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Model-driven optimization of multicomponent self-assembly processes.

Peter A Korevaar1, Christophe Grenier, Albert J Markvoort

  • 1Institute for Complex Molecular Systems, Laboratory of Macromolecular and Organic Chemistry, and Computational Biology Group, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands.

Proceedings of the National Academy of Sciences of the United States of America
|October 9, 2013
PubMed
Summary
This summary is machine-generated.

Researchers developed a method to control molecular self-assembly, preventing unwanted structures. This engineering approach optimizes assembly rates to achieve desired nanostructures, overcoming kinetic barriers.

Keywords:
chiral amplificationkinetic modelingpathway selectionsupramolecular polymerssystems chemistry

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Area of Science:

  • Materials Science
  • Chemical Engineering
  • Supramolecular Chemistry

Background:

  • Multicomponent self-assembly is crucial for creating complex nanostructures.
  • Metastable aggregates often hinder the formation of desired, thermodynamically stable assemblies.
  • Controlling pathway complexity is key to successful self-assembly.

Purpose of the Study:

  • To develop an engineering methodology to circumvent metastable assemblies in multicomponent self-assembly processes.
  • To optimize the rate of assembly along the correct pathway to avoid off-pathway aggregates.
  • To investigate the influence of monomer ratio and temperature on assembly kinetics.

Main Methods:

  • Studied the coassembly of R- and S-chiral enantiomers of a π-conjugated oligo(p-phenylene vinylene) derivative as a model system.
  • Developed a kinetic model to analyze coassembly kinetics.
  • Utilized simulations to explore strategies for circumventing metastable pathways.

Main Results:

  • Identified initial assembly of metastable structures that buffer free monomers, slowing the formation of stable assemblies.
  • Found that metastable assemblies significantly influence the favored pathway when monomer ratios approach 1:1.
  • Demonstrated that assembly is most hindered at intermediate temperatures and can be optimized by tuning cooling rates.

Conclusions:

  • Optimizing assembly rates by controlling cooling rates can improve nanostructure formation.
  • Stepwise increases in the driving force for assembly, via solvent composition changes, can circumvent metastable pathways.
  • The developed methodology offers a strategy to guide self-assembly directly into the desired thermodynamic pathway.