Au-WO3 Nanocomposite Coatings for Localized Surface Plasmon Resonance Sensing

• Autor(a) principal: Figueiredo, Nuno M.
• Data de Publicação: 2020
• Outros Autores: Vaz, Filipe, Cunha, Luís, Cavaleiro, Albano
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10316/106363; https://doi.org/10.3390/ma13010246
• topic: localized surface plasmon resonance (LSPR) sensing; Au-WO3 nanocomposites; Au nanoparticles; refractive index sensitivity; optical properties

Localized surface plasmon resonance (LSPR) gas sensors are gaining increasing importance due to their unique tuneable functional properties. Au-WO3-x nanocomposite coatings, in particular, can be outstandingly sensitive to many different gases. However, a proper understanding of their optical properties and the way in which those properties are correlated to their structure/microstructure, is still needed. In this work, Au-WO3 nanocomposite coatings, with Au contents between 0-11 atomic percent, were grown using reactive magnetron co-sputtering technique and were characterized concerning their optical response. The precipitation of Au nanoparticles in the oxide matrix was promoted through thermal annealing treatments until 500 °C. Along with the Au nanoparticles' morphological changes, the annealing treatments stimulated the crystallization of WO3, together with the appearance of oxygen-deficient WO3-x phases. Through theoretical simulations, we have related the LSPR effect with the different structural and morphological variations (namely, size and distribution of the nanoparticles and their local environment), which were a function of the Au content and annealing temperature. Our results suggest that local voids were present in the vicinity of the Au nanoparticles, for all temperature range, and that they should be present in a wide variety of Au-WO3 nanocomposites. A theoretical study concerning the refractive index sensitivity was carried out in order to predict the optimal coating design parameters for gas sensing experiments.