Phase Behavior of Reversibly Bonding Polymer Blends
Blending polymers is a versatile strategy for creating materials with tailored properties, but controlling the phase behavior of polymer blends remains a central challenge. Functionalization with sparse, associative chemical groups is a powerful way to shift phase behavior without changing individual component properties. We develop a field-theoretic model for heteroassociating polymer blends using the coherent states formalism, enabling an exact treatment of reversible bonding while avoiding explicit enumeration of polymer topologies. This framework captures the full distribution of supramolecular species, including higher-order branching and large clusters, and reveals how correlations between association sites of multifunctional polymers govern thermodynamic behavior across length scales. Using the random phase approximation, we identify conditions for macrophase separation and microphase ordering, and uncover a new motif for microphase separation in which bond density, rather than species density, exhibits spatial variations. These results unify and extend existing theories of reversibly bonding polymers, including phenomena such as gelation, and establish a foundation for designing compatibilizers through polymer architecture and sequence-level control of reversible interactions.
Authors
- Christopher J. Balzer (ORCID: https://orcid.org/0000-0002-9767-8437)
- Glenn H. Fredrickson (ORCID: https://orcid.org/0000-0002-6716-9017)
- Puck Springintveld
Institutions
- University of California System (US)
- Institute of Macromolecular Chemistry (UA)
- Division of Materials Research (US)
- Eindhoven University of Technology (NL)
Publication Details
- Journal
- Macromolecules
- Published
- 2025-06-18
- DOI
- https://doi.org/10.1021/acs.macromol.5c01173
- Citations
- 6
- Primary Topic
- Polymer crystallization and properties
- Type
- article
- Field-Weighted Citation Impact
- 3.64
Funders
- University of California, Santa Barbara
- Division of Materials Research
- Division of Computer and Network Systems