Regular self-assembled plasmonic nanoparticle superlattices: Characterization, modelling and applications.

Mathias Charconnet, Matiyas Tsegay Korsa, Søren Petersen, Luis M. Liz-Marzán, Jost Adam, Andreas Seifert

Research output: Contribution to conference without publisher/journalConference abstract for conferenceResearch


Noble metal nanoparticles (NPs) are known for their ability to confine visible and near-infrared light at the nanoscale through plasmonic resonances. The plasmonic resonance frequency can be tuned by changing the nanostructure shape, material, or adjacent environment. To extend the features of plasmonic resonances, NPs can be arranged into periodic structures, also called superlattices. Such lattice structures potentially foster inter-particle and inter-cluster interactions through photonic coupling, giving rise to so-called lattice plasmons, which have interesting properties, the potential for high Q factors, strong near-field enhancement, and the potential to be tuned by period, incident angle, and polarization. Moreover, the inner structure of a unit cell (cluster) of such periodic arrangement and its homogeneity has a strong influence on the plasmonic response. Here, we present a self-assembly process that allows us to assemble a controlled number of nanospheres, nanorods, or nano triangles into superlattices on large scale. Capillary forces drive the NP self-assembly, via a nanostructured mold that confines the NPs in periodically arranged wells, yielding NP clusters in a superlattice. The chemical composition of the NP dispersion controls the formation of homogeneous NP superlattices. We studied the impact of homogeneity concerning extinction properties, near-field enhancement, and irregularities of superlattices. Further, we demonstrate the generalization of our process regarding different shapes of NPs. The fabrication of superlattices with a defined number of NPs in each cluster allows us to compare their extinction properties, moreover, to study the formation of hybrid plasmonic modes originating from the individual clusters and the lattice. We support our experimental studies by numerical modeling, thereby calculating the superlattice-induced extinction. To minimize the gap between electromagnetic simulations and experimental characterization, we combine statistical image analysis (based on SEM images of self-assembled clusters), finite-element modeling, and material and structure optimization. To identify the superlattice plasmonic shift for a varying lattice parameter, we analyze the cluster’s near-field electromagnetic response, for weighed superpositions of statistically relevant particle arrangements identified by image analysis. Based on statistical analysis, we introduce and superimpose various geometric irregularities in our model, for matching the fabricated superlattice extinction curve, alongside optimization of particle radius, potential shell thickness and refractive index, and particle materials. By Mie theory and colloidal particle measurements, we calibrate our material model and incorporate the results regarding the gap between self-assembled NPs. We demonstrate polarization effects and extinction spectra with respect to variations of the aforementioned parameters. As a special case, we additionally show how sensitive the system responds when irregularities are introduced. Our results, corroborated by electromagnetic simulations and complemented by surface-enhanced Raman scattering (SERS) measurements, provide insight into the near-field enhancement of nanospheres, nanorods, and nano triangles, arranged in sub-wavelength superlattices of macroscopic dimensions, and give rise to new ideas for plasmon-coupled sensing.


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