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Self-Propelling Nanomotors in the Presence of Strong Brownian Forces

2014

Article

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Motility in living systems is due to an array of complex molecular nanomotors that are essential for the function and survival of cells. These protein nanomotors operate not only despite of but also because of stochastic forces. Artificial means of realizing motility rely on local concentration or temperature gradients that are established across a particle, resulting in slip velocities at the particle surface and thus motion of the particle relative to the fluid. However, it remains unclear if these artificial motors can function at the smallest of scales, where Brownian motion dominates and no actively propelled living organisms can be found. Recently, the first reports have appeared suggesting that the swimming mechanisms of artificial structures may also apply to enzymes that are catalytically active. Here we report a scheme to realize artificial Janus nanoparticles (JNPs) with an overall size that is comparable to that of some enzymes similar to 30 nm. Our JNPs can catalyze the decomposition of hydrogen peroxide to water and oxygen and thus actively move by self-electrophoresis. Geometric anisotropy of the Pt-Au Janus nanoparticles permits the simultaneous observation of their translational and rotational motion by dynamic light scattering. While their dynamics is strongly influenced by Brownian rotation, the artificial Janus nanomotors show bursts of linear ballistic motion resulting in enhanced diffusion.

Author(s): Lee, Tung-Chun and Alarcon-Correa, Mariana and Miksch, Cornelia and Hahn, Kersten and Gibbs, John G. and Fischer, Peer
Journal: NANO LETTERS
Volume: 14
Number (issue): 5
Pages: 2407-2412
Year: 2014

Department(s): Micro, Nano, and Molecular Systems
Bibtex Type: Article (article)

DOI: 10.1021/nl500068n

BibTex

@article{ISI:000336074800026,
  title = {Self-Propelling Nanomotors in the Presence of Strong Brownian Forces},
  author = {Lee, Tung-Chun and Alarcon-Correa, Mariana and Miksch, Cornelia and Hahn, Kersten and Gibbs, John G. and Fischer, Peer},
  journal = {NANO LETTERS},
  volume = {14},
  number = {5},
  pages = {2407-2412},
  year = {2014},
  doi = {10.1021/nl500068n}
}