<p>The aim of this study is to synthesize a material with high thermal conductivity and a low coefficient of thermal expansion (CTE), useful as a heat sink. Carbon nanofibres (CNF) are first coated with copper by an electroless plating technique and then sintered to a solid sample by either spark plasma sintering (SPS) or hot pressing (HP). The final product is a carbon nanofibre reinforced copper composite. Two different fibre structures are considered: platlet (PL) and herringbone (HB). The influence of the amount of CNF reinforcement (6-24 %wt), on the thermal conductivity and CTE is studied. CNF has an excellent thermal conductivity in the direction along the fibre while it is poor in the transverse direction. The CTE is close to zero in the temperature range of interest. The adhesion of Cu to the CNF surface is in general poor and thus improving the the wetting of the copper by surface modifications of the fibres are of interest such that thermal gaps in the microstructure can be avoided. The poor wetting results in CNF agglomerates, resulting in an inhomogeneous microstructure. In this report a combination of three different types of surface modifications has been tested: (1) electroless deposition of copper was used to improve Cu impregnation of CNF; (2) heat treatment of CNF to improve wetting; and (3) introduction of a Cr buffer layer to further enhance wetting. The obtained composite microstructures are characterized in terms of chemical composition, grain size and degree of agglomeration. In addition their densities are also reported. The thermal properties were evaluated in terms of thermal diffusivity, thermal conductivity and CTE. Cr/Cu coated platelet fibres (6wt% of CNF reinforcement) sintered by SPS is the sample with the highest thermal conductivity, ~200 W/Km. The thermal conductivity is found to decrease with increasing content of CNFs.</p>

The aim of this study is to synthesize a material with high thermal conductivity and a low coefficient of thermal expansion (CTE), useful as a heat sink. Carbon nanofibres (CNF) are first coated with copper by an electroless plating technique and then sintered to a solid sample by either spark plasma sintering (SPS) or hot pressing (HP). The final product is a carbon nanofibre reinforced copper composite. Two different fibre structures are considered: platlet (PL) and herringbone (HB). The influence of the amount of CNF reinforcement (6-24 %wt), on the thermal conductivity and CTE is studied. CNF has an excellent thermal conductivity in the direction along the fibre while it is poor in the transverse direction. The CTE is close to zero in the temperature range of interest. The adhesion of Cu to the CNF surface is in general poor and thus improving the the wetting of the copper by surface modifications of the fibres are of interest such that thermal gaps in the microstructure can be avoided. The poor wetting results in CNF agglomerates, resulting in an inhomogeneous microstructure. In this report a combination of three different types of surface modifications has been tested: (1) electroless deposition of copper was used to improve Cu impregnation of CNF; (2) heat treatment of CNF to improve wetting; and (3) introduction of a Cr buffer layer to further enhance wetting. The obtained composite microstructures are characterized in terms of chemical composition, grain size and degree of agglomeration. In addition their densities are also reported. The thermal properties were evaluated in terms of thermal diffusivity, thermal conductivity and CTE. Cr/Cu coated platelet fibres (6wt% of CNF reinforcement) sintered by SPS is the sample with the highest thermal conductivity, ~200 W/Km. The thermal conductivity is found to decrease with increasing content of CNFs.

This work describes a tool for extraction of features in 2D images applied to industrial automation. The method uses techniques implemented targeting of images into pieces model as detection of edges in the extraction of spatial coordinates of the image and import applications in CAD (Computer-Aided Design) for the generation of programmers for Computer Numerical Control (CNC). This work is to copy a particular model (image) from an existing object, which features a process of reverse engineering. An initial prototype was developed using the Java language with the Eclipse IDE and library for handling complex images, the API Java Advanced Image (JAI). For the acquisition of parts to be machined, was prepared an environment of lighting to highlight areas of interest improving the luminance of the same and enabling the application of techniques developed in this prototype. Different operators for detecting edges were exploited in order to implement the best technical and that best represent the real piece. A new technique of targeting the prototype was adapted from the integration of technology Java / MatLab and with the acquisition of images through technical Multi-flash. After the application of different processing techniques, a text file containing the coordinates of the image (piece) is generated and imported into CAD. In the CAD environment, runs calculating the trajectory of the tool that identifies the geometry of the piece and defines the path of the tool in the generation of CNC program for breeding the same. Results presented and evaluation of the tool demonstrates the feasibility of applying the automated system developed as part of parts to play in numerical control machines. / O presente trabalho descreve uma ferramenta para extração de características em imagens 2D aplicado à automação industrial. O método implementado utiliza técnicas de segmentação de imagens em peças modelo, como detecção de bordas, na extração das coordenadas espaciais da imagem e importação em aplicativos CAD (Computer-Aided Design) para a geração de programas de Comando Numérico Computadorizado (CNC). Este trabalho consiste em copiar um determinado modelo (imagem) partindo de um objeto já existente, o que caracteriza um processo de engenharia reversa. Um protótipo inicial foi desenvolvido usando a linguagem Java com o IDE Eclipse e a biblioteca para manipulação de imagens complexas, o API Java Advanced Image (JAI). Para a aquisição das peças a serem usinadas, foi elaborado um ambiente de iluminação a fim de ressaltar áreas de interesse melhorando a luminância das mesmas e viabilizando a aplicação das técnicas desenvolvidas nesse protótipo. Diferentes operadores de detecção de bordas foram explorados, a fim de aplicar a melhor técnica e que melhor representasse a peça real. Uma nova técnica de segmentação foi adaptada ao protótipo, a partir da integração da tecnologia Java/MatLab e com a aquisição de imagens através da técnica Multi-flash. Após a aplicação de diferentes técnicas de processamento, um arquivo texto contendo as coordenadas da imagem (peça) é gerado e importado no CAD. No ambiente CAD, é executado o cálculo da trajetória da ferramenta que identifica a geometria da peça e define o caminho da ferramenta na geração do programa CNC para reprodução da mesma. Resultados apresentados e a avaliação da ferramenta demonstram a viabilidade de aplicação do sistema desenvolvido como parte automatizada para reprodução de peças em máquinas de comando numérico.

Zellulare metallische Strukturen zeichnen sich durch ihre hohe Porosität und ihre komplexe geometrische Struktur aus. Dadurch ist die Bestimmung ihrer Wärmeleitfähigkeit eine komplizierte und aufwändige Messaufgabe. Für die vorliegende Arbeit wurden Materialien ausgewählt, die sich im Grundmaterial, in der Herstellungsmethode und im strukturellen Aufbau unterscheiden. Dabei wurden Materialien mit unterschiedlicher Porosität und Porengröße untersucht. Die effektive Wärmeleitfähigkeit wurde mit drei unterschiedlichen Messverfahren bestimmt. Die Messungen wurden bei normalem Druck bei Raumtemperatur und für ausgewählte Materialien bis maximal 800 °C durchgeführt. Dabei wurden die Bedingungen für die optimale Durchführung der Messungen und die Probleme jedes Verfahrens herausgearbeitet. Daraus wurden Empfehlungen für die optimale Messungsdurchführung abgeleitet. Die gewonnenen Messergebnisse wurden miteinander, mit Werten aus der Literatur und mit vorhandenen mathematischen Modellen verglichen.

Zellulare metallische Strukturen zeichnen sich durch ihre hohe Porosität und ihre komplexe geometrische Struktur aus. Dadurch ist die Bestimmung ihrer Wärmeleitfähigkeit eine komplizierte und aufwändige Messaufgabe. Für die vorliegende Arbeit wurden Materialien ausgewählt, die sich im Grundmaterial, in der Herstellungsmethode und im strukturellen Aufbau unterscheiden. Dabei wurden Materialien mit unterschiedlicher Porosität und Porengröße untersucht. Die effektive Wärmeleitfähigkeit wurde mit drei unterschiedlichen Messverfahren bestimmt. Die Messungen wurden bei normalem Druck bei Raumtemperatur und für ausgewählte Materialien bis maximal 800 °C durchgeführt. Dabei wurden die Bedingungen für die optimale Durchführung der Messungen und die Probleme jedes Verfahrens herausgearbeitet. Daraus wurden Empfehlungen für die optimale Messungsdurchführung abgeleitet. Die gewonnenen Messergebnisse wurden miteinander, mit Werten aus der Literatur und mit vorhandenen mathematischen Modellen verglichen.