Controllable Copolymerization of Polymeric Micelles for the Construction of Supramolecular Chains

Supramolecular polymerization of nanoparticles is attracting considerable attention for preparing one-dimensional (1D) nanostructures with controllable geometries and promising properties. However, so far, little is known about the supramolecular copolymerization of polymeric micelles, including the general rules and polymerization kinetics. Herein, we demonstrate a supramolecular copolymerization of micelles with various activities into supramolecular chains with controllable lengths and sequences including random, block, and alternate. It is also found that micelles with extremely low activity can act as supramolecular chain stoppers to terminate the polymerization. Since accurate statistical data on supramolecular copolymerization is crucial for revealing the mechanism and building a theoretical model, we propose a machine learning-based image recognition method. This method can precisely differentiate various micellar subunits in the supramolecular copolymer chains. A theoretical kinetic model is proposed, and the kinetic studies reveal that diffusion of the micelles plays a dominant role in supramolecular copolymerization. This work enriches the supramolecular polymerization of micelles and provides theoretical guidance for the engineering of 1D nanostructures with controllable structures.