Image processing for the characterization of porous silicon nanostructure

Abstract

Abstract This paper presents a new method based on image processing (IP) for the characterization of porous silicon (PS) nanostructures. It was developed using porous silicon layers (PS 1 and PS 2 ) having different nanostructures. According to gravimetric measurements, these layers present the same porosity of 45%. First we characterized the PS layers by Barrett‐Joyner‐Halenda (BJH) theory applied to sorption data. Then applying BJH theory, we found that the mean pore diameter of PS 1 and PS 2 are 4.3 and 5.5 nm respectively. With Brunauer‐Emmet‐Teller (BET) theory, we found that PS 1 has a specific area of 330 m 2 /g, and PS 2 has a specific area of 223 m 2 /g. We obtained images of the PS layer surface by high resolution scanning electronic microscopy (HRSEM). The processing of these images leads to the estimation of mean pore diameter: 5.6 nm and 7.5 nm for PS 1 and PS 2 respectively, and to the representation of pore size distribution. According to a geometrical model, we estimated the porosity and found 55% and 48% for PS 1 and PS 2 respectively. The calculation of specific area according to the same model leads to the values of 343 m 2 /g and 217 m 2 /g for PS 1 and PS 2 respectively. The close agreement of results obtained by IP to those obtained by sorption theories shows the validity of our method. Advantages of images processing are discussed. (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)