Smartphone Nanocolorimetric Determination of Hydrogen Sulfide in Biosamples after Silver-Gold Core-Shell Nanoprism-Based Headspace Single-Drop Microextraction.
Sheng TangTong QiDasha XiaMengchan XuMengyuan XuAnni ZhuWei ShenHian Kee LeePublished in: Analytical chemistry (2019)
In this work, the sensitive detection of hydrogen sulfide (H2S) was realized at low cost and high efficiency through the application of silver-gold core-shell nanoprism (Ag@Au-np) combined with headspace single-drop microextraction (HS-SDME). After SDME, smartphone nanocolorimetry (SNC), with the aid of a smartphone camera and color picker software, was used to detect and quantify the H2S. The method took advantage of the inhibition of the ultraviolet-visible (UV-vis) signal caused by H2S etching of the Ag@Au-np preadded to the SDME solvent to measure the H2S concentration. The coating of the gold layer not only ensured the high stability of the nanomaterial but also enhanced the selectivity toward H2S. The HS-SDME method was simple to process and required only a droplet of solvent for analysis to be realized. This HS-SDME-SCN approach exhibited a calibration graph linearity of between 0.1 and 100 μM and a limit of detection of 65 nM (relative standard deviations of N% ( n = 3) < 4.80). A comparison with UV-vis spectrophotometry was conducted. The practical applicability of HS-SDME-SNC was successfully demonstrated by determining H2S in genuine biosamples (egg and milk).
Keyphrases
- sensitive detection
- quantum dots
- low cost
- gas chromatography
- silver nanoparticles
- ionic liquid
- loop mediated isothermal amplification
- high efficiency
- solid phase extraction
- gas chromatography mass spectrometry
- molecularly imprinted
- gold nanoparticles
- mass spectrometry
- tandem mass spectrometry
- high performance liquid chromatography
- liquid chromatography tandem mass spectrometry
- simultaneous determination
- liquid chromatography
- convolutional neural network
- visible light
- highly efficient
- photodynamic therapy
- single cell
- reduced graphene oxide
- high resolution
- solar cells
- label free
- aqueous solution
- deep learning
- neural network