Version 1
: Received: 28 August 2023 / Approved: 28 August 2023 / Online: 29 August 2023 (08:30:55 CEST)
How to cite:
Annenkov, V. Study of Nanoparticles by Dynamic Light Scattering: Processing Challenges. Preprints2023, 2023081929. https://doi.org/10.20944/preprints202308.1929.v1
Annenkov, V. Study of Nanoparticles by Dynamic Light Scattering: Processing Challenges. Preprints 2023, 2023081929. https://doi.org/10.20944/preprints202308.1929.v1
Annenkov, V. Study of Nanoparticles by Dynamic Light Scattering: Processing Challenges. Preprints2023, 2023081929. https://doi.org/10.20944/preprints202308.1929.v1
APA Style
Annenkov, V. (2023). Study of Nanoparticles by Dynamic Light Scattering: Processing Challenges. Preprints. https://doi.org/10.20944/preprints202308.1929.v1
Chicago/Turabian Style
Annenkov, V. 2023 "Study of Nanoparticles by Dynamic Light Scattering: Processing Challenges" Preprints. https://doi.org/10.20944/preprints202308.1929.v1
Abstract
Nanoparticles are of great importance for various scientific and technological applications, drug discovery, ecology, molecular biology, etc. Size is a basic characteristic of any particle, and dynamic light scattering is beyond competition when measuring particle size in dispersions ranging from nanometers to micrometers. Unfortunately, this method has a serious problem in processing and interpreting experimental data. Instrument noise and polydispersity of the sample lead to the situation when one initial autocorrelation function corresponds to several different particle size distributions. Sometimes these different solutions of the inverse task can be found by changing parameters in the software. Sometimes the scientist cannot be suspicious of possible other solutions, having one result from the program. In this article I demonstrate the problem on model and experimental data using three known programs: CONTIN, the Malvern Zetasizer and DynaLS. I also present my own free program Autocor, which allows to test our own hypotheses about the modality and shape of the particle size distribution by optimizing the parameters of our own models with a small number of degrees of freedom.
Keywords
dynamic light scattering, autocorrelation function, inverse task, particle size distribution
Subject
Chemistry and Materials Science, Polymers and Plastics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
