Plasmonic Nanoparticle-Based Metamaterials: From Electric to Magnetic Response

  • José Dintinger
  • Toralf Scharf
Part of the Nano-Optics and Nanophotonics book series (NON)


The self-assembly of nanoparticles into hierarchical architectures is currently attracting a lot of interest due to their potential applications in a wide range of fields like nanophotonics, nanoelectronics or catalysis. In the present chapter, we discuss the potential of metal nanospheres for the bottom-up fabrication of optical metamaterials. Controlling the spatial arrangement of the nanoparticles in these composites offers a promising route to engineer unique optical responses originating from their collective plasmonic resonance. Here we explore experimentally how different types of NP arrangements can give rise to distinct macroscopic effective properties, including both electric and magnetic optical responses. For each of the structures investigated, we propose a brief overview of the current state-of-the-art of the appropriate bottom-up fabrication methods and analyze their optical properties in details. First, the optical constants of “bulk” amorphous nanoparticle metamaterials are investigated by ellipsometry, demonstrating that controlling the nanoparticle filling fraction provides an efficient route to tune the metamaterial permittivity. As an example of a potential application, the realization of a hybrid plasmonic Bragg mirror is discussed. Finally, we focused on the fabrication and characterization of dense spherical nanoclusters that can sustain a magnetic response at optical frequencies. In doing so, we demonstrate the possibility to engineer the permeability of nanocluster-based metamaterials, thereby opening interesting perspectives for the realization of isotropic negative index materials operating in the visible.


Surface Enhance Raman Scatter Localize Surface Plasmon Resonance Effective Permittivity Dipolar Magnetic Resonance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was funded by the European Union’s Seven Framework Programme (FP7/2007-2013) under grant agreement n228455 (Nanogold project). We thank Carsten Rockstuhl, Stefan Mühlig and Tobias Kienzler for their input and support regarding the theoretical aspects of this work, and Houda Sellame for the preparation of multilayer samples.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Optics & Photonics Technology LaboratoryEcole Polytechnique Fédérale de Lausanne (EPFL)NeuchâtelSwitzerland

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