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Microfluidic Synthesis of Microgel Building Blocks for Microporous Annealed Particle Scaffold
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Simulation of interpenetrating networks microgel synthesis
Vladimir Yu Rudyak1, Elena Yu Kozhunova, Alexander V Chertovich
1Faculty of Physics, Lomonosov Moscow State University, Leninskie Gory, 1-2, Moscow 119991, Russia.
Soft Matter
|May 19, 2020
Summary
Computer simulations revealed conditions for synthesizing interpenetrating network (IPN) microgels. Researchers demonstrated novel shell-corona structures in IPN microgels formed in silico, aiding experimental design.
Area of Science:
- Polymer Chemistry
- Materials Science
- Computational Chemistry
Background:
- Interpenetrating network (IPN) microgels offer unique properties due to their complex network structures.
- Understanding the synthesis-structure-property relationships is crucial for designing advanced functional materials.
Purpose of the Study:
- To implement sequential template synthesis of IPN microgels via computer simulations.
- To investigate the influence of network interactions on polymerization and IPN formation.
- To explore the topological properties and solvent-induced morphologies of IPN microgels.
Main Methods:
- Sequential template synthesis simulation.
- Analysis of polymerization kinetics and network interactions.
- Morphological studies in various solvent conditions (good, poor, selective).
- In silico investigation of shell-corona structure formation.
Main Results:
- Identified critical conditions for successful IPN microgel formation.
- Established correlations between synthesis parameters and microgel topology.
- Observed distinct microgel morphologies dependent on solvent quality.
- Demonstrated the novel formation of shell-corona structures in in silico synthesized IPN microgels under selective solvent conditions.
Conclusions:
- The study provides a computational framework for understanding IPN microgel synthesis.
- The findings elucidate the formation mechanisms of complex microgel architectures.
- Results offer guidance for experimentalists in tuning synthesis and interpreting characterization data, particularly static structure factors.

