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Sivakov, Vladimir A.
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article
Silver Coated Platinum Core–Shell Nanostructures on Etched Si Nanowires: Atomic Layer Deposition (ALD) Processing and Application in SERS
Abstract
A new method to prepare plasmonically active noble metal<br/>nanostructures on large surface area silicon nanowires (SiNWs)<br/>mediated by atomic layer deposition (ALD) technology has<br/>successfully been demonstrated for applications of surface-enhanced<br/>Raman spectroscopy (SERS)-based sensing. As host material<br/>for the plasmonically active nanostructures we use dense<br/>single-crystalline SiNWs with diameters of less than 100 nm as<br/>obtained by a wet chemical etching method based on silver nitrate<br/>and hydrofluoric acid solutions. The SERS active metal<br/>nanoparticles/islands are made from silver (Ag) shells as deposited<br/>by autometallography on the core nanoislands made from<br/>platinum (Pt) that can easily be deposited by ALD in the form<br/>of nanoislands covering the SiNW surfaces in a controlled way.<br/>The density of the plasmonically inactive Pt islands as well as<br/>the thickness of noble metal Ag shell are two key factors determining<br/>the magnitude of the SERS signal enhancement and<br/>sensitivity of detection. The optimized Ag coated Pt islands on<br/>SiNWs exhibit great potential for ultrasensitive molecular sensing<br/>in terms of high SERS signal enhancement ability, good stability<br/>and reproducibility. The plasmonic activity of the coreshell<br/>Pt//Ag system that will be experimentally realized in this<br/>paper as an example was demonstrated in numerical finite element<br/>simulations as well as experimentally in Raman measurements<br/>of SERS activity of a highly diluted model dye molecule.<br/>The morphology and structure of the core-shell Pt//Ag nanoparticles<br/>on SiNW surfaces were investigated by scanning- and<br/>transmission electron microscopy. Optimized core–shell nanoparticle<br/>geometries for maximum Raman signal enhancement<br/>is discussed essentially based on the finite element modeling.