ABSTRACT
Imaging ellipsometry is an optical characterization tool that is widely used to investigate the spatial variations of the opto-geometrical properties of thin films. As ellipsometry is an indirect method, an ellipsometric map analysis requires a modeling step. Classical methods such as the Levenberg-Marquardt algorithm (LM) are generally too time consuming to be applied on a large data set. In this way, an artificial neural network (ANN) approach was introduced for the analysis of an ellipsometric map. As a proof of concept this method was applied for the characterization of silver nanoparticles embedded in a poly-(vinyl alcohol) film. We demonstrate that the LM and ANN give similar results. However, the time required for the ellipsometric map analysis decreases from 15 days for the LM to 1â s for the ANN. This suggests that the ANN is a powerful tool for fast spectroscopic-ellipsometric-imaging analysis.
ABSTRACT
We investigate the productivity of ultra-small gold nanoparticles generated by pulsed-laser ablation in liquid of a high-speed rotating gold target as functions of laser ablation time and rotation speed of the target in the range 90-3000 rpm. These experiments were performed byin situmonitoring the extinction spectra of the gold colloidal suspension. The time evolution of the gold volume fraction in the colloidal suspension of the target was determined by modeling the extinction spectra using the shape distribution effective medium theory. The time dependence of the ablation rate, deduced from that of the volume fraction, shows an initial exponential decay followed by a steady-state value at longer ablation time. The influence of the laser-induced roughening of the target surface on the time evolution of the ablation rate is clearly demonstrated. The experimental results also reveal the dependence of the time evolution of the ablation rate of the target on its rotation speed. The effect of the liquid flow on the ablation rate of the target is analyzed and discussed.
ABSTRACT
In this Letter, we propose a new, to the best of our knowledge, approach to determine the shape distribution of gold (Au) nanorods from real-time extinction spectroscopy measurements. This method is based on the linearization of the shape distribution effective medium theory (SDEMT). The aspect ratio distribution of Au colloids is obtained in a few tens of ms without any a priori information on the distribution. Both bimodal and monomodal shape distributions of nanoparticles can be extracted by analyzing their extinction spectra. The proposed method is applied to monitor the change in the nanoparticle shape during their exposure to ns-laser pulses.
ABSTRACT
Due to their tunable physical and chemical properties, alloys are of fundamental importance in material science. The determination of stoichiometry is crucial for alloy engineering. Classical characterization tools such as energy-dispersive x-ray spectroscopy (EDX) are time consuming and cannot be performed in an ambient atmosphere. In this context, we introduce a new methodology to determine the stoichiometry of alloys from ellipsometric measurements. This approach, based on the analysis of ellipsometric spectra by an artificial neural network (ANN), is applied to electrum alloys. We demonstrate that the accuracy of this approach is of the same order of magnitude as that of EDX. In addition, the ANN analysis is sufficiently robust that it can be used to characterize rough alloys. Finally, we demonstrate that the exploitation of ellipsometric maps with the ANN is a powerful tool to determine composition gradients in alloys.
Subject(s)
Alloys , Neural Networks, Computer , Alloys/chemistry , Spectrometry, X-Ray EmissionABSTRACT
We propose an advanced in situ extinction spectroscopy set up to investigate the dynamic of the fragmentation and reshaping processes of gold colloids during a ns-laser pulse exposure. The evolution of the aspect ratio distribution of gold nanorods (NRs) during the laser exposure is obtained by analyzing each spectra with the shape distributed effective medium theory. We demonstrate that the kinetics of NR shape transformation can be divided into two fluence regimes. At small fluence, the kinetic is limited by the NRs orientation, while at high fluence, the fragmentation rate is only limited by the probability of NRs to be located in the irradiated volume.
ABSTRACT
We studied the nanosecond laser-induced shape modifications of Ag colloids exposed to a converging laser beam during the ablation of a Ag target in water. To this end, we performed a series of laser ablation experiments in which the laser energy was varied while all other parameters were kept constant. In addition to transmission electron microscopy (TEM), the shape distribution of the Ag nanoparticles was determined by modelling the extinction spectra of the final colloidal solutions using theoretical calculations based on shape distributed effective medium theory (SDEMT). From these calculations, two physical parameters named sphericity and dispersity were introduced and used to gauge the evolution of the shape distribution of the particles. As the laser energy on the target was increased from 5 to 20 mJ/pulse, an apparently abrupt modification of the shape distribution of the particles was evidenced by both TEM and SDEMT calculations. This change is explained in terms of competitive fragmentation, growth and reshaping processes. On the basis the heating-melting-vaporization model, we demonstrate how the competition between these processes, occurring at different locations of the converging beam, determines the shape distribution of the final product. We highlight the relevance of the fluence gradient along the beam path and the laser interaction volume on the laser-induced modifications of the suspended particles during the ablation process.
