Smartphone-Enabled Platform for Direct Recognition of the Morphology of Copolymer Nano-Objects during Polymerization-Induced Self-Assembly

Abstract

Polymerization-induced self-assembly (PISA) has been demonstrated as a robust method for the preparation of polymeric nanoparticles with various morphologies in high solid content. Developing efficient methods for the direct recognition of the morphologies of copolymer nanoparticles during PISA in a low-cost and simple manner is of practical significance. Herein, we proposed a fluorescent chroma method that enabled the direct recognition of the morphologies of copolymer nano-objects in the PISA process. Methacrylate monomer bearing pyrene fluorophore (PyAMA) with a broad emission region was first synthesized, which exhibited blue monomeric fluorescence and produced green excimer emission when stacked together in a dimer state. PyAMA was then used as a comonomer during the RAFT dispersion polymerization of benzyl methacrylate (BzMA) using 4-cyano-4-(2phenylethanesulfanyl-thiocarbonyl)sulfanylpentanoic acid (PETTC) capped poly(ethylene oxide) (PEO-PETTC) as a macromolecular chain transfer agent (macroCTA). Accompanying with the morphological transformation from micelles to nanowires to vesicles, the fluorescent color of the copolymer nanoparticles underwent the variation from blue to cyan to green due to the increased emission ratio of pyrene excimer to monomer (I excimer /I monomer ), and the direct observation of the nanostructural changes during PISA by naked eyes was realized. Furthermore, an easy-to-use smartphone program was elaborately designed to simplify the morphological recognition based on the fluorescent colors for different morphologies. This strategy provides a facile platform to monitor the morphological evolutions during PISA and realizes the preassessment of the morphologies of PISA-generated nanoparticles.