From experiments with images to 3D models
Doctoral thesis, 2017

For developing the next generation sustainable materials, it is often crucial to understand and control their properties and function. This work presents cross-disciplinary research starting with experimentally fabricated porous soft biomaterials and images of their micro-structure obtained by electron or laser microscopy. It is investigated how much information on the three-dimensional material structure can be extracted from two-dimensional images and how conclusions compare to three-dimensional image analysis. Based on the image data, spatial statistical models are constructed and fitted to two different materials: a colloidal nanoparticle gel and a porous polymer blended film. Colloidal systems are everywhere in our everyday life and of high interest for the development of new advanced materials. Polymer films are popular for pharmaceutical coatings which control the release of a drug to obtain important therapeutic benefits. Besides presenting image analysis routines, three-dimensional finite Gibbs point processes with inhomogeneous and anisotropic pair-potential functions are introduced. Observed point patterns are formed by silica particle positions or pore branching points located at intersections of at least three pore channels. Due to physical chemical forces between particles and polymers, it is assumed that the points interact with each other. The pairwise interaction is described in the pair-potential function of a Gibbs process. In this way, there is a link between static Gibbs point process models and dynamic physical chemical processes like colloidal particle aggregation and polymer phase separation. Furthermore, a new spatial statistical summary function is suggested for the cluster size analysis on different length scales in aggregated structures. This function is a useful tool for comparing two regimes for particle aggregation resulting in different size and shape distributions of particle clusters. More precisely, it is used to study the diffusion limited and the reaction limited cluster aggregation. The methods introduced in this work can be applied to point processes in general and are important contributions to the point process literature. The results are useful for setting up a virtual design framework for the study of properties of various materials, which may not yet have even been synthesized, in simulation studies instead of experiments involving valuable resources.

porous polymer blended films

mass transport

Anisotropy

colloidal particle aggregation

image analysis

Gibbs point processes

Pascal, Matematiska vetenskaper, Chalmers tvärgata 3, Göteborg
Opponent: Associate Professor Ute Hahn, Department of Mathematics, Aarhus University, Denmark

Author

Henrike Häbel

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Characterization of pore structure of polymer blended films used for controlled drug release

Journal of Controlled Release,; Vol. 222(2016)p. 151-158

Journal article

From static micrographs to particle aggregation dynamics in three dimensions

Journal of Microscopy,; Vol. 262(2016)p. 102-111

Journal article

Häbel, H., Särkkä, A., Rudemo, M., Hamngren Blomqvist, C., Olsson, E., and Nordin, M. (2017). Colloidal particle aggregation in three dimensions. In manuscript.

Häbel, H., Rajala, T., Boissier, C., Marucci, M., Schladitz, K., Redenbach, C., and Särkkä, A. (2017). A three-dimensional anisotropic point process characterization for pharmaceutical coatings. Submitted.

För att utveckla nästa generations hållbara material är det ofta viktigt att förstå och kontrollera deras egenskaper och funktion. Syftet med denna avhandling är statistisk karakterisering och modellering av biomaterial, där två olika material används som exempel: en gel av sfäriska partiklar och en porös film. Sådana geler finns överallt i vår vardag, t.ex. mjukost, och är av stort intresse för utvecklingen av nya avancerade material. Porösa filmer är populära för farmaceutiska drageringar omkring ett läkemedel och styr frisättningen av läkemedlet till kroppen.

Detta arbete presenterar tvärvetenskaplig forskning som baseras på experimentellt tillverkade material och bilder av deras mikrostruktur. Det undersöks hur mycket information om den tredimensionella materialstrukturen fångas i tvådimensionella bilder och hur slutsatser överensstämmer med tredimensionell bildanalys. Baserat på punktmönster hittat i bilderna konstrueras och anpassas rumsliga statistiska modeller. Punktmönstren bildas här av positionerna, antingen av partiklarna eller av porförgreningspunkter med minst tre porkanaler. Punkterna kan attrahera och repellera eller så interagerar de inte alls med varandra. Karakteriseringsfunktioner och modeller försöker sedan beskriva interaktionen mellan punkterna.

Metoderna som presenteras i detta arbete kan tillämpas på olika punktmönster och är ett viktigt bidrag till punktprocesslitteraturen. Resultaten är användbara för att studera egenskaper hos olika material som ännu inte ens finns, i simuleringsstudier istället för kostsamma experiment.

Driving Forces

Sustainable development

Subject Categories

Physical Chemistry

Probability Theory and Statistics

Areas of Advance

Materials Science

ISBN

978-91-7597-569-6

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4250

Publisher

Chalmers

Pascal, Matematiska vetenskaper, Chalmers tvärgata 3, Göteborg

Opponent: Associate Professor Ute Hahn, Department of Mathematics, Aarhus University, Denmark

More information

Created

4/13/2017