Structure of pH sensitive self-assembled amphiphilic di- and triblock copolyelectrolytes: micelles, aggregates and transient networks
Literature Information
Céline Charbonneau, Christophe Chassenieux, Olivier Colombani, Taco Nicolai
We have studied the self-assembly of aqueous dispersions of amphiphilic di- and triblock copolyelectrolytes using static and dynamic light scattering. The hydrophobic blocks contained both ionisable and hydrophobic units rendering the association dynamic and thus ensuring that thermodynamic equilibrium was reached. The incorporation of ionisable units into the hydrophobic blocks caused the self-assembly to be strongly influenced by the pH and the ionic strength. As in the case of neutral block copolymers, diblock copolyelectrolytes self-assembled into star-like micelles and triblock copolyelectrolytes formed flower-like micelles. The latter was not predicted to occur for block copolyelectrolytes. At higher concentrations a system spanning network was formed. The structure of the systems could be quantitatively described by a model of purely repulsive spheres for the diblocks and attractive spheres for the triblocks. The polyelectrolyte effect expressed itself by a sensitivity of the structure to the pH and the ionic strength. The attraction increased with decreasing pH and increasing ionic strength leading at high ionic strength to phase separation.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.










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