Date: Wednesday 1st of November 2023, 13:30 (GMT).
Location: Isaac Newton Building (INB3305) and Online MS Teams meeting

‘Aqueous Dispersions of Amphiphilic Statistical Copolymer’

by Dr Oleksandr Mykhaylyk, Soft Matter AnalyticaL Laboratory, Department of Chemistry, University of Sheffield, Sheffield, UK.

Abstract:

Over the last few years, research into the self-assembly behaviour of statistical copolymers has been reinvigorated. The obvious reasons for this revived interest are: (1) statistical copolymers can be synthesized easily and cheaply via a one-pot reaction using various polymerisation techniques including standard free radical polymerization making these copolymers highly industrially viable; (2) the distribution of amphiphilic components in the statistical copolymers force their self-assembly behaviour to be very different from the block copolymer counterparts and in some respect puts them in a position of synthetic mimics for biomolecules making these systems interesting for bio-inspired applications such as catalysis, drug delivery, nano-sensors, water-purification, etc. However, there has been a recent resurgence in the interest towards these systems as they have been found to self-assemble into useful nano-objects such as spheres, rods/worms, vesicles, and ‘bowl-like’ morphologies and can also be tuned to form single chain nanoparticles.
Statistical copolymers can self-assemble into useful nano-objects such as spheres, rods/worms, vesicles, and ‘bowl-like’ morphologies and can also be tuned to form single chain nanoparticles. The self-assembly of charged amphiphilic statistical copolymers in water is composition-dependent and the size of formed copolymer particles could be related to the particle surface charge density (PSC model, see Macromolecules 2018, 51, 1474) which points towards an existence of universal rules for statistical copolymer self-assembly. This finding on a single system, poly(butyl methacrylate-stat-methacrylic acid), have been confirmed using a library of statistical copolymers with both anionic and cationic stabilizing components (see Macromolecules 2021, 54, 1425). Structural techniques such as small angle X-ray and neutron scattering (SAXS and SANS) are explored to specifically investigate the effect of copolymer composition and component hydrophobicity (logP) on the copolymer self-assembly. The previously hypothesized PSC model were verified on an extremely wide data set, where both the hydrophobicity and charge of the monomers are varied. Furthermore, a relationship between the logP of the hydrophobe and the surface charge density required to form stable dispersions is found. Thus, universal rules for predicting the statistical copolymer self-assembly and particle size formed were established – a feat that has not been seen for copolymers of this type. Furthermore, this work demonstrates that bespoke particles can be synthesized easily and cheaply using statistical copolymers without the need for expensive and time-consuming controlled polymerization techniques making them a viable alternative to block copolymers in many industrial applications. The particle surface charge model that has been developed and intensively tested can give significant insight into the behavior of biomolecules and in particular, protein folding.
Some variations of statistical copolymers towards triblock copolymers with statistical blocks will also be presented. In water these copolymers self-assemble into spherical particles with a particulate shell. Films cast from both copolymer solutions and aqueous dispersions demonstrate different mechanical properties directly related to their structural morphologies formed by the phase-separated triblock copolymers (Macromolecules 2022, 55, 9726).