<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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.</p></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.

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

Acta Universitatis Cibiniensis. Technical Series

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Using a Lorentzian function fit as reference, a basic experiment was designed for processing Dynamic Light Scattering time series, allowing to estimate the...

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

Pubblicato online: 11 gen 2018

Pagine: 155 - 161

DOI: https://doi.org/10.1515/aucts-2017-0020

Parole chiave
Dynamic Light Scattering, Suspensions, Particles, Neural Networks, Time Series

© 2018

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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

Pubblicato online: 11 gen 2018

Pagine: 155 - 161

DOI: https://doi.org/10.1515/aucts-2017-0020

Parole chiaveDynamic Light Scattering, Suspensions, Particles, Neural Networks, Time Series

© 2018

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Parole chiave
Dynamic Light Scattering, Suspensions, Particles, Neural Networks, Time Series