Two-dimensional relaxation-diffusion analysis to study water compartmentalization in cells by a single-sided NMR device

In questo lavoro di tesi è presentato un metodo per lo studio della compartimentalizzazione dell’acqua in cellule biologiche, mediante lo studio dell’autodiffusione delle molecole d’acqua tramite uno strumento NMR single-sided. Le misure sono state eseguite nel laboratorio NMR all’interno del DIFA di Bologna. Sono stati misurati i coefficienti di autodiffusione di tre campioni in condizione bulk, ottenendo risultati consistenti con la letteratura. È stato poi analizzato un sistema cellulare modello, Saccharomyces cerevisiae, allo stato solido, ottimizzando le procedure per l’ottenimento di mappe di correlazione 2D, aventi come assi il coefficiente di autodiffusione D e il tempo di rilassamento trasversale T2. In questo sistema l’acqua è confinata e l’autodiffusione è ristretta dalle pareti cellulari, si parla quindi di coefficiente di autodiffusione apparente, Dapp. Mediante le mappe sono state individuate due famiglie di nuclei 1H. Il campione è stato poi analizzato in diluizione in acqua distillata, confermando la separazione del segnale in due distinte famiglie. L’utilizzo di un composto chelato, il CuEDTA, ha permesso di affermare che la famiglia con il Dapp maggiore corrisponde all’acqua esterna alle cellule. L’analisi dei dati ottenuti sulle due famiglie al variare del tempo lasciato alle molecole d’acqua per la diffusione hanno portato alla stima del raggio dei due compartimenti: r=2.3±0.2µm per l’acqua extracellulare, r=0.9±0.1µm per quella intracellulare, che è probabilmente acqua scambiata tra gli organelli e il citoplasma. L’incertezza associata a tali stime tiene conto soltanto dell’errore nel calcolo dei parametri liberi del fit dei dati, è pertanto una sottostima, dovuta alle approssimazioni connesse all’utilizzo di equazioni valide per un sistema poroso costituito da pori sferici connessi non permeabili. Gli ordini di grandezza dei raggi calcolati sono invece consistenti con quelli osservabili dalle immagini ottenute con il microscopio ottico.

Characterization of in-gap electronic states in two-dimensional single crystal PEA2PbBr4 perovskite for X-ray detection

Hybrid Organic-Inorganic Halide Perovskites (HOIPs) include a large class of materials described with the general formula ABX3, where A is an organic cation, B an inorganic cation and X an halide anion. HOIPs show excellent optoelectronic characteristics such as tunable band gap, high adsorption coefficient and great mobility life-time. A subclass of these materials, the so-called two- dimensional (2D) layered HOIPs, have emerged as potential alternatives to traditional 3D analogs to enhance the stability and increase performance of perovskite devices, with particular regard in the area of ionizing radiation detectors, where these materials have reached truly remarkable milestones. One of the key challenges for future development of efficient and stable 2D perovskite X-ray detector is a complete understanding of the nature of defects that lead to the formation of deep states. Deep states act as non-radiative recombination centers for charge carriers and are one of the factors that most hinder the development of efficient 2D HOIPs-based X-ray detectors. In this work, deep states in PEA2PbBr4 were studied through Photo-Induced Current Transient Spectroscopy (PICTS), a highly sensitive spectroscopic technique capable of detecting the presence of deep states in highly resistive ohmic materials, and characterizing their activation energy, capture cross section and, under stringent conditions, the concentration of these states. The evolution of deep states in PEA 2 PbBr 4 was evaluated after exposure of the material to high doses of ionizing radiation and during aging (one year). The data obtained allowed us to evaluate the contribution of ion migration in PEA2PbBr4. This work represents an important starting point for a better understanding of transport and recombination phenomena in 2D perovskites. To date, the PICTS technique applied to 2D perovskites has not yet been reported in the scientific literature.

Impact of convective motions on pollutant dispersion in urban canyons: an analysis through RANS simulations

Since the majority of the population of the world lives in cities and that this number is expected to increase in the next years, one of the biggest challenges of the research is the determination of the risk deriving from high temperatures experienced in urban areas, together with improving responses to climate-related disasters, for example by introducing in the urban context vegetation or built infrastructures that can improve the air quality. In this work, we will investigate how different setups of the boundary and initial conditions set on an urban canyon generate different patterns of the dispersion of a pollutant. To do so we will exploit the low computational cost of Reynolds-Averaged Navier-Stokes (RANS) simulations to reproduce the dynamics of an infinite array of two-dimensional square urban canyons. A pollutant is released at the street level to mimic the presence of traffic. RANS simulations are run using the k-ɛ closure model and vertical profiles of significant variables of the urban canyon, namely the velocity, the turbulent kinetic energy, and the concentration, are represented. This is done using the open-source software OpenFOAM and modifying the standard solver simpleFoam to include the concentration equation and the temperature by introducing a buoyancy term in the governing equations. The results of the simulation are validated with experimental results and products of Large-Eddy Simulations (LES) from previous works showing that the simulation is able to reproduce all the quantities under examination with satisfactory accuracy. Moreover, this comparison shows that despite LES are known to be more accurate albeit more expensive, RANS simulations represent a reliable tool if a smaller computational cost is needed. Overall, this work exploits the low computational cost of RANS simulations to produce multiple scenarios useful to evaluate how the dispersion of a pollutant changes by a modification of key variables, such as the temperature.