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Supramolecular Transformation of Metallacycle-linked Star Polymers Driven by Simple Phosphine Ligand-Exchange Reaction.

Wei ZhengWei WangShu-Ting JiangGuang YangZhen LiXu-Qing WangGuang-Qiang YinYing ZhangHongwei TanXiaopeng LiHongming DingGuosong ChenHai-Bo Yang
Published in: Journal of the American Chemical Society (2018)
As a common phenomenon in biological systems, supramolecular transformations of biomacromolecules lead to specific biological functions as outputs, which thus inspire people to construct biomimetic dynamic systems through supramolecular transformation strategy. It should be noted that well-modulating the artificial macromolecules to fine-tune their properties is of great significance yet still remains a big challenge in polymer chemistry. In this study, through the combination of coordination-driven self-assembly and postassembly ring-opening polymerization, a six-armed star polymer linked by well-defined hexagonal metallacycle as core was successfully prepared. At the same time, the trans-platinum acetylide moieties as transformation sites were anchored onto the discrete metallacycle scaffold. Subsequently, the simple phosphine ligand-exchange reaction induced the conversions of platinum acetylide building blocks with the varied binding angles, which thus resulted in the successive hexagon-rhomboid-hexagon transformations of metallacyclic scaffold, therefore allowing for the corresponding supramolecular transformation of metallacycle-linked star polymers. More importantly, accompanied by such transformation process, property modulation of the resultant polymers has been successfully realized. In a word, by taking advantage of dynamic nature of metal-ligand coordination bonds and simple phosphine ligand-exchange reactions, facile architecture transformation of a star polymer to a linear polymer and back to a star polymer was successfully realized, which may provide a promising approach toward the construction of new dynamic polymeric materials.
Keyphrases
  • water soluble
  • drug delivery
  • energy transfer
  • air pollution
  • signaling pathway
  • machine learning
  • oxidative stress
  • transcription factor
  • cancer therapy
  • diabetic rats
  • high glucose
  • neural network
  • electron transfer