timely and accurate identification of aflatoxin is extremely high because of the severe effect on the safety of food and human health. Traditional methods of detection are usually time-consuming, complicated, and demand much preparation of samples, which restrict its applicability in the context of real-time and fast-paced monitoring. To address these shortcomings, this paper suggests a more improved surface plasmon resonance (SPR) biosensor to detect aflatoxins in sensitive and label-free. The sensor suggested in this paper will have a fixed wavelength of 633 nm and will identify minute changes in the refractive index of the material by which the sensor is sensing the medium by detecting changes in the angle of resonance. The sensor is designed based on a multilayer Kretschmann configuration whereby FK51A prism, a silver (Ag) metal layer, polymeric zinc oxide (ZnO) quantum dots (QDs), black phosphorus (BP) nanolayers, and the analyte medium are used. The Ag layer is optimized systematically within the thickness of 40–60 nm to achieve better resonance properties. The effects of ZnO QD and BP layers, as well as their combination, on the sensing performance, are also studied in a comparative analysis of the various sensor configurations, and the number of BP layers also is a topic of study. The sensor performance is measured against the main parameters like sensitivity, full width of half maximum (FWHM), quality factor (QF), signal-to-noise ratio (SNR), figure of merit (FOM), and integrated sensitivity factor (CSF). Optimized hybrid ZnO QD -BP -based SPR sensor has the highest sensitivity, and its value is 427.1 ° / RIU with corresponding QF of 99.1987 RIU − 1 SNR equal to 0.297596, FOM of 99.15895, and CSF of 92.84522, which is quite higher than the conventional SPR configurations. These findings validate that the suggested sensor provides a very sensitive, dependable and non-invasive platform, and has a great capability to detect aflatoxin in food safety assay and biomedical research.
Authors
- Yesudasu Vasimalla (ORCID: https://orcid.org/0000-0002-5037-2318)
- Santosh Kumar (ORCID: https://orcid.org/0000-0003-4149-0096)
- Lohitha Doppalapudi
Institutions
- Koneru Lakshmaiah Education Foundation (IN)
Publication Details
- Journal
- Next Nanotechnology
- Published
- 2026-08-03
- DOI
- https://doi.org/10.1016/j.nxnano.2026.100646
- Primary Topic
- Mycotoxins in Agriculture and Food
- Type
- article
- Field-Weighted Citation Impact
- 0.00