Issue 9, 2019

Diameter distribution by deconvolution (DdD): absorption spectra as a practical tool for semiconductor nanoparticle PSD determination

Abstract

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.

Graphical abstract: Diameter distribution by deconvolution (DdD): absorption spectra as a practical tool for semiconductor nanoparticle PSD determination

Supplementary files

Article information

Article type
Paper
Submitted
01 Jun 2019
Accepted
08 Jul 2019
First published
11 Jul 2019
This article is Open Access
Creative Commons BY-NC license

Nanoscale Adv., 2019,1, 3499-3505

Diameter distribution by deconvolution (DdD): absorption spectra as a practical tool for semiconductor nanoparticle PSD determination

D. Onna, I. Perez Ipiña, A. Fernández Casafuz, Á. Mayoral, M. R. Ibarra García, S. A. Bilmes and M. L. Martínez Ricci, Nanoscale Adv., 2019, 1, 3499 DOI: 10.1039/C9NA00344D

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