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Confinement Assembly in Polymeric Micelles Enables Nanoparticle Superstructures with Tunable Molecular-Like Geometries.

Zhebin ZhangYan XiaSiyu WanAngang DongAngang Dong
Published in: Small methods (2022)
The self-assembly of a small number of nanoparticles into superstructures that mimic the geometry of molecules provides an unprecedented route for creating materials with precisely defined structures and potentially programmable functionalities. Such nanoparticle clusters (NPCs), also known as colloidal molecules, have a wide range of applications due to the decisive ensemble effect. Here, a universal and straightforward strategy is developed to construct NPCs with tunable molecular-like geometries by confining the self-assembly of hydrophobic nanoparticles within micelles formed by amphiphilic copolymers. It is found that confinement assembly of both spherical and anisotropic nanoparticles can lead to NPCs, the molecular-like conformation of which is widely tunable by adjusting the ratio between copolymers and nanoparticles. Mechanistic studies reveal the formation of large-vesicle intermediates along the path toward forming NPCs. This work establishes a facile and general strategy of assembling finite nanoparticles with precisely tunable geometries without introducing any directional interactions, which can accelerate the exploration of clustered superstructures toward broad applications.
Keyphrases
  • drug delivery
  • cancer therapy
  • drug release
  • walled carbon nanotubes
  • gold nanoparticles
  • machine learning
  • genome wide
  • deep learning
  • neural network
  • monte carlo