Highly parallel acoustic assembly of microparticles into well-ordered colloidal crystallites.

Published

Journal Article

The precise arrangement of microscopic objects is critical to the development of functional materials and ornately patterned surfaces. Here, we present an acoustics-based method for the rapid arrangement of microscopic particles into organized and programmable architectures, which are periodically spaced within a square assembly chamber. This macroscale device employs two-dimensional bulk acoustic standing waves to propel particles along the base of the chamber toward pressure nodes or antinodes, depending on the acoustic contrast factor of the particle, and is capable of simultaneously creating thousands of size-limited, isotropic and anisotropic assemblies within minutes. We pair experiments with Brownian dynamics simulations to model the migration kinetics and assembly patterns of spherical microparticles. We use these insights to predict and subsequently validate the onset of buckling of the assemblies into three-dimensional clusters by experiments upon increasing the acoustic pressure amplitude and the particle concentration. The simulations are also used to inform our experiments for the assembly of non-spherical particles, which are then recovered via fluid evaporation and directly inspected by electron microscopy. This method for assembly of particles offers several notable advantages over other approaches (e.g., magnetics, electrokinetics and optical tweezing) including simplicity, speed and scalability and can also be used in concert with other such approaches for enhancing the types of assemblies achievable.

Full Text

Duke Authors

Cited Authors

  • Owens, CE; Shields, CW; Cruz, DF; Charbonneau, P; López, GP

Published Date

  • January 2016

Published In

Volume / Issue

  • 12 / 3

Start / End Page

  • 717 - 728

PubMed ID

  • 26558940

Pubmed Central ID

  • 26558940

Electronic International Standard Serial Number (EISSN)

  • 1744-6848

International Standard Serial Number (ISSN)

  • 1744-683X

Digital Object Identifier (DOI)

  • 10.1039/c5sm02348c

Language

  • eng