A model for diffusive and displacive phase transitions in steels

Heat treatment of steels is a process of fundamental importance in tailoring the properties of a material to the desired application; developing a model able to describe such process would allow to predict the microstructure obtained from the treatment and the consequent mechanical properties of the material. A steel, during a heat treatment, can undergo two different kinds of phase transitions [p.t.]: diffusive (second order p.t.) and displacive (first order p.t.); in this thesis, an attempt to describe both in a thermodynamically consistent framework is made; a phase field, diffuse interface model accounting for the coupling between thermal, chemical and mechanical effects is developed, and a way to overcome the difficulties arising from the treatment of the non-local effects (gradient terms) is proposed. The governing equations are the balance of linear momentum equation, the Cahn-Hilliard equation and the balance of internal energy equation. The model is completed with a suitable description of the free energy, from which constitutive relations are drawn. The equations are then cast in a variational form and different numerical techniques are used to deal with the principal features of the model: time-dependency, non-linearity and presence of high order spatial derivatives. Simulations are performed using DOLFIN, a C++ library for the automated solution of partial differential equations by means of the finite element method; results are shown for different test-cases. The analysis is reduced to a two dimensional setting, which is simpler than a three dimensional one, but still meaningful.

Conductive Polymer Composites

In recent years, nanotechnologies have led to the production of materials with new and sometimes unexpected qualities through the manipulation of nanoscale components. This research aimed primarily to the study of the correlation between hierarchical structures of hybrid organic-inorganic materials such as conductive polymer composites (CPCs). Using a bottom-up methodology, we could synthesize a wide range of inorganic nanometric materials with a high degree of homogeneity and purity, such as thiol capped metal nanoparticles, stoichiometric geomimetic chrysotile nanotubes and metal dioxide nanoparticles. It was also possible to produce inorganic systems formed from the interaction between the synthesized materials. These synthesized materials and others like multiwalled carbon nanotubes and grapheme oxide were used to produce conductive polymer composites. Electrospinning causes polymer fibers to become elongated using an electric field. This technique was used to produce fibers with a nanometric diameter of a polymer blend based on two different intrinsically conducting polymers polymers (ICPs): polyaniline (PANI) and poly(3-hexylthiophene) (P3HT). Using different materials as second phase in the initial electrospun polymer fibers caused significant changes to the material hierarchical structure, leading to the creation of CPCs with modified electrical properties. Further study of the properties of these new materials resulted in a better understanding of the electrical conductivity mechanisms in these electrospun materials.

Biodegradable systems for the development of functional materials

This PhD work was aimed to design, develop, and characterize gelatin-based scaffolds, for the repair of defects in the muscle-skeletal system. Gelatin is a biopolymer widely used for pharmaceutical and medical applications, thanks to its biodegradability and biocompatibility. It is obtained from collagen via thermal denaturation or chemical-physical degradation. Despite its high potential as biomaterial, gelatin exhibits poor mechanical properties and a low resistance in aqueous environment. Crosslinking treatment and enrichment with reinforcement materials are thus required for biomedical applications. In this work, gelatin based scaffolds were prepared following three different strategies: films were prepared through the solvent casting method, electrospinning technique was applied for the preparation of porous mats, and 3D porous scaffolds were prepared through freeze-drying. The results obtained on films put into evidence the influence of pH, crosslinking and reinforcement with montmorillonite (MMT), on the structure, stability and mechanical properties of gelatin and MMT/gelatin composites. The information acquired on the effect of crosslinking in different conditions was utilized to optimize the preparation procedure of electrospun and freeze-dried scaffolds. A successful method was developed to prepare gelatin nanofibrous scaffolds electrospun from acetic acid/water solution and stabilized with a non-toxic crosslinking agent, genipin, able to preserve their original morphology after exposure to water. Moreover, the co-electrospinning technique was used to prepare nanofibrous scaffolds at variable content of gelatin and polylactic acid. Preliminary in vitro tests indicated that the scaffolds are suitable for cartilage tissue engineering, and that their potential applications can be extended to cartilage-bone interface tissue engineering. Finally, 3D porous gelatin scaffolds, enriched with calcium phosphate, were prepared with the freeze-drying method. The results indicated that the crystallinity of the inorganic phase influences porosity, interconnectivity and mechanical properties. Preliminary in vitro tests show good osteoblast response in terms of proliferation and adhesion on all the scaffolds.

Earthquake forecasting and seismic hazard analysis: some insights on the testing phase and the modeling

This thesis is divided in three chapters. In the first chapter we analyse the results of the world forecasting experiment run by the Collaboratory for the Study of Earthquake Predictability (CSEP). We take the opportunity of this experiment to contribute to the definition of a more robust and reliable statistical procedure to evaluate earthquake forecasting models. We first present the models and the target earthquakes to be forecast. Then we explain the consistency and comparison tests that are used in CSEP experiments to evaluate the performance of the models. Introducing a methodology to create ensemble forecasting models, we show that models, when properly combined, are almost always better performing that any single model. In the second chapter we discuss in depth one of the basic features of PSHA: the declustering of the seismicity rates. We first introduce the Cornell-McGuire method for PSHA and we present the different motivations that stand behind the need of declustering seismic catalogs. Using a theorem of the modern probability (Le Cam's theorem) we show that the declustering is not necessary to obtain a Poissonian behaviour of the exceedances that is usually considered fundamental to transform exceedance rates in exceedance probabilities in the PSHA framework. We present a method to correct PSHA for declustering, building a more realistic PSHA. In the last chapter we explore the methods that are commonly used to take into account the epistemic uncertainty in PSHA. The most widely used method is the logic tree that stands at the basis of the most advanced seismic hazard maps. We illustrate the probabilistic structure of the logic tree, and then we show that this structure is not adequate to describe the epistemic uncertainty. We then propose a new probabilistic framework based on the ensemble modelling that properly accounts for epistemic uncertainties in PSHA.