A range of amphiphilic statistical copolymers was synthesized using reversible addition-fragmentation chain transfer (RAFT) solution polymerization where the hydrophilic component was methacrylic acid and the hydrophobic component was one of a variety of a hydrophobic methacrylic ester monomers with different carbon chain lengths and in turn different hydrophobicity and logP values. The hydrophobic monomers investigated were methyl, ethyl, butyl, hexyl, and 2-ethylhexyl, methacrylate where they increase in hydrophobicity respectively. Small-angle X-ray scattering (SAXS) studies showed that these copolymers aggregate into well-defined spherical particles on dilution with water where the size of the particle was highly composition dependant. Furthermore, varying the hydrophobic group also influenced the self-assembly where a more hydrophobic monomer induced a larger particle size. A contrast matching small-angle neutron scattering (SANS) experiment was used to investigate the internal structure of these particles and found that the copolymers arrange within the particle to locate MAA onto the surface causing pseudo-phase separation and a BMA-rich core. Finally, a mathematical model based around surface charge density stabilization was used to describe the relationship between the copolymer composition and the particle size formed. The model fits well with the experimental data collected across all the investigated systems and showed a linear relationship between the surface charge density needed to achieve stabilization and the logP of the hydrophobic component in the copolymer. This finding allows the particle size of similar amphiphilic statistical copolymers to be predicted accurately based upon the copolymer composition and the hydrophobicity of the hydrophobic component, therefore, making these types of systems a cheaper and highly viable alternative to diblock copolymer nano-particles currently used in industrial applications.

Tuning composition and hydrophobicity of ionic statistical amphiphilic copolymers to control and predict copolymer particle size

2019 Fall National Meeting

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