Both in design and production of nanoparticles and nanocomposites it is of vital importance to have information about their size and concentration. During the formation of nanoparticles, real-time monitoring of particle size and concentration during bottom-up synthesis in liquids allows for a detailed study of nucleation and growth. This provides valuable insights into the formation of nanoparticles that can be used for process optimization and scale up. In the production of nanoparticles, real-time monitoring enables intervention to minimize the number of off-spec batches. In this paper we will qualify an ultrasound nanoparticle sizer (UNPS) as a real-time monitor for the growth of nanoparticles (or sub-micro particles) in the 100 nm-1 μm range. Nanoparticles affect the speed and attenuation of ultrasonic waves in the dispersion. The size of the change depends, amongst other things, on the size and concentration of the nanoparticles. This dependency is used in the UNPS method. The qualification of the UNPS was undertaken in two successful experiments. The first experiment consisted of static measurements on commercially available silica particles, and the second experiment was real-time monitoring of the size and concentration during the growth of silica nanoparticles in Stöber synthesis in a water-alcohol mixture starting from the molecular precursor tetraethyl orthosilicate. The results of the UNPS were verified by measurements of a dynamic light scattering device and a transmission electron microscope.@en

The use of phased arrays is growing in the non-destructive testing industry and the trend is towards large 2D arrays, but due to limitations, it is currently not possible to record the signals from all elements, resulting in aliased data. In the past, we have presented a data interpolation scheme 'beyond spatial aliasing' to overcome this aliasing. In this paper, we present a different approach: blending and deblending of data. On the hardware side, groups of receivers are blended (grouped) in only a few transmit/recording channels. This allows for transmission and recording with all elements, in a shorter acquisition time and with less channels. On the data processing side, this blended data is deblended (separated) by transforming it to a different domain and applying an iterative filtering and thresholding. Two different filtering methods are compared: f-k filtering and wavefield extrapolation filtering. The deblending and filtering methods are demonstrated on simulated experimental data. The wavefield extrapolation filtering proves to outperform f-k filtering. The wavefield extrapolation method can deal with groups of up to 24 receivers, in a phased array of 48 × 48 elements.@en