Raster Image Analysis of Diffusion via Single Particle Methods
Licentiate thesis, 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.

raster scan

single particle tracking

diffusion

image correlation spectroscopy

confocal laser scanning microscopy

Euler, Matematiska vetenskaper, Chalmers tvärgata 3.
Opponent: Prof. Chris Glasbey, Biomathematics and Statistics, Edinburgh, United Kingdom.

Author

Marco Longfils

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Longfils, M., Röding, M., Altskär A.; Schuster, E., Loren, N., Särkkä, A., ands Rudemo, M. Raster image analysis of diffusion for particle mixtures.

Longfils, M., Schuster, E., Loren, N., Särkkä, A., and Rudemo, M.. Single particle raster image analysis of diffusion. Journal of Microscopy, doi:10.1111/jmi.12511.

Subject Categories

Probability Theory and Statistics

Areas of Advance

Materials Science

Publisher

Chalmers University of Technology

Euler, Matematiska vetenskaper, Chalmers tvärgata 3.

Opponent: Prof. Chris Glasbey, Biomathematics and Statistics, Edinburgh, United Kingdom.

More information

Created

4/21/2017