Predictable Synthesis of 3D Polymer Networks Using Crystal Component-Linking.

Area of Science:

• Polymer Chemistry
• Materials Science
• Computational Chemistry

Background:

• Controlled synthesis of 3D polymer networks is challenging due to complex solution polymerization reactions.
• Predicting polymer network structures and properties experimentally is difficult.

Purpose of the Study:

• To develop a polymerization system enabling prediction of polymer network structure via percolation simulations.
• To bridge the gap between theoretical percolation simulations and experimental polymerization by addressing molecular mobility.

Main Methods:

• A crystal component-linking method was employed, arranging monomers in a supramolecular crystalline state.
• Percolation simulations were utilized, based on the crystal structure of arranged monomers.
• Key properties like gelation point, gel fraction, and degree of swelling were calculated and compared with experimental data.

Main Results:

• The crystal component-linking method successfully imitated simple percolation theory, accounting for molecular arrangement.
• Percolation simulations accurately predicted experimental results, including gelation point, gel fraction, degree of swelling, and atomic formula.
• Simulations also predicted complex structural features like loops, branched polymers, and crosslinking points, which are hard to measure experimentally.

Conclusions:

• Precisely arranged immobilized monomers in supramolecular structures offer a promising route for synthesizing controlled polymer networks.
• The developed crystal component-linking method combined with percolation simulation allows for accurate prediction of polymer network structures.
• This approach provides a powerful tool for understanding and designing complex polymer architectures.