Diameter distribution by deconvolution (DdD): Absorption spectra as a practical tool for semiconductor nanoparticle PSD determination
Semiconductor nanoparticles (SNPs) are excellent candidates for various applications in fields like solar cells, light emitting diodes or sensors. Their size strongly determines their properties, thus characterizing their size is crucial for applications. In most cases, they are included in complex...
| Autores: | , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2019 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/121648 |
| Acceso en línea: | http://hdl.handle.net/11336/121648 |
| Access Level: | acceso abierto |
| Palabra clave: | Q-dots size distribution exciton mesoporous oxides https://purl.org/becyt/ford/1.4 https://purl.org/becyt/ford/1 |
| Sumario: | Semiconductor nanoparticles (SNPs) are excellent candidates for various applications in fields like solar cells, light emitting diodes or sensors. Their size strongly determines their properties, thus characterizing their size is crucial for applications. In most cases, they are included in complex matrices which make it difficult to determine their average diameter and statistical distribution. In this work, we present a non-destructive, cheap and in situ procedure to calculate particle size distributions (PSDs) of SNPs in different media based on deconvolution of the absorbance spectrum with a database of the absorbance spectra of SNPs with different sizes. The method was validated against the SNP sizes obtained from transmission microscopy images, showing excellent agreement between both distributions. In particular, CdS SNPs embedded in mesoporous thin films were analyzed in detail. Additional composite systems were studied in order to extend the method to SNPs in polymers or bacteria, proving that it applies to several SNPs in diverse matrices. The PSDs obtained from the proposed method do not show any statistical difference with the one derived from TEM images. Finally, a web app that implements the methodology of this work has been developed. |
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