The hydrophobic collapse is a structural transition of grafted polymer chains in a poor solvent. Although such a transition seems an intrinsic event during clustering of polymer-stabilized nanoparticles in the liquid phase, it has not been resolved in real time. In this work, we implemented a microfluidic 3D-flow-focusing mixing reactor equipped with real-time analytics, small-angle X-ray scattering (SAXS), and UV-vis-NIR spectroscopy to study the early stage of cluster formation for polystyrene-stabilized gold nanoparticles. The polymer shell dynamics obtained by in situ SAXS analysis and numerical simulation of the solvent composition allowed us to map the interaction energy between the particles at early state of solvent mixing, 30 ms behind the crossing point. We found that the rate of hydrophobic collapse depends on water concentration, ranging between 100 and 500 nm/s. Importantly, we confirmed that the polymer shell collapses prior to the commencement of clustering.

Time-Resolved Analysis of the Structural Dynamics of Assembling Gold Nanoparticles

Litti, Lucio;
2019

Abstract

The hydrophobic collapse is a structural transition of grafted polymer chains in a poor solvent. Although such a transition seems an intrinsic event during clustering of polymer-stabilized nanoparticles in the liquid phase, it has not been resolved in real time. In this work, we implemented a microfluidic 3D-flow-focusing mixing reactor equipped with real-time analytics, small-angle X-ray scattering (SAXS), and UV-vis-NIR spectroscopy to study the early stage of cluster formation for polystyrene-stabilized gold nanoparticles. The polymer shell dynamics obtained by in situ SAXS analysis and numerical simulation of the solvent composition allowed us to map the interaction energy between the particles at early state of solvent mixing, 30 ms behind the crossing point. We found that the rate of hydrophobic collapse depends on water concentration, ranging between 100 and 500 nm/s. Importantly, we confirmed that the polymer shell collapses prior to the commencement of clustering.
2019
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3302923
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