Green microfluidic synthesis of monodisperse silver nanoparticles via genetic algorithm optimization – Syrris in Publications

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RSC Advances Issue 98, 2016

  • Daneil L. A. Fernandes,a Cristina Paun,a Mariia V. Paviuk,a Arthur B. Fernandes,b Erick L. Bastosb and Jacinto Sáa,c
    • aDepartment of Chemistry-Ångström Laboratory, Uppsala University, 75120 Uppsala, Sweden
    • bDepartment of Fundamental Chemistry, Institute of Chemistry, University of São Paulo, 05508-000 São Paulo, Brazil
    • cInstitute of Physical Chemistry-Polish Academy of Sciences, 01-224 Warsaw, Poland

Using the Syrris Asia system, researchers at the Department of Chemistry (Uppsala University, Sweden) have reported the scalable and green synthesis of monodisperse silver nanoparticles via genetic algorithm optimization. Microfluidic flow systems are well-suited to nanoparticle production because they allow rapid and controlled manipulation of reaction conditions to influence nanoparticle properties. By combining the microfluidic reactor with an optimization algorithm, it was possible to greatly improve the output quality of the nanoparticles far faster than by batch methods, without the need for human input.

Green microfluidic synthesis of monodisperse silver nanoparticles via genetic algorithm optimization

Abstract: A scalable and green procedure for the microfluidic flow synthesis of monodisperse silver nanoparticles is reported. Beetroot extract is used both as a reducing and growth-regulating agent. A multi-objective genetic algorithm was used to automate the optimization of the reaction and reduce sample polydispersity observed in previous reports. The proposed methodology ensures high-quality nanoparticles in a rapid manner and devoid of human skill or intuition, essential for method standardization and implementation.

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