Current trends in scientific studies focus on the development of smartphone-based biosensors via green nanoparticle for clinical diagnosis, food, and environmental monitoring. In this study, we developed a novel portable smartphone-based biosensor via green dendrimer-coated matcha extract/silver nanoparticles (ME-Ag NPs) enriched with polyphenol for detecting hydrogen peroxide (H2O2). Also, we investigated the biological evaluation of the nanostructure as a safe preservative for use in biomedical applications. Ag NPs were prepared using a green sonochemical method and were characterized to determine surface and chemical properties by different techniques such as scanning electron microscopy-energy-dispersive X-ray, transmission electron microscope, Fourier transform infrared spectroscopy, atomic force microscopy, X-ray diffraction, and Brunauer-Emmett-Teller. Furthermore, antimicrobial and antifungal properties of ME-Ag NPs were investigated against pathogenic microorganisms such as Staphylococcus aureus, Pseudomonas aureginosa, Escherichia coli, Candida albicans, and Aspergillus brasiliensis. The experimental sensor methodology was based on the detection of H2O2 by analysis of images of novel silver nanostructure-coated papers and processing of color histograms with a RGB (red-green-blue) analyzer software. Consequently, the smartphone-based biosensor exhibited high sensitivity with detection limits of 0.82 μM response time of 5 s. The smartphone-based biosensor via ME-Ag NPs provided a rapid and selective detection of H2O2.
Keyphrases
- hydrogen peroxide
- silver nanoparticles
- electron microscopy
- label free
- candida albicans
- loop mediated isothermal amplification
- quantum dots
- sensitive detection
- atomic force microscopy
- gold nanoparticles
- staphylococcus aureus
- biofilm formation
- nitric oxide
- escherichia coli
- real time pcr
- highly efficient
- oxidative stress
- risk assessment
- magnetic resonance
- anti inflammatory
- magnetic resonance imaging
- high throughput
- pseudomonas aeruginosa
- convolutional neural network
- computed tomography
- human health
- mass spectrometry
- gas chromatography