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Updated: Aug 19, 2025
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Synthesis of Information-bearing Peptoids and their Sequence-directed Dynamic Covalent Self-assembly
Published on: February 6, 2020
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Structure-Reactivity-Property Relationships in Covalent Adaptable Networks.
Vivian Zhang1, Boyeong Kang1, Joseph V Accardo1
1Department of Chemistry, Northwestern University, 2145 Sheridan Road, Evanston, Illinois60208, United States.
Journal of the American Chemical Society
|November 29, 2022
Summary
Dynamic covalent bonds in polymer networks enable adaptable materials that can self-heal and be remolded. Understanding these covalent adaptable networks (CANs) links molecular properties to macroscopic behavior for advanced applications.
Area of Science:
- Polymer Chemistry
- Materials Science
- Chemical Engineering
Background:
- Dynamic covalent bonds allow polymer networks to rearrange their topology.
- Covalent adaptable networks (CANs) exhibit properties like flow, self-healing, and stimulus-responsiveness.
- Controlling network rearrangement is crucial for applications in sustainability and tissue engineering.
Purpose of the Study:
- To analyze structure-reactivity-property relationships in covalent adaptable networks (CANs).
- To illustrate general design principles for CANs.
- To highlight the predictive potential of linear free energy relationships (LFERs) in CANs.
Main Methods:
- Analysis of structure-reactivity-property relationships across various CAN classes.
- Application of linear free energy relationships (LFERs) to CANs.
- Review of existing literature and research trends in dynamic covalent polymer networks.
Main Results:
- Demonstrated connection between molecular bond characteristics and macroscopic network properties.
- Illustrated the utility of LFERs for predicting CAN behavior.
- Identified key design principles for tuning CAN properties.
Conclusions:
- Quantitative structure-reactivity-property relationships are essential for advancing CAN technology.
- Further development is needed to fully harness the potential of CANs.
- Bridging molecular and macroscopic scales is key for future innovations in adaptable materials.
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