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Raster Image Analysis of Diffusion via Single Particle Methods

Marco Longfils (Institutionen för matematiska vetenskaper, Tillämpad matematik och statistik)
Gothenburg : Chalmers University of Technology, 2017.

Soft biomaterials are widely used in many application areas, spanning from packaging materials to pharmaceuticals. To enhance their functionalities, understanding the interplay between microstructure and mass transport properties in these materials is fundamental. Consequently, there is a growing need to introduce new and improve existing methods for estimating mass transport heterogeneity in materials with high spatial resolution. In this work, statistical methods are developed for mapping mass transport locally based on raster images collected using a confocal laser scanning microscope.The methods introduced resemble single particle tracking methods, where molecules are identified using image analysis techniques and followed in successive frames of a video to measure their diffusive mobility. Both a maximum likelihood and a centroid-based method have been applied to locate particles and hence to estimate the diffusion coefficient. The method has been generalized to analyse mixtures of particles having different diffusion coefficients. The single particle approach allows to reveal and study the entire distribution of diffusion coefficients, enabling to examine heterogeneous systems. Further, for the case of particle mixtures, a simple criterion for model selection, i.e. the number of components, is proposed.

Nyckelord: diffusion, single particle tracking, raster scan, confocal laser scanning microscopy, image correlation spectroscopy

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Denna post skapades 2017-04-21. Senast ändrad 2017-06-28.
CPL Pubid: 248928


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Institutioner (Chalmers)

Institutionen för matematiska vetenskaper, Tillämpad matematik och statistikInstitutionen för matematiska vetenskaper, Tillämpad matematik och statistik (GU)


Sannolikhetsteori och statistik

Chalmers infrastruktur


Datum: 2017-05-16
Lokal: Euler, Matematiska vetenskaper, Chalmers tvärgata 3.
Opponent: Prof. Chris Glasbey, Biomathematics and Statistics, Edinburgh, United Kingdom.