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Hierarchical Self-Assembly of Multidimensional Functional Materials from Sequence-Defined Peptoids.

Li ShaoDehong HuShao-Liang ZhengThi Kim Hoang TrinhWenhao ZhouHaoyu WangYanxu ZongChangning LiChun-Long Chen
Published in: Angewandte Chemie (International ed. in English) (2024)
Hierarchical self-assembly represents a powerful strategy for the fabrication of functional materials across various length scales. However, achieving precise formation of functional hierarchical assemblies remains a significant challenge and requires a profound understanding of molecular assembly interactions. In this study, we present a molecular-level understanding of the hierarchical assembly of sequence-defined peptoids into multidimensional functional materials, including twisted nanotube bundles serving as a highly efficient artificial light harvesting system. By employing synchrotron-based powder X-ray diffraction and analyzing single crystal structures of model compounds, we elucidated the molecular packing and mechanisms underlying the assembly of peptoids into multidimensional nanostructures. Our findings demonstrate that incorporating aromatic functional groups, such as tetraphenyl ethylene (TPE), at the termini of assembling peptoid sequences promotes the formation of twisted bundles of nanotubes and nanosheets, thus enabling the creation of a highly efficient artificial light harvesting system. This research exemplifies the potential of leveraging sequence-defined synthetic polymers to translate microscopic molecular structures into macroscopic assemblies. It holds promise for the development of functional materials with precisely controlled hierarchical structures and designed functions.
Keyphrases
  • highly efficient
  • high resolution
  • magnetic resonance imaging
  • computed tomography
  • climate change
  • psychometric properties
  • deep learning
  • artificial intelligence