PhD Thesis Defence Presentations - Χρήστος Στιάπης

In several critical engineering applications, such as gas particulate filtration, coal bio-conversion process, CO₂ geological storage, and biomedical processes, heterogeneous porous materials are ubiquitous. These applications rely on specific physical mechanisms, such as transport (e.g., mass, momentum, or energy) and chemical reactions for their functioning. The physical mechanisms in the interior of the porous media are strongly dependent upon the porous medium structure and morphology. Therefore, detailed elucidation of the internal structure of such porous media is needed to understand and improve the physical processes in which they are used. A detailed microstructure description can be used to find the physical properties and estimate and enhance their performance. This thesis uses statistical properties extracted from scanning electron microscopy (SEM) images to explore and digitally re-create porous media structures. First, a stochastic approach for reconstructing porous media is chosen because it captures their stochastic nature in reasonable cost and time ranges. Then, a digital reconstruction model and a computer program are created to recreate porous media structures with various statistical properties. The main objective of this thesis is the digital characterization of PES/ PVP membranes used in hemodialysis processes and the development of a model that can predict their blood purification performance. Those membranes comprise multiple layers, and usually, a foam-like structure is formed in the center path of those membranes affecting the separation performance and providing superior mechanical properties to the whole membrane structure.

In this framework, a novel method for digitally reconstructing foams was developed utilizing the Laguerre Tessellation approach, which shows a remarkable ability to describe foamy materials comprised of macrovoids with polyhedral shapes [1]. Furthermore, to describe foamy materials with macrovoids of spherical shapes and increased connectivity, an alternative method was developed based on the generation of packings of hollow spheres [2]. Finally, a model to describe the removal of protein-bound toxins during the hemodialysis process using mixed matrix membranes was developed and validated against experimental data [3]. This model was further extended and utilized to predict the performance of a multilayer mixed matrix membrane during creatinine removal [4]. In addition, the incorporation of the reconstruction processes developed into the model further reduced the required experimental data.

The utilization of those reconstruction methods into the newly developed model provided insight into the membrane characteristics and process conditions. Thus, it could assist in optimizing the mass transfer through the hemodialysis membrane. Furthermore, this procedure can be extended into different separation technologies paving the way towards designing tailored porous media structures with desired transport properties avoiding exhaustive physical experimentation

1. Stiapis, C.S.; Skouras, E.D.; Burganos, V.N. Advanced Laguerre Tessellation for the Reconstruction of Ceramic Foams and Prediction of Transport Properties. Materials 2019, 12, 1137.

2. Stiapis, C.S.; Skouras, E.D.; Burganos, V.N. Three-Dimensional Digital Reconstruction of Ti2AlC Ceramic Foams Produced by the Gelcast Method. Materials 2019, 12, 4085.

3. Stiapis, C.; Skouras, E.; Pavlenko, D.; Stamatialis, D.; Burganos, V. Evaluation of the Toxin-to-Protein Binding Rates during Hemodialysis Using Sorbent-Loaded Mixed-Matrix Membranes. Applied Sciences 2018, 8, 536.

4. Stiapis, C.S.; Skouras, E.D.; Burganos, V.N. Prediction of Toxin Removal Efficiency of Novel Hemodialysis Multilayered Mixed-Matrix Membranes. Separation and Purification Technology 2020, 250, 117272.