Roman Schuh

Comparison of numerical methods in near-field computation for metallic nanoparticles

Four widely used electromagnetic field solvers are applied to the problem of scattering by a spherical or spheroidal silver nanoparticle in glass. The solvers are tested in a frequency range where the imaginary part of the scatterer refractive index is relatively large. The scattering efficiencies and near-field results obtained by the different methods are compared to each other, as well as to recent experiments on laser-induced shape transformation of silver nanoparticles in glass.

Scattering by particles on or near a plane surface

Computation of light scattering from particles deposited upon a surface is of great interest in the simulation, development and calibration of surface scanners for wafer inspection [1]. More recent applications include laser cleaning [2], scanning near-field optical microscopy (SNOM) [3] and plasmon resonances effects in surface-enhanced Raman spectroscopy (SERS) [4]. Several studies have addressed this scattering problem using different methods. Simplified theoretical models have been developed on the basis of Lorenz-Mie theory and Fresnel surface reflection [5, 6, 7, 8]. A coupled-dipole algorithm has been employed by Taubenblatt and Tran [9] and Nebeker et al. [10] using a three-dimensional array of dipoles to model a feature shape and the Sommerfeld integrals to describe the interaction between a dipole and a surface. The theoretical aspects of the coupled-dipole model has been fully outlined by R. Schmehl [11]. A model based on the discrete source method has been given by Eremin and Orlov [12,13], whereas the transmission conditions at the interface are satisfied analytically and the fields of discrete sources are derived by using the Green tensor for a plane surface. More details on computational methods and experimental results can be found in a book edited by Moreno and Gonzales [14].

Investigation of a measurement technique to estimate concentration and size of inclusions in droplets

Inhomogeneous droplets including small spherical inclusions are characterized by the estimation of droplet diameter, inclusion concentration and inclusion diameter and a measure for the polydispersity of the inclusions. In most cases, it is reasonable to assume that the material parameters are known and therefore the index of refraction and the shape of inclusions. In this paper, the results from a measurement technique are investigated. The method will be evaluated on the basis of light scattering measurements for a range of scattering angles. These measurements have been taken with a fast CCD line scan camera and appropriate optics. An attempt is made to derive information from these measurements only. The continuous wavelet transform, speckle image analysis and turbidity measurement methods are used to estimate the concentration and the diameter of the monodisperse polystyrene particles within a droplet. The droplets, generated by a drop-on-demand droplet generator, are nearly monodisperse. The volume concentration of the inclusions within the suspensions varies between 0.01% and 9%. The inclusions are monodisperse. However, it seems to be possible that they coagulate due to the fast fluid flows at the droplet generation. As a result, the technique may be used only for the estimation of average values of size and concentration of inclusions from the measurements.

The inclusion-concentration measurement of suspension droplets based on Monte Carlo ray tracing

In this paper we analyse suspension droplet light scattering with respect to measuring the size of the host particle and the inclusion concentration. The light-scattering simulations show significant changes in the scattering distribution of suspension droplets with different inclusion concentrations. The evaluation reduces to only two parameters, namely angular fringe spacing and the slope in the scattering domain 30-70°. This method relies on the simulation of scattering with parameters such as the refractive indices of the host and the inclusions and the size of the inclusions.