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    Chapter Microemulsions as Nanoreactors to Obtain Bimetallic Nanoparticles

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    Author(s)
    Tojo, C.
    Buceta, David
    Arturo López-Quintela, M.
    Language
    English
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    Abstract
    Microemulsions are frequently used as nanoreactors for the synthesis of bimetallic nanoparticles. The ability to manipulate the metal distribution in bimetallic nanoparticles is essential for optimizing applications, and it requires a deeper understanding of how compartmentalization of reaction medium affects nanoparticle synthesis. A simulation model was developed to predict the atomic structure of bimetallic nanoparticles prepared via microemulsion in terms of metals employed and microemulsion composition. The model was successfully proved by comparing theoretical and experimental Au/Pt STEM profiles. On this basis, the model becomes a strong tool to further enhance our knowledge of the complex mechanisms governing reactions in microemulsions and its impact on final nanostructures. The purpose of this study is to perform a comprehensive kinetic analysis of coreduction of different couple of metals in the light of the interplay between three kinetic parameters: intermicellar exchange rate, chemical reduction rates of the two metals, and reactants concentration. The particular combination of these factors determines the reaction rate of each metal, which in turn determines the final metal arrangement.
    URI
    https://library.oapen.org/handle/20.500.12657/49298
    Keywords
    bimetallic nanoparticles, microemulsions, reduction rate, intermicellar exchange rate, nanocatalysts
    DOI
    10.5772/intechopen.80549
    Publisher
    InTechOpen
    Publisher website
    https://www.intechopen.com/
    Publication date and place
    2019
    Classification
    Chemistry
    Rights
    https://creativecommons.org/licenses/by/3.0/
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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