Rapid Deposition of Uniform Polydopamine Coatings on Nanoparticle Surfaces with Controllable Thickness.

نویسندگان

  • Nazar Orishchin
  • Cameron C Crane
  • Matthew Brownell
  • Tengjiao Wang
  • Samuel Jenkins
  • Min Zou
  • Arun Nair
  • Jingyi Chen
چکیده

Polydopamine is a bioinspired, versatile material that can adhere to bulk and nanoscale surfaces made of disparate materials to improve their physical and chemical properties in many applications. The typical methods to coat polydopamine on the nanoparticle substrates usually take several hours to a day. This work successfully applies a dispersion method to form a controllable, uniform coating on a nanoparticle surface within minutes. Using plasmonic Ag nanoparticles as a substrate, the coating thickness can be monitored using a spectroscopic method based on the extinction peak shifts of the Ag nanoparticles. The deposition rate increases with dopamine concentration; however, too much excess dopamine leads to the formation of free dopamine particles. The optimized concentration of dopamine (i.e., ∼6 mM) can be applied to other nanoparticles by normalizing the number of particles to maintain a constant concentration of dopamine per unit surface area (i.e., 1.70 × 104 dopamine/nm2). The molecular dynamics simulation reveals that the amount of hydrogen bonding increases with water content, suggesting that sufficient mixing using the dispersion tool facilitates the formation of hydrogen bonding, thus rapidly depositing PDA on the nanoparticle surface. The physical and chemical properties (e.g., pH response and thermal stability) can be tailored by varying the coating thickness due to the changes in the number of hydrogen bonds and the conformation of π-π interactions. This dispersion method provides a facile means to control the PDA coating thickness on nanoparticle surfaces and thus the surface properties of nanoparticles toward various applications.

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عنوان ژورنال:
  • Langmuir : the ACS journal of surfaces and colloids

دوره 33 24  شماره 

صفحات  -

تاریخ انتشار 2017