A coopetition-driven strategy of parallel/perpendicular aromatic stacking enabling metastable supramolecular...

Area of Science:

• Supramolecular Chemistry
• Materials Science
• Polymer Chemistry

Background:

• Metastable supramolecular polymerization, under kinetic control, offers a closer mimicry to biological systems compared to thermodynamic processes.
• Existing non-covalent driving modes for metastable supramolecular systems are limited, necessitating versatile solutions for energy landscape regulation.
• Designing easily tunable energy landscapes is crucial for advancing metastable aggregation research.

Purpose of the Study:

• To introduce a novel coopetition-driven metastability strategy for constructing metastable supramolecular polymers.
• To explore the use of parallel/perpendicular aromatic stacking for controlling supramolecular assembly.
• To demonstrate the application of these systems in dynamic cell imaging.

Main Methods:

• Synthesized simple monomers with lateral indoles and aromatic cores.
• Investigated the effect of varying aromatic core stacking strength (phenyl to anthryl) on aggregate formation.
• Utilized seeding to accelerate the kinetic-to-thermodynamic transformation for living supramolecular polymerization.
• Employed time-dependent emission changes for dynamic cell imaging.

Main Results:

• A coopetition-driven metastability strategy was successfully implemented using parallel/perpendicular aromatic stacking.
• Metastable face-to-face stacked aggregates were formed and subsequently transformed into thermodynamically favorable structures via edge-to-face and offset stacking.
• The transformation process, tunable via seeding, exhibited time-dependent emission shifts from red to yellow.
• Demonstrated successful dynamic cell imaging with reduced background interference.

Conclusions:

• The coopetition of different aromatic stacking modes provides an effective strategy for pathway-controlled metastable supramolecular systems.
• This approach enables the design of functional materials with tunable aggregation pathways.
• The developed system shows promise for advanced applications like dynamic cell imaging.