Plasmon-enhanced detection of Aflatoxin B1 using copper–silver hybrid nanostructures on a paper-free platform
摘要
Aflatoxin B1 (AFB1) is a very toxic mycotoxin that might be detected in contaminated grains and has severe food safety and health issues. Herein, we present a copper-silver (Cu-Ag) hybrid nanostructure-based paperless plasmonic sensing in our new work in order to rapidly and with a high degree of specificity sense AFB1. The hybrid nanostructures built generate such strong electromagnetic hotspots and enhanced localized surface plasmon resonance (LSPR) by means of the plasmonic coupling between the Ag and Cu domains which is synergistic. Compared to the traditional paper-based plasmonic substrates, the given arrangement promises enhanced stability and less background interference along with the detection signal improvement.The platform is well-suited for on-site grain analysis due to its rapid response rate (less than 5 min) and low detection limit in the nanomolar scale. Moreover, the sensor is robust in a range of environmental conditions and exhibits excellent selectivity against structural analogues, ensuring reliable performance in real-world applications. The combination of low-cost Cu and Ag nanostructures brings near the ability to enable useful food safety monitoring by offering a cost-effective alternative to plasmonic systems based on noble metals. This work demonstrates that Cu-Ag hybrid plasmonic structures can be employed to design next-generation paperless platforms for rapid, precise, and scalable detection of hazardous pollutants.
Graphical AbstractThe graphical abstract shows the paper-free plasmonic sensor detection of Aflatoxin B1 rapid workflow. On the top-left, there is the CuAg hybrid nanostructure sensor platform that produces hotspots of strong plasmonic features at the top-right end (where SERS signal enhancement is vital). Aflatoxin B1 (chemical structure) molecules (bottom-left) react with these hotspots resulting in increased Raman signals. The bottom-right justifies the sensor performance in real grain matrices (maize and groundnut) and in a bar graph, it indicates a high intensity of Raman intensities within a broad range of concentration levels. Combined, the schematic outlines the sensitivity of the sensor, its actual applicability with real-sample and its possible food safety tracking capability