Microfluidic-integrated SSPP sensor for rapid and sensitive label-free honey adulteration

Abstract

A Spoof surface plasmon polariton (SSPP) sensor is developed to identify honey samples by adding different concentrations levels of sugar (glucose and fructose). The SSPP-based sensor is integrated with a microfluidic reservoir to discriminate honey samples. The change in the resonating frequency shift with changed percentages of fructose and glucose levels of honey samples shows the performance of the SSPP sensor. This innovative approach presents a non-destructive, non-intrusive, label-free, rapid, and real-time methodology for analysing honey samples. The sensor exhibits exceptional sensitivity in detecting subtle differences in the dielectric constants of diverse samples. We systematically investigate the impact of distinct geometrical parameters on the sensor’s performance, focusing on optimizing its characteristics. A distinctive pentagon-shaped unit cell (UC) for the SSPP construction is thoroughly explored, revealing its unique performance and sensing capabilities. We construct a multilayer SSPP microwave structure with a pentagon unit cell to create a functional sensing platform for honey samples. The transient solver is used for computational analysis. Our results indicate a remarkable sensitivity of 1522 MHz/epsilon unit, with a correlation coefficient (R²) of 0.9367, for discerning between different dielectric samples ranging from 1 to 5 for normal pentagon unit cells. Additionally, for vertex-based pentagon unit cells, the sensor demonstrates a sensitivity of 1105 MHz/epsilon unit, with an R² of 0.9524, when applied dielectric constants within the range of 1–5. These simulation outcomes highlight the viability of the suggested SSPP-inspired sensor as a promising solution for monitoring applied dielectric quality and characterizing the honey sample’s dielectric constants. This integrated approach showcases the potential to revolutionize quality assessment within the realm of honey production and diverse materials through its advanced sensing capabilities.