The pore geometry of pharmaceutical coatings: statistical modelling, characterization methods and transport prediction

This thesis contains new methods for bridging the gap between the pore geometry of porous materials and experimentally measured functional properties. The focus has been on diffusive transport in pharmaceutical coatings used in controlled drug delivery systems, but the methods are general and can be applied to other porous materials and functional properties. Relatively large datasets are needed to train realistic models connecting the pore geometry and diffusive transport properties of porous materials. 3-D statistical pore models based on microscopy images of the coating material were in this thesis used to generate large sets of pore structures, in which diffusive transport was computed numerically. Characterization measures capturing important features of the pore geometry were developed and used as predictors of diffusive transport rates in multiplicative regression models. The characterization measures have been implemented in a freely available software, MIST.In Paper I, a Gaussian random field based pore model was developed and fitted to microscopy images of the coating material. Due to the large size of the data, the model was formulated using a Gaussian Markov random field approximation, which allows for efficient inference. A new method for solving linear equations with Kronecker matrices which reduced the complexity of the model fitting algorithm considerably was developed. The pore model was found to fit the microscopy images well. In Paper II, characterization measures that have been shown to provide good regression models for diffusive transport rates were developed further and implemented. Multiplicative regression models were fitted to pore structures from the model from Paper I, and the new methods were shown to give improved results. In Papers III and V characterization measures that capture a type of bottleneck effect which was observed in another set of microscopy images of the coating material (Papers III and IV), but which is not captured by existing methods, were invented. Pore structures with this type of bottleneck were generated using 3-D statistical pore models, and the new type of bottleneck was found to be an important determinant of diffusive transport rates when the regression models were fitted to simple pore structures (Paper V)

Heading in the right direction : guiding cellular alignment by substrate anisotropy

Energie en entropie sturen cellen in de zelfde richtin

ICR ANNUAL REPORT 2022 (Volume 29)[All Pages]

This Annual Report covers from 1 January to 31 December 202

Structural Design of Ionic Liquids for Process Optimisation

Ionic liquids (ILs) are designer solvents with tuneable cationic and anionic structures. We propose structural factors that are key to realising the designer solvent promise of ILs. We highlight their potential for translation to new generations of low-cost and environmentally sustainable cation and anion motifs for large-scale applications. Starting from a comparison among primary and secondary ammonium ILs, the unusual liquid nanostructure of pyrrolidinium ILs explains its versatile solvent properties. In the context of biomass processing, we present a framework for the design of IL structure to minimize competition and to enhance driving forces for aromatic extraction. Choline amino-acid ILs and their water mixtures show great promise as low-cost biocompatible solvents. ILs as solvents have the rare ability to promote amphiphilic self-assembly of molecules, such as n-alkanols, that are not conventionally considered as amphiphilic surfactants in water. We investigate the structure of complex solutions using a combination of small-angle X-ray scattering (SAXS), small-angle neutron scattering (SANS), invariant analysis, and neutron diffraction combined with Empirical Potential Structural Refinement (EPSR) simulation technique. We rationalise how IL-supported self-assembly can be controlled over solute polarity, packing geometry and formulation. The design of ILs as solvents is not restricted to pure ionic species. We demonstrate new categories of ILs based on molecular complexation around metal cations. Non-ionic surfactants self-assemble in inorganic salts as they do in ILs or water, with predictable phase behaviours rationalised by the surfactant packing parameter. Further, we show mixtures of paramagnetic salts and low-volatile solvents as magnetic ionic liquids. Our structural understanding of ILs and their mixtures creates opportunities for formulating new types of nanomaterials and facilitates the design of future solvents for process optimisation

【研究分野別】シーズ集 [英語版]

[英語版