Gingerol extract-stabilized silver nanoparticles and their applications: colorimetric and machine learning-based sensing of Hg(ii) and antibacterial properties.
Kittiya PlaeyaoRatchaneekorn KampangtaYuparat KorkokklangChanon TalodthaisongApichart SaenchoopaSaengrawee ThammawithanKrailikhit LatpalaRina PatramanonNavaphun KayunkidSirinan KulchatPublished in: RSC advances (2023)
This study focused on synthesizing ginger-stabilized silver nanoparticles (Gin-AgNPs) using a more eco-friendly method that utilized AgNO 3 and natural ginger solution. These nanoparticles underwent a color change from yellow to colorless when exposed to Hg 2+ , enabling the detection of Hg 2+ in tap water. The colorimetric sensor had good sensitivity, with a limit of detection (LOD) of 1.46 μM and a limit of quantitation (LOQ) of 3.04 μM. Importantly, the sensor operated accurately without being affected by various other metal ions. To enhance its performance, a machine learning approach was employed and achieved accuracy ranging from 0% to 14.66% when trained with images of Gin-AgNP solutions containing different Hg 2+ concentrations. Furthermore, the Gin-AgNPs and Gin-AgNPs hydrogels exhibited antibacterial effects against both Gram-negative and Gram-positive bacteria, indicating potential future applications in the detection of Hg 2+ and in wound healing.
Keyphrases
- high performance liquid chromatography
- silver nanoparticles
- fluorescent probe
- aqueous solution
- gram negative
- machine learning
- living cells
- solid phase extraction
- simultaneous determination
- label free
- multidrug resistant
- loop mediated isothermal amplification
- wound healing
- gold nanoparticles
- ms ms
- liquid chromatography tandem mass spectrometry
- deep learning
- hydrogen peroxide
- sensitive detection
- artificial intelligence
- oxidative stress
- big data
- body composition
- optical coherence tomography
- resistance training
- human health
- low cost
- climate change
- high resolution