New possibilities of accurate particle characterisation by applying direct boundary models to analytical centrifugation

Please always quote using this URN: urn:nbn:de:bvb:29-opus4-83863
  • Analytical centrifugation (AC) is a powerful technique for the characterisation of nanoparticles in colloidal systems. As a direct and absolute technique it requires no calibration or measurements of standards. Moreover, it offers simple experimental design and handling, high sample throughput as well as moderate investment costs. However, the full potential of AC for nanoparticle size analysis requires the development of powerful data analysis techniques. In this study we show how the application of direct boundary models to AC data opens up new possibilities in particle characterisation. An accurate analysis method, successfully applied to sedimentation data obtained by analyticalAnalytical centrifugation (AC) is a powerful technique for the characterisation of nanoparticles in colloidal systems. As a direct and absolute technique it requires no calibration or measurements of standards. Moreover, it offers simple experimental design and handling, high sample throughput as well as moderate investment costs. However, the full potential of AC for nanoparticle size analysis requires the development of powerful data analysis techniques. In this study we show how the application of direct boundary models to AC data opens up new possibilities in particle characterisation. An accurate analysis method, successfully applied to sedimentation data obtained by analytical ultracentrifugation (AUC) in the past, was used for the first time in analysing AC data. Unlike traditional data evaluation routines for AC using a designated number of radial positions or scans, direct boundary models consider the complete sedimentation boundary, which results in significantly better statistics. We demonstrate that meniscus fitting, as well as the correction of radius and time invariant noise significantly improves the signal-to-noise ratio and prevents the occurrence of false positives due to optical artefacts. Moreover, hydrodynamic non-ideality can be assessed by the residuals obtained from the analysis. The sedimentation coefficient distributions obtained by AC are in excellent agreement with the results from AUC. Brownian dynamics simulations were used to generate numerical sedimentation data to study the influence of diffusion on the obtained distributions. Our approach is further validated using polystyrene and silica nanoparticles. In particular, we demonstrate the strength of AC for analysing multimodal distributions by means of gold nanoparticles.show moreshow less

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Metadaten
Author:Johannes Walter, Thaseem Thajudeen, Sebastian Süβ, Doris Segets, Wolfgang Peukert
Persistent identifiers - URN:urn:nbn:de:bvb:29-opus4-83863
Persistent identifiers - DOI:https://doi.org/10.1039/C5NR00995B
Title of the journal / compilation (English):Nanoscale
Document Type:Article
Language:English
Year of publication:2015
Date of online publication (Embargo Date):2017/04/25
Publishing Institution:Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
Release Date:2017/05/24
SWD-Keyword:-
Volume/year:7
Issue:15
Length/size:6574 - 6587
Original publication:Nanoscale 7.15 (2015): S. 6574-6587. <http://pubs.rsc.org/en/content/articlelanding/2015/nr/c5nr00995b#!divAbstract>
Institutes:Technische Fakultät
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 66 Chemische Verfahrenstechnik / 660 Chemische Verfahrenstechnik
open_access (DINI-Set):open_access
Collections:Universität Erlangen-Nürnberg / Allianzlizenzen: Alle Beiträge sind mit Zustimmung der Rechteinhaber aufgrund einer DFG-geförderten Allianzlizenz frei zugänglich. / Allianzlizenzen 2015
Licence (German):Keine Creative Commons Lizenz - es gilt der Veröffentlichungsvertrag und das deutsche Urheberrecht