scholarly journals Dynamic Light Scattering Signal Conditioning for Data Processing

2017 ◽  
Vol 69 (1) ◽  
pp. 130-135
Author(s):  
Silviu Rei ◽  
Dan Chicea ◽  
Beriliu Ilie ◽  
Sorin Olaru
Keyword(s):  
Time Series ◽  
Light Scattering ◽  
Dynamic Light Scattering ◽  
Data Processing ◽  
Electrical Signal ◽  
Signal Conditioning ◽  
Scattering Experiment ◽  
Logical Unit ◽  
Scattering Signal ◽  
Digital Time

Abstract When performing data acquisition for a Dynamic Light Scattering experiment, one of the most important aspect is the filtering and conditioning of the electrical signal. The signal is amplified first and then fed as input for the analog digital convertor. As a result a digital time series is obtained. The frequency spectrum is computed by the logical unit offering the basis for further Dynamic Light Scattering analysis methods. This paper presents a simple setup that can accomplish the signal conditioning and conversion to a digital time series.

Reappearance of slow mode in mixtures of polyethylene glycol and poly(sodium methacrylate)

Soft Matter ◽  
2018 ◽  
Vol 14 (24) ◽  
pp. 5039-5047
Author(s):  
Ksenija Kogej ◽  
Jaka Štirn ◽  
Jurij Reščič
Keyword(s):  
Polyethylene Glycol ◽  
Light Scattering ◽  
Dynamic Light Scattering ◽  
Ethylene Glycol ◽  
Slow Mode ◽  
Poly Ethylene Glycol ◽  
Poly Ethylene ◽  
Scattering Signal ◽  
Sodium Methacrylate

After addition of poly(ethylene glycol) to a solution of poly(sodium methacrylate), the slow-mode dynamic light scattering signal reappears.

Simulation of dynamic light scattering signal for ultrafine particles based on the exponential model

2010 ◽  
Vol 6 (4) ◽  
pp. 302-305 ◽  
Author(s):  
Ya-jing Wang ◽  
Gang Zheng ◽  
Jin Shen ◽  
Wei Liu ◽  
Xin-jun Zhu
Keyword(s):  
Light Scattering ◽  
Dynamic Light Scattering ◽  
Ultrafine Particles ◽  
Exponential Model ◽  
Scattering Signal

scholarly journals An Advanced Sensor for Particles in Gases Using Dynamic Light Scattering in Air as Solvent

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5115
Author(s):  
Dan Chicea ◽  
Cristian Leca ◽  
Sorin Olaru ◽  
Liana Maria Chicea
Keyword(s):  
Particle Size ◽  
Light Scattering ◽  
Light Intensity ◽  
Dynamic Light Scattering ◽  
Scattered Light ◽  
Experimental Setup ◽  
Scattering Experiment ◽  
Processing Procedure ◽  
Average Size ◽  
Data Processing Procedure

Dynamic Light Scattering is a technique currently used to assess the particle size and size distribution by processing the scattered light intensity. Typically, the particles to be investigated are suspended in a liquid solvent. An analysis of the particular conditions required to perform a light scattering experiment on particles in air is presented in detail, together with a simple experimental setup and the data processing procedure. The results reveal that such an experiment is possible and using the setup and the procedure, both simplified to extreme, enables the design of an advanced sensor for particles and fumes that can output the average size of the particles in air.

scholarly journals Using Dynamic Light Scattering for Monitoring the Size of the Suspended Particles in Wastewater

2019 ◽  
Vol 21 (3) ◽  
pp. 1-10 ◽  
Author(s):  
Dan Chicea ◽  
Silviu Mihai Rei
Keyword(s):  
Neural Network ◽  
Light Scattering ◽  
Dynamic Light Scattering ◽  
Average Diameter ◽  
Processing Plant ◽  
Coherent Light ◽  
Dominant Type ◽  
Scattering Experiment ◽  
The Subject ◽  
Wastewater Samples

Abstract 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.

scholarly journals Using Dynamic Light Scattering Experimental Setup and Neural Networks For Particle Sizing

2017 ◽  
Vol 69 (1) ◽  
pp. 155-161
Author(s):  
Silviu Rei ◽  
Dan Chicea
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Light Scattering ◽  
Dynamic Light Scattering ◽  
Average Particle Size ◽  
Average Particle ◽  
Particle Sizing ◽  
Proof Of Concept ◽  
Scattering Time ◽  
Averaged Power Spectrum

Abstract Using a Lorentzian function fit as reference, a basic experiment was designed for processing Dynamic Light Scattering time series, allowing to estimate the average particle size of a suspension. For fitting the averaged power spectrum of the time series, several neural network configurations were tested in order to compare the results with the reference. The results of this comparison revealed a good match, serving as a proof of concept for using neural networks as an alternative for DLS time series processing.

scholarly journals Profiling Suspensions in Natural Water by a Simplified Dynamic Light Scattering Procedure and Sedimentation

2015 ◽  
Vol 17 (2) ◽  
pp. 1-10
Author(s):  
Dan Chicea ◽  
Liana-Maria Chicea
Keyword(s):  
Light Scattering ◽  
Dynamic Light Scattering ◽  
Natural Water ◽  
Average Diameter ◽  
Least Square ◽  
Coherent Light ◽  
Time Intervals ◽  
Dominant Type ◽  
Scattering Experiment ◽  
Water Suspensions

Abstract A coherent light scattering experiment was carried out. The samples were aqueous natural water suspensions picked from the same river. While sedimentation occurred in the samples, they were subjected to a dynamic light scattering (DLS) experiment and the time series was recorded at certain time intervals. For each recording, a program written for this purpose, performing at least square minimisation, computed the average diameter of the particles in suspension. The variation of the average diameter in time indicates the dominant type of suspensions in water.

scholarly journals An Artificial Neural Network Assisted Dynamic Light Scattering Procedure for Assessing Living Cells Size in Suspension

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3425 ◽  
Author(s):  
Dan Chicea
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Artificial Neural Network ◽  
Light Scattering ◽  
Dynamic Light Scattering ◽  
Training Procedure ◽  
Particle Size Range ◽  
Processing Procedure ◽  
Long Time ◽  
Artificial Neural

Dynamic light scattering (DLS) is an essential technique used for assessing the size of the particles in suspension, covering the range from nanometers to microns. Although it has been very well established for quite some time, improvement can still be brought in simplifying the experimental setup and in employing an easier to use data processing procedure for the acquired time-series. A DLS time series processing procedure based on an artificial neural network is presented with details regarding the design, training procedure and error analysis, working over an extended particle size range. The procedure proved to be much faster regarding time-series processing and easier to use than fitting a function to the experimental data using a minimization algorithm. Results of monitoring the long-time variation of the size of the Saccharomyces cerevisiae during fermentation are presented, including the 10 h between dissolving from the solid form and the start of multiplication, as an application of the proposed procedure. The results indicate that the procedure can be used to identify the presence of bigger particles and to assess their size, in aqueous suspensions used in the food industry.

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