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Updated: Mar 15, 2026

The Preparation and Properties of Thermo-reversibly Cross-linked Rubber Via Diels-Alder Chemistry

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Bound Rubber as a Transferable Structural Descriptor: Connecting MD-Derived Interfacial Scaling to Continuum

Yancai Sun^1,2,3,4, Wenzhong Deng^2,3, Haoran Wang⁵

¹College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao 266061, China.

|March 14, 2026

Summary

This summary is machine-generated.

This study links molecular structure to elastomer reinforcement using multiscale modeling. Molecular dynamics simulations provide structural insights, improving macroscopic predictions and reducing errors in material behavior modeling.

Keywords:

dynamic mechanical analysis fractional Maxwell model interfacial scaling molecular dynamics polymer nanocomposites rheological modeling

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Area of Science:

Polymer Science
Materials Science
Computational Chemistry

Background:

Filled elastomers show a low-frequency power-law storage modulus (G-prime).
Quantitative links between molecular interfacial structure and macroscopic reinforcement are not well understood.
Existing models struggle to predict macroscopic properties from molecular details.

Purpose of the Study:

To establish quantitative links between molecular interfacial structure and macroscopic reinforcement in filled elastomers.
To develop a hierarchical multiscale framework integrating molecular dynamics (MD) and dynamic mechanical analysis (DMA).
To improve the prediction of elastomer mechanical properties from molecular-level information.

Main Methods:

Utilized a hierarchical multiscale framework combining coarse-grained molecular dynamics (MD) and dynamic mechanical analysis (DMA).
MD simulations generated structural descriptors, including bound-layer scaling relations.
Employed single-phase fractional Maxwell and dual-phase models for analyzing EPDM and PC/ABS data, respectively.
Developed a regime-partitioned bridge model for cross-scale predictions, incorporating MD-derived baselines.

Main Results:

MD simulations provided transferable structural descriptors, not direct rheology predictions.
The dual-phase model was favored for larger datasets (PC/ABS, n=952).
The regime-partitioned bridge model significantly reduced prediction error (7.3%) by incorporating MD structural priors and resolving uncaptured relaxation physics.
Linear-viscoelastic constraints improved nonlinear predictions, reducing die-swell error by 87%.

Conclusions:

The developed multiscale framework successfully links molecular interfacial structure to macroscopic elastomer reinforcement.
This approach enhances the accuracy of predicting material properties and behavior.
The findings offer a pathway for designing elastomers with tailored macroscopic properties based on molecular architecture.