論文

査読有り
2016年9月

Self-assembly of like-charged nanoparticles into Voronoi diagrams

PHYSICAL CHEMISTRY CHEMICAL PHYSICS
  • Daniel Zambo
  • ,
  • Kohta Suzuno
  • ,
  • Szilard Pothorszky
  • ,
  • Dora Bardfalvy
  • ,
  • Gabor Hollo
  • ,
  • Hideyuki Nakanishi
  • ,
  • Dawei Wang
  • ,
  • Daishin Ueyama
  • ,
  • Andras Deak
  • ,
  • Istvan Lagzi

18
36
開始ページ
25735
終了ページ
25740
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1039/c6cp04297j
出版者・発行元
ROYAL SOC CHEMISTRY

The self-assembly of nanoscopic building blocks into higher order macroscopic patterns is one possible approach for the bottom-up fabrication of complex functional systems. Macroscopic pattern formation, in general, is determined by the reaction and diffusion of ions and molecules. In some cases macroscopic patterns emerge from diffusion and interactions existing between nanoscopic or microscopic building blocks. In systems where the distribution of the interaction-determining species is influenced by the presence of a diffusion barrier, the evolving macroscopic patterns will be determined by the spatiotemporal evolution of the building blocks. Here we show that a macroscopic pattern can be generated by the spatiotemporally controlled aggregation of like-charged carboxyl-terminated gold nanoparticles in a hydrogel, where clustering is induced by the screening effect of the sodium ions that diffuse in a hydrogel. Diffusion fronts of the sodium ions and the induced nanoparticle aggregation generate Voronoi diagrams, where the Voronoi cells consist of aggregated nanoparticles and their edges are aggregation-free and nanoparticle-free zones. We also developed a simple aggregation-diffusion model to adequately describe the evolution of the experimentally observed Voronoi patterns.

リンク情報
DOI
https://doi.org/10.1039/c6cp04297j
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000384249300105&DestApp=WOS_CPL
ID情報
  • DOI : 10.1039/c6cp04297j
  • ISSN : 1463-9076
  • eISSN : 1463-9084
  • Web of Science ID : WOS:000384249300105

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