Unexpected toroidal micelles formed from St/MMA gradient copolymers

Nanoscale polymer discs, toroids and platelets: a survey of their syntheses and potential applications

Polymer self-assembly has become a reliable and versatile workhorse to produce polymeric nanomaterials. With appropriate polymer design and monomer selection, polymers can assemble into shapes and morphologies beyond well-studied spherical and cylindrical micellar structures. Steadfast access to anisotropic polymer nanoparticles has meant that the fabrication and application of 2D soft matter has received increasing attention in recent years. In this review, we focus on nanoscale polymer discs, toroids, and platelets: three morphologies that are often interrelated and made from similar starting materials or common intermediates. For each morphology, we illustrate design rules, and group and discuss commonly used self-assembly strategies. We further highlight polymer compositions, fundamental principles and self-assembly conditions that enable precision in bottom-up fabrication strategies. Finally, we summarise potential applications of such nanomaterials, especially in the context of biomedical research and template chemistry and elaborate on future endeavours in this space.

Copolymers with Nonblocky Sequences as Novel Materials with Finely Tuned Properties

The copolymer sequence can be considered as a new tool to shape the resulting system properties on demand. This perspective is devoted to copolymers with "partially segregated" (or nonblocky) sequences. Such copolymers include gradient copolymers and copolymers with random sequences as well as copolymers with precisely controlled sequences. We overview recent developments in the synthesis of these systems as well as new findings regarding their properties, in particular, self-assembly in solutions and in melts. An emphasis is put on how the microscopic behavior of polymer chains is influenced by the chain sequences. In addition to that, a novel class of approaches allowing one to efficiently tackle the problem of copolymer chain sequence design─data driven methods (artificial intelligence and machine learning)─is discussed.