Breaking Composition Constraints: Viscoelasticity-Driven Phase Inversion for Mechanically Robust Block Copolymer Networks

Overcoming the thermodynamic constraints of minority composition for achieving continuous networks in block copolymers remains a fundamental challenge to realize lightweight structural nanomaterials. To resolve this challenge, we develop multiscale modeling to establish dynamic asymmetry as an engineering strategy for achieving metastable nanostructures and enhanced mechanical properties through unusual viscoelastic microphase separation. The simulations of dynamic self-consistent field theory reveal that the dynamic asymmetry arising from bulk modulus differences has the capability to reprogram the kinetic pathways of microphase separation of block copolymers, triggering composition-independent phase inversion. Particularly, this inversion phenomenon can yield the continuous percolating networks of high-bulk-modulus blocks in spite of their minority composition, a thermodynamically forbidden configuration at equilibrium. Furthermore, we employ a dynamic lattice spring model to demonstrate that nanostructured materials with quenched metastable networks have exceptional mechanical enhancement, surpassing both cases of homogeneous melts and stable morphologies. Overall, the viscoelastic microphase separation induced by the dynamic asymmetry presents a robust alternative to accessing lightweight, high-strength nanomaterials beyond thermodynamic design rules.

Authors

Institutions

Publication Details

Journal
Macromolecules
Published
2025-12-24
DOI
https://doi.org/10.1021/acs.macromol.5c02227
Primary Topic
Block Copolymer Self-Assembly
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Breaking Composition Constraints: Viscoelasticity-Driven Phase Inversion for Mechanically Robust Block Copolymer Networks

Jiaping Lin, Liangshun Zhang, Zhepeng Zhu
Macromolecules
Block Copolymer Self-Assembly
article

Breaking Composition Constraints: Viscoelasticity-Driven Phase Inversion for Mechanically Robust Block Copolymer Networks

Jiaping Lin, Liangshun Zhang, Zhepeng Zhu
article en

Abstract

Overcoming the thermodynamic constraints of minority composition for achieving continuous networks in block copolymers remains a fundamental challenge to realize lightweight structural nanomaterials. To resolve this challenge, we develop multiscale modeling to establish dynamic asymmetry as an engineering strategy for achieving metastable nanostructures and enhanced mechanical properties through unusual viscoelastic microphase separation. The simulations of dynamic self-consistent field theory reveal that the dynamic asymmetry arising from bulk modulus differences has the capability to reprogram the kinetic pathways of microphase separation of block copolymers, triggering composition-independent phase inversion. Particularly, this inversion phenomenon can yield the continuous percolating networks of high-bulk-modulus blocks in spite of their minority composition, a thermodynamically forbidden configuration at equilibrium. Furthermore, we employ a dynamic lattice spring model to demonstrate that nanostructured materials with quenched metastable networks have exceptional mechanical enhancement, surpassing both cases of homogeneous melts and stable morphologies. Overall, the viscoelastic microphase separation induced by the dynamic asymmetry presents a robust alternative to accessing lightweight, high-strength nanomaterials beyond thermodynamic design rules.

MacromoleculesVol. 59(1)
East China University of Science and Technology (CN), Division of Materials Science and Engineering (AU)
Openalex Percentile: Top 48%
Block Copolymer Self-Assembly
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.