MoS 2 nanosheets grown on bowl-shaped hollow carbon spheres as an efficient electrochemical sensor for ultrasensitive determination of nephrotoxic aristolochic acids in Chinese traditional herbs.
Menglin ZhouTingfan TangXiujun DengQian LiZesen ZuoGuangzhi HuPublished in: Analytical methods : advancing methods and applications (2023)
Aristolochic acid, a substance in herbs, is highly nephrotoxic, so it is crucial to develop an assay that can rapidly and accurately analyze its content. In this study, bowl-shaped hollow carbon spheres (BHCs) were synthesized using a complex template method, and a MoS 2 layer was grown in situ on their surface using a hydrothermal method. The synthesized MoS 2 -BHCs were used to fabricate an electrochemical sensor for the ultrasensitive and highly selective detection of aristolochic acids (AAs). The optimal conditions for AA detection were determined by tailoring the amount of MoS 2 used to modify the BHCs and the pH of the electrolyte. Under optimal conditions, the MoS 2 -BHC-based sensor presented excellent AA detection performance. The linear concentration ranges of the MoS 2 -BHC-based sensor for the detection of AA were 0.05-10 μmol L -1 and 10-80 μmol L -1 , and the limit of detection of the sensor was 14.3 nmol L -1 . Moreover, the MoS 2 -BHC-based sensor detected AA in Aristolochia and Asarum sieboldii samples. The results were consistent with high-performance liquid chromatography data, demonstrating the satisfactory recovery and accuracy of the sensor. Therefore, we believe that MoS 2 -BHC-based sensors can be used as effective platforms for detecting AA in traditional Chinese herbs.
Keyphrases
- quantum dots
- label free
- reduced graphene oxide
- molecularly imprinted
- room temperature
- gold nanoparticles
- loop mediated isothermal amplification
- highly efficient
- transition metal
- high performance liquid chromatography
- sensitive detection
- visible light
- real time pcr
- solid phase extraction
- ionic liquid
- mass spectrometry
- high throughput
- high resolution
- big data
- ms ms
- electron transfer
- liquid chromatography