Monte Carlo Simulations of Novel Scintillator Detectors and Dosimetry Calculations

Monte Carlo (MC) simulation techniques are becoming very common in the Medical Physicists community. MC can be used for modeling Single Photon Emission Computed Tomography (SPECT) and for dosimetry calculations. 188Re, is a promising candidate for radiotherapeutic production and understanding the mechanisms of the radioresponse of tumor cells "in vitro" is of crucial importance as a first step before "in vivo" studies. The dosimetry of 188Re, used to target different lines of cancer cells, has been evaluated by the MC code GEANT4. The simulations estimate the average energy deposition/per event in the biological samples. The development of prototypes for medical imaging, based on LaBr3:Ce scintillation crystals coupled with a position sensitive photomultiplier, have been studied using GEANT4 simulations. Having tested, in the simulation, surface treatments different from the one applied to the crystal used in our experimental measurements, we found out that the Energy Resolution (ER) and the Spatial Resolution (SR) could be improved, in principle, by machining in a different way the lateral surfaces of the crystal. We have then studied a system able to acquire both echographic and scintigraphic images to let the medical operator obtain the complete anatomic and functional information for tumor diagnosis. The scintigraphic part of the detector is simulated by GEANT4 and first attempts to reconstruct tomographic images have been made using as method of reconstruction a back-projection standard algorithm. The proposed camera is based on slant collimators and LaBr3:Ce crystals. Within the Field of View (FOV) of the camera, it possible to distinguish point sources located in air at a distance of about 2 cm from each other. In particular conditions of uptake, tumor depth and dimension, the preliminary results show that the Signal to Noise Ratio (SNR) values obtained are higher than the standard detection limit.

Local Earthquake Tomography by trans-dimensional Monte Carlo Sampling

In this study a new, fully non-linear, approach to Local Earthquake Tomography is presented. Local Earthquakes Tomography (LET) is a non-linear inversion problem that allows the joint determination of earthquakes parameters and velocity structure from arrival times of waves generated by local sources. Since the early developments of seismic tomography several inversion methods have been developed to solve this problem in a linearized way. In the framework of Monte Carlo sampling, we developed a new code based on the Reversible Jump Markov Chain Monte Carlo sampling method (Rj-McMc). It is a trans-dimensional approach in which the number of unknowns, and thus the model parameterization, is treated as one of the unknowns. I show that our new code allows overcoming major limitations of linearized tomography, opening a new perspective in seismic imaging. Synthetic tests demonstrate that our algorithm is able to produce a robust and reliable tomography without the need to make subjective a-priori assumptions about starting models and parameterization. Moreover it provides a more accurate estimate of uncertainties about the model parameters. Therefore, it is very suitable for investigating the velocity structure in regions that lack of accurate a-priori information. Synthetic tests also reveal that the lack of any regularization constraints allows extracting more information from the observed data and that the velocity structure can be detected also in regions where the density of rays is low and standard linearized codes fails. I also present high-resolution Vp and Vp/Vs models in two widespread investigated regions: the Parkfield segment of the San Andreas Fault (California, USA) and the area around the Alto Tiberina fault (Umbria-Marche, Italy). In both the cases, the models obtained with our code show a substantial improvement in the data fit, if compared with the models obtained from the same data set with the linearized inversion codes.

The XENON1T experiment: Monte Carlo background estimation and sensitivity curves study

Despite the scientific achievement of the last decades in the astrophysical and cosmological fields, the majority of the Universe energy content is still unknown. A potential solution to the “missing mass problem” is the existence of dark matter in the form of WIMPs. Due to the very small cross section for WIMP-nuleon interactions, the number of expected events is very limited (about 1 ev/tonne/year), thus requiring detectors with large target mass and low background level. The aim of the XENON1T experiment, the first tonne-scale LXe based detector, is to be sensitive to WIMP-nucleon cross section as low as 10^-47 cm^2. To investigate the possibility of such a detector to reach its goal, Monte Carlo simulations are mandatory to estimate the background. To this aim, the GEANT4 toolkit has been used to implement the detector geometry and to simulate the decays from the various background sources: electromagnetic and nuclear. From the analysis of the simulations, the level of background has been found totally acceptable for the experiment purposes: about 1 background event in a 2 tonne-years exposure. Indeed, using the Maximum Gap method, the XENON1T sensitivity has been evaluated and the minimum for the WIMP-nucleon cross sections has been found at 1.87 x 10^-47 cm^2, at 90% CL, for a WIMP mass of 45 GeV/c^2. The results have been independently cross checked by using the Likelihood Ratio method that confirmed such results with an agreement within less than a factor two. Such a result is completely acceptable considering the intrinsic differences between the two statistical methods. Thus, in the PhD thesis it has been proven that the XENON1T detector will be able to reach the designed sensitivity, thus lowering the limits on the WIMP-nucleon cross section by about 2 orders of magnitude with respect to the current experiments.

An experimental and theoretical approach to correct for the scattered radiation in an X-ray computer tomography system for industrial applications

The main problem connected to cone beam computed tomography (CT) systems for industrial applications employing 450 kV X-ray tubes is the high amount of scattered radiation which is added to the primary radiation (signal). This stray radiation leads to a significant degradation of the image quality. A better understanding of the scattering and methods to reduce its effects are therefore necessary to improve the image quality. Several studies have been carried out in the medical field at lower energies, whereas studies in industrial CT, especially for energies up to 450 kV, are lacking. Moreover, the studies reported in literature do not consider the scattered radiation generated by the CT system structure and the walls of the X-ray room (environmental scatter). In order to investigate the scattering on CT projections a GEANT4-based Monte Carlo (MC) model was developed. The model, which has been validated against experimental data, has enabled the calculation of the scattering including the environmental scatter, the optimization of an anti-scatter grid suitable for the CT system, and the optimization of the hardware components of the CT system. The investigation of multiple scattering in the CT projections showed that its contribution is 2.3 times the one of primary radiation for certain objects. The results of the environmental scatter showed that it is the major component of the scattering for aluminum box objects of front size 70 x 70 mm2 and that it strongly depends on the thickness of the object and therefore on the projection. For that reason, its correction is one of the key factors for achieving high quality images. The anti-scatter grid optimized by means of the developed MC model was found to reduce the scatter-toprimary ratio in the reconstructed images by 20 %. The object and environmental scatter calculated by means of the simulation were used to improve the scatter correction algorithm which could be patented by Empa. The results showed that the cupping effect in the corrected image is strongly reduced. The developed CT simulation is a powerful tool to optimize the design of the CT system and to evaluate the contribution of the scattered radiation to the image. Besides, it has offered a basis for a new scatter correction approach by which it has been possible to achieve images with the same spatial resolution as state-of-the-art well collimated fan-beam CT with a gain in the reconstruction time of a factor 10. This result has a high economic impact in non-destructive testing and evaluation, and reverse engineering.

Probabilistic approaches in civil engineering: generation of random fields and structural identification with genetic algorithms

The inherent stochastic character of most of the physical quantities involved in engineering models has led to an always increasing interest for probabilistic analysis. Many approaches to stochastic analysis have been proposed. However, it is widely acknowledged that the only universal method available to solve accurately any kind of stochastic mechanics problem is Monte Carlo Simulation. One of the key parts in the implementation of this technique is the accurate and efficient generation of samples of the random processes and fields involved in the problem at hand. In the present thesis an original method for the simulation of homogeneous, multi-dimensional, multi-variate, non-Gaussian random fields is proposed. The algorithm has proved to be very accurate in matching both the target spectrum and the marginal probability. The computational efficiency and robustness are very good too, even when dealing with strongly non-Gaussian distributions. What is more, the resulting samples posses all the relevant, welldefined and desired properties of “translation fields”, including crossing rates and distributions of extremes. The topic of the second part of the thesis lies in the field of non-destructive parametric structural identification. Its objective is to evaluate the mechanical characteristics of constituent bars in existing truss structures, using static loads and strain measurements. In the cases of missing data and of damages that interest only a small portion of the bar, Genetic Algorithm have proved to be an effective tool to solve the problem.

Study of silicon-on-insulator multiple-gate MOS structures including band-gap engineering and self heating effects

The progresses of electron devices integration have proceeded for more than 40 years following the well–known Moore’s law, which states that the transistors density on chip doubles every 24 months. This trend has been possible due to the downsizing of the MOSFET dimensions (scaling); however, new issues and new challenges are arising, and the conventional ”bulk” architecture is becoming inadequate in order to face them. In order to overcome the limitations related to conventional structures, the researchers community is preparing different solutions, that need to be assessed. Possible solutions currently under scrutiny are represented by: • devices incorporating materials with properties different from those of silicon, for the channel and the source/drain regions; • new architectures as Silicon–On–Insulator (SOI) transistors: the body thickness of Ultra-Thin-Body SOI devices is a new design parameter, and it permits to keep under control Short–Channel–Effects without adopting high doping level in the channel. Among the solutions proposed in order to overcome the difficulties related to scaling, we can highlight heterojunctions at the channel edge, obtained by adopting for the source/drain regions materials with band–gap different from that of the channel material. This solution allows to increase the injection velocity of the particles travelling from the source into the channel, and therefore increase the performance of the transistor in terms of provided drain current. The first part of this thesis work addresses the use of heterojunctions in SOI transistors: chapter 3 outlines the basics of the heterojunctions theory and the adoption of such approach in older technologies as the heterojunction–bipolar–transistors; moreover the modifications introduced in the Monte Carlo code in order to simulate conduction band discontinuities are described, and the simulations performed on unidimensional simplified structures in order to validate them as well. Chapter 4 presents the results obtained from the Monte Carlo simulations performed on double–gate SOI transistors featuring conduction band offsets between the source and drain regions and the channel. In particular, attention has been focused on the drain current and to internal quantities as inversion charge, potential energy and carrier velocities. Both graded and abrupt discontinuities have been considered. The scaling of devices dimensions and the adoption of innovative architectures have consequences on the power dissipation as well. In SOI technologies the channel is thermally insulated from the underlying substrate by a SiO2 buried–oxide layer; this SiO2 layer features a thermal conductivity that is two orders of magnitude lower than the silicon one, and it impedes the dissipation of the heat generated in the active region. Moreover, the thermal conductivity of thin semiconductor films is much lower than that of silicon bulk, due to phonon confinement and boundary scattering. All these aspects cause severe self–heating effects, that detrimentally impact the carrier mobility and therefore the saturation drive current for high–performance transistors; as a consequence, thermal device design is becoming a fundamental part of integrated circuit engineering. The second part of this thesis discusses the problem of self–heating in SOI transistors. Chapter 5 describes the causes of heat generation and dissipation in SOI devices, and it provides a brief overview on the methods that have been proposed in order to model these phenomena. In order to understand how this problem impacts the performance of different SOI architectures, three–dimensional electro–thermal simulations have been applied to the analysis of SHE in planar single and double–gate SOI transistors as well as FinFET, featuring the same isothermal electrical characteristics. In chapter 6 the same simulation approach is extensively employed to study the impact of SHE on the performance of a FinFET representative of the high–performance transistor of the 45 nm technology node. Its effects on the ON–current, the maximum temperatures reached inside the device and the thermal resistance associated to the device itself, as well as the dependence of SHE on the main geometrical parameters have been analyzed. Furthermore, the consequences on self–heating of technological solutions such as raised S/D extensions regions or reduction of fin height are explored as well. Finally, conclusions are drawn in chapter 7.

Sistemi liquido cristallini complessi: simulazioni al calcolatore e studi ESR

The aim of this PhD thesis was to study at a microscopic level different liquid crystal (LC) systems, in order to determine their physical properties, resorting to two distinct methodologies, one involving computer simulations, and the other spectroscopic techniques, in particular electron spin resonance (ESR) spectroscopy. By means of the computer simulation approach we tried to demonstrate this tool effectiveness for calculating anisotropic static properties of a LC material, as well as for predicting its behaviour and features. This required the development and adoption of suitable molecular models based on a convenient intermolecular potentials reflecting the essential molecular features of the investigated system. In particular, concerning the simulation approach, we have set up models for discotic liquid crystal dimers and we have studied, by means of Monte Carlo simulations, their phase behaviour and self­-assembling properties, with respect to the simple monomer case. Each discotic dimer is described by two oblate Gay­Berne ellipsoids connected by a flexible spacer, modelled by a harmonic "spring" of three different lengths. In particular we investigated the effects of dimerization on the transition temperatures, as well as on the characteristics of molecular aggregation displayed and the relative orientational order. Moving to the experimental results, among the many experimental techniques that are typically employed to evaluate LC system distinctive features, ESR has proved to be a powerful tool in microscopic scale investigation of the properties, structure, order and dynamics of these materials. We have taken advantage of the high sensitivity of the ESR spin probe technique to investigate increasingly complex LC systems ranging from devices constituted by a polymer matrix in which LC molecules are confined in shape of nano- droplets, as well as biaxial liquid crystalline elastomers, and dimers whose monomeric units or lateral groups are constituted by rod-like mesogens (11BCB). Reflection-mode holographic-polymer dispersed liquid crystals (H-PDLCs) are devices in which LCs are confined into nanosized (50­-300 nm) droplets, arranged in layers which alternate with polymer layers, forming a diffraction grating. We have determined the configuration of the LC local director and we have derived a model of the nanodroplet organization inside the layers. Resorting also to additional information on the nanodroplet size and shape distribution provided by SEM images of the H-PDLC cross-section, the observed director configuration has been modeled as a bidimensional distribution of elongated nanodroplets whose long axis is, on the average, parallel to the layers and whose internal director configuration is a uniaxial quasi- monodomain aligned along the nanodroplet long axis. The results suggest that the molecular organization is dictated mainly by the confinement, explaining, at least in part, the need for switching voltages significantly higher and the observed faster turn-off times in H-PDLCs compared to standard PDLC devices. Liquid crystal elastomers consist in cross-linked polymers, in which mesogens represent the monomers constituting the main chain or the laterally attached side groups. They bring together three important aspects: orientational order in amorphous soft materials, responsive molecular shape and quenched topological constraints. In biaxial nematic liquid crystalline elastomers (BLCEs), two orthogonal directions, rather than the one of normal uniaxial nematic, can be controlled, greatly enhancing their potential value for applications as novel actuators. Two versions of a side-chain BLCEs were characterized: side­-on and end­-on. Many tests have been carried out on both types of LCE, the main features detected being the lack of a significant dynamical behaviour, together with a strong permanent alignment along the principal director, and the confirmation of the transition temperatures already determined by DSC measurements. The end­-on sample demonstrates a less hindered rotation of the side group mesogenic units and a greater freedom of alignment to the magnetic field, as already shown by previous NMR studies. Biaxial nematic ESR static spectra were also obtained on the basis of Molecular Dynamics generated biaxial configurations, to be compared to the experimentally determined ones, as a mean to establish a possible relation between biaxiality and the spectral features. This provides a concrete example of the advantages of combining the computer simulation and spectroscopic approaches. Finally, the dimer α,ω-bis(4'-cyanobiphenyl-4-yl)undecane (11BCB), synthesized in the "quest" for the biaxial nematic phase has been analysed. Its importance lies in the dimer significance as building blocks in the development of new materials to be employed in innovative technological applications, such as faster switching displays, resorting to the easier aligning ability of the secondary director in biaxial phases. A preliminary series of tests were performed revealing the population of mesogenic molecules as divided into two groups: one of elongated straightened conformers sharing a common director, and one of bent molecules, which display no order, being equally distributed in the three dimensions. Employing this model, the calculated values show a consistent trend, confirming at the same time the transition temperatures indicated by the DSC measurements, together with rotational diffusion tensor values that follow closely those of the constituting monomer 5CB.

Measurement of top quark pairs production cross-section in the semi-leptonic channel with the ATLAS experiment

This thesis is about three major aspects of the identification of top quarks. First comes the understanding of their production mechanism, their decay channels and how to translate theoretical formulae into programs that can simulate such physical processes using Monte Carlo techniques. In particular, the author has been involved in the introduction of the POWHEG generator in the framework of the ATLAS experiment. POWHEG is now fully used as the benchmark program for the simulation of ttbar pairs production and decay, along with MC@NLO and AcerMC: this will be shown in chapter one. The second chapter illustrates the ATLAS detectors and its sub-units, such as calorimeters and muon chambers. It is very important to evaluate their efficiency in order to fully understand what happens during the passage of radiation through the detector and to use this knowledge in the calculation of final quantities such as the ttbar production cross section. The last part of this thesis concerns the evaluation of this quantity deploying the so-called "golden channel" of ttbar decays, yielding one energetic charged lepton, four particle jets and a relevant quantity of missing transverse energy due to the neutrino. The most important systematic errors arising from the various part of the calculation are studied in detail. Jet energy scale, trigger efficiency, Monte Carlo models, reconstruction algorithms and luminosity measurement are examples of what can contribute to the uncertainty about the cross-section.

Theoretical studies of microfluidics: "walking" drops and "melting" snowflakes.

The present PhD thesis summarizes two examples of research in microfluidics. Both times water was the subject of interest, once in the liquid state (droplets adsorbed on chemically functionalized surfaces), the other time in the solid state (ice snowflakes and their fractal behaviour). The first problem deals with a slipping nano-droplet of water adsorbed on a surface with photo-switchable wettability characteristics. Main focus was on identifying the underlying driving forces and mechanical principles at the molecular level of detail. Molecular Dynamics simulation was employed as investigative tool owing to its record of successfully describing the microscopic behaviour of liquids at interfaces. To reproduce the specialized surface on which a water droplet can effectively “walk”, a new implicit surface potential was developed. Applying this new method the experimentally observed droplet slippage could be reproduced successfully. Next the movement of the droplet was analyzed at various conditions emphasizing on the behaviour of the water molecules in contact with the surface. The main objective was to identify driving forces and molecular mechanisms underlying the slippage process. The second part of this thesis is concerned with theoretical studies of snowflake melting. In the present work snowflakes are represented by filled von Koch-like fractals of mesoscopic beads. A new algorithm has been developed from scratch to simulate the thermal collapse of fractal structures based on Monte Carlo and Random Walk Simulations (MCRWS). The developed method was applied and compared to Molecular Dynamics simulations regarding the melting of ice snowflake crystals and new parameters were derived from this comparison. Bigger snow-fractals were then studied looking at the time evolution at different temperatures again making use of the developed MCRWS method. This was accompanied by an in-depth analysis of fractal properties (border length and gyration radius) in order to shed light on the dynamics of the melting process.

Measurement of the muon-induced neutron flux at LNGS with the LVD experiment

In this thesis we describe in detail the Monte Carlo simulation (LVDG4) built to interpret the experimental data collected by LVD and to measure the muon-induced neutron yield in iron and liquid scintillator. A full Monte Carlo simulation, based on the Geant4 (v 9.3) toolkit, has been developed and validation tests have been performed. We used the LVDG4 to determine the active vetoing and the shielding power of LVD. The idea was to evaluate the feasibility to host a dark matter detector in the most internal part, called Core Facility (LVD-CF). The first conclusion is that LVD is a good moderator, but the iron supporting structure produce a great number of neutrons near the core. The second conclusions is that if LVD is used as an active veto for muons, the neutron flux in the LVD-CF is reduced by a factor 50, of the same order of magnitude of the neutron flux in the deepest laboratory of the world, Sudbury. Finally, the muon-induced neutron yield has been measured. In liquid scintillator we found $(3.2 \pm 0.2) \times 10^{-4}$ n/g/cm$^2$, in agreement with previous measurements performed at different depths and with the general trend predicted by theoretical calculations and Monte Carlo simulations. Moreover we present the first measurement, in our knowledge, of the neutron yield in iron: $(1.9 \pm 0.1) \times 10^{-3}$ n/g/cm$^2$. That measurement provides an important check for the MC of neutron production in heavy materials that are often used as shield in low background experiments.

Employing Distances in Design-based Spatial Estimation

In the last couple of decades we assisted to a reappraisal of spatial design-based techniques. Usually the spatial information regarding the spatial location of the individuals of a population has been used to develop efficient sampling designs. This thesis aims at offering a new technique for both inference on individual values and global population values able to employ the spatial information available before sampling at estimation level by rewriting a deterministic interpolator under a design-based framework. The achieved point estimator of the individual values is treated both in the case of finite spatial populations and continuous spatial domains, while the theory on the estimator of the population global value covers the finite population case only. A fairly broad simulation study compares the results of the point estimator with the simple random sampling without replacement estimator in predictive form and the kriging, which is the benchmark technique for inference on spatial data. The Monte Carlo experiment is carried out on populations generated according to different superpopulation methods in order to manage different aspects of the spatial structure. The simulation outcomes point out that the proposed point estimator has almost the same behaviour as the kriging predictor regardless of the parameters adopted for generating the populations, especially for low sampling fractions. Moreover, the use of the spatial information improves substantially design-based spatial inference on individual values.

The effect of osmolytes on protein fold stability at the single-molecule level

By pulling and releasing the tension on protein homomers with the Atomic Force Miscroscope (AFM) at different pulling speeds, dwell times and dwell distances, the observed force-response of the protein can be fitted with suitable theoretical models. In this respect we developed mathematical procedures and open-source computer codes for driving such experiments and fitting Bell’s model to experimental protein unfolding forces and protein folding frequencies. We applied the above techniques to the study of proteins GB1 (the B1 IgG-binding domain of protein G from Streptococcus) and I27 (a module of human cardiac titin) in aqueous solutions of protecting osmolytes such as dimethyl sulfoxide (DMSO), glycerol and trimethylamine N-oxide (TMAO). In order to get a molecular understanding of the experimental results we developed an Ising-like model for proteins that incorporates the osmophobic nature of their backbone. The model benefits from analytical thermodynamics and kinetics amenable to Monte-Carlo simulation. The prevailing view used to be that small protecting osmolytes bridge the separating beta-strands of proteins with mechanical resistance, presumably shifting the transition state to significantly higher distances that correlate with the molecular size of the osmolyte molecules. Our experiments showed instead that protecting osmolytes slow down protein unfolding and speed-up protein folding at physiological pH without shifting the protein transition state on the mechanical reaction coordinate. Together with the theoretical results of the Ising-model, our results lend support to the osmophobic theory according to which osmolyte stabilisation is a result of the preferential exclusion of the osmolyte molecules from the protein backbone. The results obtained during this thesis work have markedly improved our understanding of the strategy selected by Nature to strengthen protein stability in hostile environments, shifting the focus from hypothetical protein-osmolyte interactions to the more general mechanism based on the osmophobicity of the protein backbone.

Modeling the spatial dynamics of economic models

The advances that have been characterizing spatial econometrics in recent years are mostly theoretical and have not found an extensive empirical application yet. In this work we aim at supplying a review of the main tools of spatial econometrics and to show an empirical application for one of the most recently introduced estimators. Despite the numerous alternatives that the econometric theory provides for the treatment of spatial (and spatiotemporal) data, empirical analyses are still limited by the lack of availability of the correspondent routines in statistical and econometric software. Spatiotemporal modeling represents one of the most recent developments in spatial econometric theory and the finite sample properties of the estimators that have been proposed are currently being tested in the literature. We provide a comparison between some estimators (a quasi-maximum likelihood, QML, estimator and some GMM-type estimators) for a fixed effects dynamic panel data model under certain conditions, by means of a Monte Carlo simulation analysis. We focus on different settings, which are characterized either by fully stable or quasi-unit root series. We also investigate the extent of the bias that is caused by a non-spatial estimation of a model when the data are characterized by different degrees of spatial dependence. Finally, we provide an empirical application of a QML estimator for a time-space dynamic model which includes a temporal, a spatial and a spatiotemporal lag of the dependent variable. This is done by choosing a relevant and prolific field of analysis, in which spatial econometrics has only found limited space so far, in order to explore the value-added of considering the spatial dimension of the data. In particular, we study the determinants of cropland value in Midwestern U.S.A. in the years 1971-2009, by taking the present value model (PVM) as the theoretical framework of analysis.