En esta tesis doctoral, se ha investigado y desarrollado un nuevo método de CVD asistido por aerosol (AACVD), que permite el crecimiento de nanoestructuras de WO3 intrínsecas y funcionalizadas con Au. Así mismo se han depositado capas policristalinas de SnO2 para aplicaciones de detección de gases. La síntesis de materiales nanoestructurados, la fabricación de dispositivos y sus propiedades de detección de gases, han sido estudiadas. El método AACVD fue utilizado para la síntesis y la deposición directa de capas activas encima de sustratos de alúmina y también sobre substratos micromecanizados (microhotplates), lo que demuestra la compatibilidad entre la tecnología de silicio y la deposición de la capas activas nanoestructuradas. En la tesis se ha demostrado que las capas nanoestructuradas de WO3 funcionalizadas con oro tienen una sensibilidad mejor que las intrínsecas frente a algunos gases relevantes y al mismo tiempo se ha producido un cambio de selectividad. / In this doctoral thesis, it has been investigated and developed the Aerosol Assisted Chemical Vapour Deposition (AACVD) method for direct in-situ growth of intrinsic and Au-functionalised nanostructured WO3, as well as SnO2-based devices for gas sensing applications. The nanostructured material synthesis, device fabrication and their gas sensing properties have been studied. AACVD method was used for synthesis and direct deposition of sensing films onto classical alumina and microhotplate gas sensor substrates, demonstrating the compatibility between the microhotplate fabrication process and the sensing nanostructured layer deposition. The effect of Au nanoparticles on the gas sensor’s response was measured and presented in this thesis. The test results revealed that the addition of Au nanoparticles to the WO3 nanoneedles has increased the sensor’s response towards the tested gases (i.e. EtOH). It was therefore demonstrated that the Au-functionalisation has an enhancing effect on the gas sensing properties of WO3 nanoneedles

The focus of the present research is to find the relative thermodynamic stability of ?-boron and ?-boron via heat capacity measurements. Efforts to synthesize ?-boron through the application of vapour-liquid-solid theory resulted in the discovery of a new chemical vapour deposition approach. The heat capacities of both synthesized ?-boron and commercial (99.5%) ?-boron were determined using relaxation calorimetry over the temperature range 0.2 K to 400 K. These data, in combination with literature information, allowed the calculation of the Gibbs energy of the ?-boron to ?-boron transition from 0 K to 1985 K. It was found that the transition from ?-boron to ?-boron was thermodynamically favourable at all temperatures up to 1985 K with a value of ?Gt(T = 300 K) = -10 kJ mol-1 ± 1 kJ mol-1 and ?Gt(T = 1985 K) = -15 kJ mol-1 ± 1 kJ mol-1.

Graphene is one of the most popular material due to its promising properties, for instance electronics applications. Graphene films were grown on silicon carbide (SiC) substrate using chemical vapor deposition (CVD). Influence of the deposition temperature on the morphology of the films was investigated. Characterizations were done by reflectance mapping, atomic force microscopy and Raman spectroscopy. Two samples were done by sublimation process, to compare the number of layers and the morphology of the graphene films with the one grown by chemical vapor deposition.The reflectance mapping showed that the number of layers on the samples made by CVD was notinfluenced by the deposition temperature. But also, demonstrated that sublimation growth is present in allthe samples due to the presence of silicon coating in the susceptor. The growth probably started by sublimation and then CVD deposition. The step morphology characteristic of the silicon carbide substrate surface was conserved during the deposition of graphene. But due to surface step bunching, a decrease inthe step height occurred and the width of the terraces increased. The decreasing in deposition temperature leads to a smoother surface with the CVD method. Raman spectroscopy confirmed the presence ofgraphene and of the buffer layer characteristic of the sublimation growth. Moreover, it demonstrated the presence of compressive strain in the graphene layers.

CIGS thin film solar cells usually include a thin layer of intrinsic zinc oxide (i-ZnO) deposited on a CdS buffer layer by sputtering. However an interest has grown in using chemical vapor deposition (CVD) instead. Hence, the aim of this thesis was to study how well CVD i-ZnO performs on a CdS buffer layer in a CIGS solar cell and how the properties of the layer can be controlled when using a hot-wall CVD reactor with diethylzinc and water as precursors. The process was characterized through depositions on glass substrates and was then successfully implemented in solar cell devices. The main influences of temperature, thickness and precursor flows on resistivity, optical band gap and film structure were mapped out. The analysis methods used included X-ray diffraction (XRD), X-ray fluorescence (XRF), four point probe resistivity measurements, mechanical profilometry and absorption spectrophotometry. In addition, the solar cell devices were characterized using external quantum efficiency (EQE) and current-voltage (IV) measurements. It was found that the CVD process was sensitive to the condition of the CdS surface, which resulted in a large distribution of shunted cells when grown on aged CdS. Unexpected trends in open-circuit voltage and fill factor were found. Both these factors increased when the growth temperature was decreased, resulting in higher conversion efficiencies. Compared to i-ZnO deposited by an in-house baseline sputtering process, the CVD process resulted in cells with higher short-circuit current due to higher EQE in the short-wavelength region. It was shown that the CVD process used is capable of producing solar cell devices whose performances contest those of cells manufactured with sputtered i-ZnO.

The purpose of this study was to compare between ethnicities if there is a difference in survival and treatment when it comes to cardiovascular diseases in the Middle East. To find out if there is a difference 28 articles was selected for inclusion, both qualitative and quantitative studies. Searches were made in the databases Medline, PubMed, Google and Google Scholar.The results showed that it is possible that there are differences in mortality and morbidity between ethnicities affected by cardiovascular disease. These may be due to differences in abdominal obesity, insulin resistance in diabetes and other risks such as C-reactive protein in the blood plasma which is normally excreted in inflammation in the body and also adiponectin, which is a hormone found in fat tissue whose secretion is diminished in people who have diabetes. But studies saying that a difference does exist are too few and the need for more and larger studies is needed. It may also be that not all ethnicities are as benefited from current treatments available against cardiovascular diseases for example beta-blockers. The conclusion of this study is that more research in this area is needed as well as more comprehensive studies regarding public health in the Middle East. / Syftet med denna studie var att jämföra mellan etniska grupper om det finns en skillnad i överlevnad och behandling när det gäller hjärt-och kärlsjukdomar i Mellanöstern. För att ta reda på det har 28 artiklar valts ut efter inklusionskriterierna, både kvalitativa och kvantitativa studier. Sökningar gjordes i databaserna Medline, Pubmed, Google and Google Scholar.Resultatet visade på att det sannolikt finns skillnader i dödlighet samt sjuklighet mellan etniciteter som drabbats av hjärt- och kärlsjukdomar. Dessa kan bero på skillnader i abdominal fetma, insulin resistens vid diabetes och andra risker så som C-reaktivt protein som finns i blodplasman och i vanliga fall utsöndras vid inflammationer i kroppen och adiponectin som är ett hormon som finns i fettvävnaden vars utsöndring är sämre hos personer som har diabetes. Dock är studierna som visar på skillnader alldeles för få, det behövs fler och större undersökningar inom detta område. Denna litteratur översikt visar också att det även kan vara så att inte alla etniciteter gynnas av dagens behandlingar som finns mot hjärt- och kärlsjukdomar som t ex Betablockerare. Slutsatsen i denna studie är att mer forskning inom ämnet behövs samt fler övergripande studier gällande folkhälsan i Mellanöstern.

Medicine and health domains are information intensive fields as data volume has been increasing constantly from them. In order to make full use of the data, the technique of Knowledge Discovery in Databases (KDD) has been developed as a comprehensive pathway to discover valid and unsuspected patterns and trends that are both understandable and useful to data analysts. The present study aimed to investigate the entire KDD process of developing a classification model for cardiovascular disease (CVD) from a Canadian dataset for the first time. The research data source was Canadian Heart Health Database, which contains 265 easily collected variables and 23,129 instances from ten Canadian provinces. Many practical issues involving in different steps of the integrated process were addressed, and possible solutions were suggested based on the experimental results. Five specific learning schemes representing five distinct KDD approaches were employed, as they were never compared with one another. In addition, two improving approaches including cost-sensitive learning and ensemble learning were also examined. The performance of developed models was measured in many aspects. The data set was prepared through data cleaning and missing value imputation. Three pairs of experiments demonstrated that the dataset balancing and outlier removal exerted positive influence to the classifier, but the variable normalization was not helpful. Three combinations of subset generation method and evaluation function were tested in variable subset selection phase, and the combination of Best-First search and Correlation-based Feature Selection showed comparable goodness and was maintained for other benefits. Among the five learning schemes investigated, C4.5 decision tree achieved the best performance on the classification of CVD, followed by Multilayer Feed-forward Network, KNearest Neighbor, Logistic Regression, and Naïve Bayes. Cost-sensitive learning exemplified by the MetaCost algorithm failed to outperform the single C4.5 decision tree when varying the cost matrix from 5:1 to 1:7. In contrast, the models developed from ensemble modeling, especially AdaBoost M1 algorithm, outperformed other models. Although the model with the best performance might be suitable for CVD screening in general Canadian population, it is not ready to use in practice. I propose some criteria to improve the further evaluation of the model. Finally, I describe some of the limitations of the study and propose potential solutions to address such limitations through out the KDD process. Such possibilities should be explored in further research.

Zugl.: Braunschweig, Techn. Universiẗat, Diss., 2008.

Zugl.: Dresden, Techn. Univ., Diss., 2009

Zugl.: Berlin, Techn. Univ., Diss., 2009

Saarbrücken, Univ., Diplomarb., 1996.