Temporal Flux Organization as a Principle for Network-Controlled Self-Assembly

Area of Science:

• Chemistry
• Materials Science
• Chemical Engineering

Background:

• Traditional self-assembly is classified as thermodynamically or kinetically controlled.
• Dynamic systems with reversible reactions pose challenges for predictable self-assembly outcomes.
• Understanding how to achieve high yields and selectivity in reversible systems is crucial.

Purpose of the Study:

• Introduce network-controlled self-assembly as a framework for understanding reversible systems.
• Demonstrate how temporal organization of reaction flux enables selective pathway selection.
• Showcase catalytic modulation for yield amplification in metal-organic cage formation.

Main Methods:

• Quantitative Analysis of Self-Assembly Process (QASAP) to analyze experimental time-series data.
• Numerical Analysis of Self-Assembly Process (NASAP) for reaction network modeling and flux analysis.
• Case studies involving metal-organic cage (MOC) formation (M6L4 truncated tetrahedron and square-based pyramid).

Main Results:

• Temporal flux organization generates quasi-irreversible behavior in fully reversible networks.
• Pathway competition in MOC formation showed dominant pathway selection over time.
• Catalytic modulation amplified product yield by reorganizing temporal flux and suppressing intermediates.

Conclusions:

• Network-controlled self-assembly provides a new paradigm for designing self-assembled systems.
• Temporal flux organization is a unifying principle linking microscopic kinetics to macroscopic outcomes.
• This framework enables rational control of pathways and yields in dynamic reaction networks.