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    Detection of engineered nanoparticles by SERS

    Liou, Polly
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    Date
    2016
    Format
    Thesis
    Metadata
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    Abstract
    There has been increasing number of consumer and food products sold on the market that contain various engineered nanomaterials (ENMs) such as silver nanoparticles (AgNPs) and gold nanoparticles (AuNPs). These nanomaterials possess novel physical and chemical properties that can be used for wide applications in agriculture and food safety. However, these ENMs can damage human and animals' health and current analytical methods to detect and measure ENMs are time-consuming, labor-intensive, and expensive. The objective of this study was to develop a novel, simple, rapid, and accurate method to detect AgNPs and AuNPs in consumer products using surface-enhanced Raman spectroscopy (SERS). SERS measurement was conducted to detect AgNPs and AuNPs using an effective Raman indicator, 4-aminothiophenol (pATP). The pATP can strongly bind with nanoparticles, generating greatly enhanced Raman signals that can be used for measurement. The pATP was combined with Ag or Au stock solutions, AgNO3, citratecoated AgNPs, citrate-coated AuNPs, AuCl, AgNPs, AuNPs, and five commercial products to study the differences in their SERS spectral data. The observed spectra of AgNPs and AuNPs have similar peaks at [about]390, [about]1087, and [about]1590 cm-1 that can be attributed to the C-S stretching vibration, C-C stretching vibration, and C-H stretching vibration, respectively. Neutron activation analysis (NAA) and electron microscopy was used to characterize and quantify AgNPs and AuNPs in the consumer products. The results demonstrate that SERS method in combination with NAA can be an effective method for detection of ENMs, and it can easily distinguish AgNPs and AuNPs from other nonnanoparticle species in the complex matrices.
    URI
    https://hdl.handle.net/10355/57598
    Degree
    M.S.
    Thesis Department
    Food science (MU)
    Rights
    OpenAccess.
    This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.
    Collections
    • 2016 MU theses - Freely available online
    • Food Science electronic theses and dissertations (MU)

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