Imaging Si nanoparticles embedded in SiO 2 layers by (S)TEM-EELS

Abstract

Fabrication of systems in which Si nanoparticles are embedded in a thin silica layer is today mature for non-volatile memory and opto-electronics applications. The control of the different parameters (position, size and density) of the nanoparticles population is a key point to optimize the properties of such systems. A review of dedicated transmission electron microscopy (TEM) methods, which can be used to measure these parameters, is presented with an emphasis on those relying on electron energy-loss spectroscopy (EELS). Defocused bright-field imaging can be used in order to determine topographic information of a whole assembly of nanoparticles, but it is not efficient for looking at individual nanoparticles. High-resolution electron imaging or dark-field imaging can be of help in the case of crystalline particles but they always provide underestimated values of the nanocrystals population. EELS imaging in the low-energy-loss domain around the Si plasmon peak, which gives rise to strong signals, is the only way to visualize all Si nanoparticles within a silica film and to perform reliable size and density measurements. Two complementary types of experiments are investigated and discussed more extensively: direct imaging with a transmission electron microscope equipped with an imaging filter (EFTEM) and indirect imaging from spectrum-imaging data acquired with a scanning transmission electron microscope equipped with a spectrometer (STEM-PEELS). The direct image (EFTEM) and indirect set of spectra (STEM-PEELS) are processed in order to deliver images where the contribution of the silica matrix is minimized. The contrast of the resulting images can be enhanced with adapted numerical filters for further morphometric analysis. The two methods give equivalent results, with an easier access for EFTEM and the possibility of a more detailed study of the EELS signatures in the case of STEM-PEELS. Irradiation damage in such systems is also discussed.