This paper presents a simple alternative to dynamic light scattering (DLS) time series processing by using an artificial neural network. A simple experiment for recording a DLS time series is presented. The reference method for DLS time series processing consisted of fitting the analytical form of the Lorentzian line to the frequency spectrum of the recorded scattered light intensity. An artificial neural network with one hidden layer was designed and trained. The training data consisted of a big set of autocorrelations of simulated time series for monodispersed spherical particles with diameters in the range 10–1200 µm. The neural network output precision was tested both on simulated and on experimental time series recorded on fluids containing nanoparticles and microparticles. The errors of the artificial neural network output relative to the reference diameters were small enough and the data processing procedure was three orders of magnitude faster, proving that, in spite of the simplicity, the artificial neural networks approach can be a faster alternative for DLS time series processing.

A coherent light scattering experiment on wastewater samples extracted from several stages of water processing within a wastewater processing plant was carried out. The samples were allowed to sediment while they were the subject of a Dynamic Light Scattering (DLS) measurement. The recorded time series were processed using an Artificial Neural Network based DLS procedure to produce the average diameter of the particles in suspension. The method, using a single physical procedure for monitoring the variation of the average diameter in time, indicates the dominant type of suspensions in water.

Using a Lorentzian function fit as reference, a basic experiment was designed for processing IntroductionThe study of nanoparticles is a topic of major interest in the last decades due to the wide array of applications, especially in the area of biology and medicine. As a consequence of their small size, one order of magnitude smaller than the living cells, they can be used to deliver various substances to living cells, producing, in general, only minor perturbations. The applications of these nanomaterials were presented in several papers, such as [1]. During development of these applications, there were concerns about the toxicity of these methods. As a result, techniques for monitoring the nanoparticles concentration were also developed [2].The properties of the systems of nanoparticles are in direct relation to the size distribution of the particles in the fluid. For this reason, the size characterization of these systems is one relevant aspect for further development of the nanotechnology applications. There are various techniques used for this. One modern technique is the Transmission Electron Microscopy (TEM) which evaluates particles in the range from nanometers to micrometers. This method has a good resolution but is in general expensive, time consuming and does not work in-situ. Another method is the X-Ray powder diffraction which can offer the size distribution of the particles [3]. For metal oxides, for which the assumption used is that the crystallite size is the same as the particle size, the Scherrer equation [4] can offer the mean particle size. For colloidal particles, the Guinier formula [5] can be used in a similar way. However, also these two methods are slow and do not work in-situ. The particle size for nano-systems can also be assessed by the method called "Atomic Force Microscopy" (AFM) [6], [7]. Paper [7] shows a comparison of AFM with TEM. Results show that AFM sizing requires very thin samples over several layers. The samples are scanned line by line and this takes a lot of time. Comparisons and reviews of other techniques used for nanoparticle size characterization are presented in many papers, such as [8]. As in [9], the properties of the nanofluid change very fast during nanoparticle aggregation, and as a consequence, a fast procedure for monitoring the size is needed. A valid option for this are the optical procedures, which use coherent light scattering.The optical methods make use of an incident coherent beam of light which illuminates an active sample volume containing the nanoparticles. Each particle represents a scattering center and becomes a secondary light source. The intensity of the scattered light is anisotropic and depends on the size and shape of the scattering centers. This is described by the phase function, for which there are several models used to represent it [10], [11], [12].If the incident beam is coherent, so are the secondary waves emitted by each scattering center. If a screen or a detector is present, all the wavelets emitted by all the scattering...

Выведены и записаны в максимально редуцированном виде замкнутые представления одно- и двукратного преобразований Лапласа хюльтеновской функции Грина уходящей волны, умноженной на потенциал Ямагучи. Выражения для двукратного преобразования используются при вычислении низкоэнергетического фазового сдвига при упругом рассеянии в системах $\alpha$-нуклон, $\alpha$-$He^3$ и $\alpha$-$H^3$. Результаты расчета хорошо согласуются с экспериментальными данными.

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