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Structure and vacancy distribution in copper telluride nanoparticles influence plasmonic activity in the near-infrared

Copper chalcogenides find applications in different domains including photonics, photothermal therapy and photovoltaics. CuTe nanocrystals have been proposed as an alternative to noble metal particles for plasmonics. Although it is known that deviations from stoichiometry are a prerequisite for plas...

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Detalles Bibliográficos
Autores principales: Willhammar, Tom, Sentosun, Kadir, Mourdikoudis, Stefanos, Goris, Bart, Kurttepeli, Mert, Bercx, Marnik, Lamoen, Dirk, Partoens, Bart, Pastoriza-Santos, Isabel, Pérez-Juste, Jorge, Liz-Marzán, Luis M., Bals, Sara, Van Tendeloo, Gustaaf
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5379103/
https://www.ncbi.nlm.nih.gov/pubmed/28358039
http://dx.doi.org/10.1038/ncomms14925
Descripción
Sumario:Copper chalcogenides find applications in different domains including photonics, photothermal therapy and photovoltaics. CuTe nanocrystals have been proposed as an alternative to noble metal particles for plasmonics. Although it is known that deviations from stoichiometry are a prerequisite for plasmonic activity in the near-infrared, an accurate description of the material and its (optical) properties is hindered by an insufficient understanding of the atomic structure and the influence of defects, especially for materials in their nanocrystalline form. We demonstrate that the structure of Cu(1.5±x)Te nanocrystals can be determined using electron diffraction tomography. Real-space high-resolution electron tomography directly reveals the three-dimensional distribution of vacancies in the structure. Through first-principles density functional theory, we furthermore demonstrate that the influence of these vacancies on the optical properties of the nanocrystals is determined. Since our methodology is applicable to a variety of crystalline nanostructured materials, it is expected to provide unique insights concerning structure–property correlations.