TCAD approaches to multidimensional simulation of advanced semiconductor devices

Technology scaling increasingly emphasizes complexity and non-ideality of the electrical behavior of semiconductor devices and boosts interest on alternatives to the conventional planar MOSFET architecture. TCAD simulation tools are fundamental to the analysis and development of new technology generations. However, the increasing device complexity is reflected in an augmented dimensionality of the problems to be solved. The trade-off between accuracy and computational cost of the simulation is especially influenced by domain discretization: mesh generation is therefore one of the most critical steps and automatic approaches are sought. Moreover, the problem size is further increased by process variations, calling for a statistical representation of the single device through an ensemble of microscopically different instances. The aim of this thesis is to present multi-disciplinary approaches to handle this increasing problem dimensionality in a numerical simulation perspective. The topic of mesh generation is tackled by presenting a new Wavelet-based Adaptive Method (WAM) for the automatic refinement of 2D and 3D domain discretizations. Multiresolution techniques and efficient signal processing algorithms are exploited to increase grid resolution in the domain regions where relevant physical phenomena take place. Moreover, the grid is dynamically adapted to follow solution changes produced by bias variations and quality criteria are imposed on the produced meshes. The further dimensionality increase due to variability in extremely scaled devices is considered with reference to two increasingly critical phenomena, namely line-edge roughness (LER) and random dopant fluctuations (RD). The impact of such phenomena on FinFET devices, which represent a promising alternative to planar CMOS technology, is estimated through 2D and 3D TCAD simulations and statistical tools, taking into account matching performance of single devices as well as basic circuit blocks such as SRAMs. Several process options are compared, including resist- and spacer-defined fin patterning as well as different doping profile definitions. Combining statistical simulations with experimental data, potentialities and shortcomings of the FinFET architecture are analyzed and useful design guidelines are provided, which boost feasibility of this technology for mainstream applications in sub-45 nm generation integrated circuits.

A candidate gene approach to identify DNA markers associated with meat quality and production traits: investigation of several cathepsin genes in Italian heavy pigs.

The cathepsin enzymes represent an important family of lysosomal proteinases with a broad spectrum of functions in many, if not in all, tissues and cell types. In addition to their primary role during the normal protein turnover, they possess highly specific proteolytic activities, including antigen processing in the immune response and a direct role in the development of obesity and tumours. In pigs, the involvement of cathepsin enzymes in proteolytic processes have important effects during the conversion of muscle to meat, due to their influence on meat texture and sensory characteristics, mainly in seasoned products. Their contribution is fundamental in flavour development of dry-curing hams. However, several authors have demonstrated that high cathepsin activity, in particular of cathepsin B, is correlated to defects of these products, such as an excessive meat softness together with abnormal free tyrosine content, astringent or metallic aftertastes and formation of a white film on the cut surface. Thus, investigation of their genetic variability could be useful to identify DNA markers associated with these dry cured hams parameters, but also with meat quality, production and carcass traits in Italian heavy pigs. Unfortunately, no association has been found between cathepsin markers and meat quality traits so far, in particular with cathepsin B activity, suggesting that other genes, besides these, affect meat quality parameters. Nevertheless, significant associations were observed with several carcass and production traits in pigs. A recent study has demonstrated that different single nucleotide polymorphisms (SNPs) localized in cathepsin D (CTSD), F (CTSF), H and Z genes were highly associated with growth, fat deposition and production traits in an Italian Large White pig population. The aim of this thesis was to confirm some of these results in other pig populations and identify new cathepsin markers in order to evaluate their effects on cathepsin activity and other production traits. Furthermore, starting from the data obtained in previous studies on CTSD gene, we also analyzed the known polymorphism located in the insulin-like growth factor 2 gene (IGF2 intron3-g.3072G>A). This marker is considered the causative mutation for the quantitative trait loci (QTL) affecting muscle mass and fat deposition in pigs. Since IGF2 maps very close to CTSD on porcine chromosome (SSC) 2, we wanted to clarify if the effects of the CTSD marker were due to linkage disequilibrium with the IGF2 intron3-g.3072G>A mutation or not. In the first chapter, we reported the results from these two SSC2 gene markers. First of all, we evaluated the effects of the IGF2 intron3-g.3072G>A polymorphism in the Italian Large White breed, for which no previous studies have analysed this marker. Highly significant associations were identified with all estimated breeding values for production and carcass traits (P<0.00001), while no effects were observed for meat quality traits. Instead, the IGF2 intron3-g.3072G>A mutation did not show any associations with the analyzed traits in the Italian Duroc pigs, probably due to the low level of variability at this polymorphic site for this breed. In the same Duroc pig population, significant associations were obtained for the CTSD marker for all production and carcass traits (P < 0.001), after excluding possible confounding effects of the IGF2 mutation. The effects of the CTSD g.70G>A polymorphism were also confirmed in a group of Italian Large White pigs homozygous for the IGF2 intron3-g.3072G allele G (IGF2 intron3-g.3072GG) and by haplotype analysis between the markers of the two considered genes. Taken together, all these data indicated that the IGF2 intron3-g.3072G>A mutation is not the only polymorphism affecting fatness and muscle deposition in pigs. In the second chapter, we reported the analysis of two new SNPs identified in cathepsin L (CTSL) and cathepsin S (CTSS) genes and the association results with meat quality parameters (including cathepsin B activity) and several production traits in an Italian Large White pig population. Allele frequencies of these two markers were evaluated in 7 different pig breeds. Furthermore, we mapped using a radiation hybrid panel the CTSS gene on SSC4. Association studies with several production traits, carried out in 268 Italian Large White pigs, indicated positive effects of the CTSL polymorphism on average daily gain, weight of lean cuts and backfat thickness (P<0.05). The results for these latter traits were also confirmed using a selective genotype approach in other Italian Large White pigs (P<0.01). In the 268 pig group, the CTSS polymorphism was associated with feed:gain ratio and average daily gain (P<0.05). Instead, no association was observed between the analysed markers and meat quality parameters. Finally, we wanted to verify if the positive results obtained for the cathepsin L and S markers and for other previous identified SNPs (cathepsin F, cathepsin Z and their inhibitor cystatin B) were confirmed in the Italian Duroc pig breed (third chapter). We analysed them in two groups of Duroc pigs: the first group was made of 218 performance-tested pigs not selected by any phenotypic criteria, the second group was made of 100 Italian Duroc pigs extreme and divergent for visible intermuscular fat trait. In the first group, the CTSL polymorphism was associated with weight of lean cuts (P<0.05), while suggestive associations were obtained for average daily gain and backfat thickness (P<0.10). Allele frequencies of the CTSL gene marker also differed positively among the visible intermuscular extreme tails. Instead, no positive effects were observed for the other DNA markers on the analysed traits. In conclusion, in agreement with the present data and for the biological role of these enzymes, the porcine CTSD and CTSL markers: a) may have a direct effect in the biological mechanisms involved in determining fat and lean meat content in pigs, or b) these markers could be very close to the putative functional mutation(s) present in other genes. These findings have important practical applications, in particular the CTSD and CTSL mutations could be applied in a marker assisted selection (MAS) both in the Italian Large White and Italian Duroc breeds. Marker assisted selection could also increase in efficiency by adding information from the cathepsin S genotype, but only in the Italian Large White breed.

Procedures of quality control and data analysis of multi-site ground-based observations for the absolute flux calibration of Gaia

The Gaia space mission is a major project for the European astronomical community. As challenging as it is, the processing and analysis of the huge data-flow incoming from Gaia is the subject of thorough study and preparatory work by the DPAC (Data Processing and Analysis Consortium), in charge of all aspects of the Gaia data reduction. This PhD Thesis was carried out in the framework of the DPAC, within the team based in Bologna. The task of the Bologna team is to define the calibration model and to build a grid of spectro-photometric standard stars (SPSS) suitable for the absolute flux calibration of the Gaia G-band photometry and the BP/RP spectrophotometry. Such a flux calibration can be performed by repeatedly observing each SPSS during the life-time of the Gaia mission and by comparing the observed Gaia spectra to the spectra obtained by our ground-based observations. Due to both the different observing sites involved and the huge amount of frames expected (≃100000), it is essential to maintain the maximum homogeneity in data quality, acquisition and treatment, and a particular care has to be used to test the capabilities of each telescope/instrument combination (through the “instrument familiarization plan”), to devise methods to keep under control, and eventually to correct for, the typical instrumental effects that can affect the high precision required for the Gaia SPSS grid (a few % with respect to Vega). I contributed to the ground-based survey of Gaia SPSS in many respects: with the observations, the instrument familiarization plan, the data reduction and analysis activities (both photometry and spectroscopy), and to the maintenance of the data archives. However, the field I was personally responsible for was photometry and in particular relative photometry for the production of short-term light curves. In this context I defined and tested a semi-automated pipeline which allows for the pre-reduction of imaging SPSS data and the production of aperture photometry catalogues ready to be used for further analysis. A series of semi-automated quality control criteria are included in the pipeline at various levels, from pre-reduction, to aperture photometry, to light curves production and analysis.

Sensory and instrumental profiling of apples: a new tool for quality assessment

Food suppliers currently measure apple quality considering basic pomological descriptors. Sensory analysis is expensive, does not permit to analyse many samples, and cannot be implemented for measuring quality properties in real time. However, sensory analysis is the best way to precisely describe food eating quality, since it is able to define, measure, and explain what is really perceivable by human senses and using a language that closely reflects the consumers’ perception. On the basis of such observations, we developed a detailed protocol for apple sensory profiling by descriptive sensory analysis and instrumental measurements. The collected sensory data were validated by applying rigorous scientific criteria for sensory analysis. The method was then applied for studying sensory properties of apples and their changes in relation to different pre- and post-harvest factors affecting fruit quality, and demonstrated to be able to discriminate fruit varieties and to highlight differences in terms of sensory properties. The instrumental measurements confirmed such results. Moreover, the correlation between sensory and instrumental data was studied, and a new effective approach was defined for the reliable prediction of sensory properties by instrumental characterisation. It is therefore possible to propose the application of this sensory-instrumental tool to all the stakeholders involved in apple production and marketing, to have a reliable description of apple fruit quality.