Cu2ZnSnS4 absorber layers obtained through sulphurization of metallic precursors: Graphite box versus sulphur flux

In this work we employed a hybrid method, combining RF-magnetron sputtering with evaporation, for the deposition of tailor made metallic precursors, with varying number of Zn/Sn/Cu (ZTC) periods and compared two approaches to sulphurization. Two series of samples with 1×, 2× and 4× ZTC periods have been prepared. One series of precursors was sulphurized in a tubular furnace directly exposed to a sulphur vapour and N2+5% H2 flux at a pressure of 5.0×10+4 Pa. A second series of identical precursors was sulphurized in the same furnace but inside a graphite box where sulphur pellets have been evaporated again in the presence of N2+5% H2 and at the same pressure as for the sulphur flux experiments. The morphological and chemical analyses revealed a small grain structure but good average composition for all three films sulphurized in the graphite box. As for the three films sulphurized in sulphur flux grain growth was seen with the increase of the number of ZTC periods whilst, in terms of composition, they were slightly Zn poor. The films' crystal structure showed that Cu2ZnSnS4 is the dominant phase. However, in the case of the sulphur flux films SnS2 was also detected. Photoluminescence spectroscopy studies showed an asymmetric broad band emission whichoccurs in the range of 1–1.5 eV. Clearly the radiative recombination efficiency is higher in the series of samples sulphurized in sulphur flux. We have found that sulphurization in sulphur flux leads to better film morphology than when the process is carried out in a graphite box in similar thermodynamic conditions. Solar cells have been prepared and characterized showing a correlation between improved film morphology and cell performance. The best cells achieved an efficiency of 2.4%.

Influence of selenization pressure on the growth of Cu2ZnSnSe4 films from stacked metallic layers

Cu2ZnSnSe4 (CZTSe) is a p-type semiconductor with a high absorption coefficient, 104 to 105 cm-1, and is being seen as a possible replacement for Cu(In,Ga)Se2 in thin film solar cells. Yet, there are some fundamental properties of CZTSe that are not well known, one of them is its band gap. In order to resolve its correct value it is necessary to improve the growth conditions to ensure that single phase crystalline thin films are obtained. One of the problems encountered when growing CZTSe is the loss of Sn through evaporation of SnSe. Stoichiometric films are then difficult to obtain and usually there are other phases present. One possible way to overcome this problem is to increase the pressure of growth of CZTSe. This can be done by introducing an atmosphere of an inert gas like Ar or N2. In this work we report the results of morphological, structural and optical studies of the properties of CZTSe thin films grown by selenization of DC magnetron sputtered metallic layers under different Ar pressures. The films are analysed by SEM/EDS, Raman scattering and XRD.

Improving quality-of-service in wireless sensor networks by mitigating “Hidden-Node Collisions”

Wireless sensor networks (WSNs) emerge as underlying infrastructures for new classes of large-scale networked embedded systems. However, WSNs system designers must fulfill the quality-of-service (QoS) requirements imposed by the applications (and users). Very harsh and dynamic physical environments and extremely limited energy/computing/memory/communication node resources are major obstacles for satisfying QoS metrics such as reliability, timeliness, and system lifetime. The limited communication range of WSN nodes, link asymmetry, and the characteristics of the physical environment lead to a major source of QoS degradation in WSNs-the ldquohidden node problem.rdquo In wireless contention-based medium access control (MAC) protocols, when two nodes that are not visible to each other transmit to a third node that is visible to the former, there will be a collision-called hidden-node or blind collision. This problem greatly impacts network throughput, energy-efficiency and message transfer delays, and the problem dramatically increases with the number of nodes. This paper proposes H-NAMe, a very simple yet extremely efficient hidden-node avoidance mechanism for WSNs. H-NAMe relies on a grouping strategy that splits each cluster of a WSN into disjoint groups of non-hidden nodes that scales to multiple clusters via a cluster grouping strategy that guarantees no interference between overlapping clusters. Importantly, H-NAMe is instantiated in IEEE 802.15.4/ZigBee, which currently are the most widespread communication technologies for WSNs, with only minor add-ons and ensuring backward compatibility with their protocols standards. H-NAMe was implemented and exhaustively tested using an experimental test-bed based on ldquooff-the-shelfrdquo technology, showing that it increases network throughput and transmission success probability up to twice the values obtained without H-NAMe. H-NAMe effectiveness was also demonstrated in a target tracking application with mobile robots - over a WSN deployment.

ViDi Stat

A tese desenvolvida tem como foco fornecer os meios necessários para extrair conhecimento contidos no histórico académico da instituição transformando a informação em algo simples e de fácil leitura para qualquer utilizador. Com o progresso da sociedade, as escolas recebem milhares de alunos todos os anos que terão de ser orientados e monitorizados pelos dirigentes das instituições académicas de forma a garantir programas eficientes e adequados para o progresso educacional de todos os alunos. Atribuir a um docente a responsabilidade de actuar segundo o historial académico dos seus alunos não é plausível uma vez que um aluno consegue produzir milhares de registos para análise. O paradigma de mineração de dados na educação surge com a necessidade de otimizar os recursos disponíveis expondo conclusões que não se encontram visiveis sem uma análise acentuada e cuidada. Este paradigma expõe de forma clara e sucinta os dados estatísticos analisados por computador oferecendo a possibilidade de melhorar as lacunas na qualidade de ensino das instituições. Esta dissertação detalha o desenvolvimento de uma ferramente de inteligência de negócio capaz de, através de mineração de dados, analisar e apresentar conclusões pertinentes de forma legível ao utilizador.