Microfabrication processes for microfluidic devices on a single laser Workstation: direct writing lithography on SU-8, laser ablation on polymers and mask manufacturing

We demonstrate the capability of a laser micromachining workstation for cost-effective manufacturing of a variety of microfluidic devices, including SU-8 microchannels on silicon wafers and 3D complex structures made on polyimide Kapton® or poly carbonate (PC). The workstation combines a KrF excimer laser at 248 nm and a Nd3+:YVO4 DPSS with a frequency tripled at 355 nm with a lens magnification 10X, both lasers working at a pulsed regime with nanoseconds (ns) pulse duration. Workstation also includes a high-resolution motorized XYZ-tilt axis (~ 1 um / axis) and a Through The Lens (TTL) imaging system for a high accurate positioning over a 120 x 120 mm working area. We have surveyed different fabrication techniques: direct writing lithography,mask manufacturing for contact lithography and polymer laser ablation for complex 3D devices, achieving width channels down to 13μ m on 50μ m SU-8 thickness using direct writing lithography, and width channels of 40 μm for polyimide on SiO2 plate. Finally, we have tested the use of some devices for capillary chips measuring the flow speed for liquids with different viscosities. As a result, we have characterized the presence of liquid in the channel by interferometric microscopy.

Processing and adsorption control in ZnO single nanowire photodetectors

ZnO single nanowire photodetectors have been measured in different ambient conditions in order to understand and control adsorption processes on the surface. A decrease in the conductivity has been observed as a function of time when the nanowires are exposed to air, due to adsorbed O2/H2O species at the nanowire surface. In order to have a device with stable characteristics in time, thermal desorption has been used to recover the original conductivity followed by PMMA coating of the exposed nanowire surface.

Evaluation of a Change Detection Methodology by Means of Binary Thresholding Algorithms and Informational Fusion Processes

Landcover is subject to continuous changes on a wide variety of temporal and spatial scales. Those changes produce significant effects in human and natural activities. Maintaining an updated spatial database with the occurred changes allows a better monitoring of the Earth?s resources and management of the environment. Change detection (CD) techniques using images from different sensors, such as satellite imagery, aerial photographs, etc., have proven to be suitable and secure data sources from which updated information can be extracted efficiently, so that changes can also be inventoried and monitored. In this paper, a multisource CD methodology for multiresolution datasets is applied. First, different change indices are processed, then different thresholding algorithms for change/no_change are applied to these indices in order to better estimate the statistical parameters of these categories, finally the indices are integrated into a change detection multisource fusion process, which allows generating a single CD result from several combination of indices. This methodology has been applied to datasets with different spectral and spatial resolution properties. Then, the obtained results are evaluated by means of a quality control analysis, as well as with complementary graphical representations. The suggested methodology has also been proved efficiently for identifying the change detection index with the higher contribution.

Double ion implantation and pulsed laser melting processes for third generation solar cells

In the framework of the third generation of photovoltaic devices, the intermediate band solar cell is one of the possible candidates to reach higher efficiencies with a lower processing cost. In this work, we introduce a novel processing method based on a double ion implantation and, subsequently, a pulsed laser melting (PLM) process to obtain thicker layers of Ti supersaturated Si. We perform ab initio theoretical calculations of Si impurified with Ti showing that Ti in Si is a good candidate to theoretically form an intermediate band material in the Ti supersaturated Si. From time-of-flight secondary ion mass spectroscopy measurements, we confirm that we have obtained a Ti implanted and PLM thicker layer of 135 nm. Transmission electron microscopy reveals a single crystalline structure whilst the electrical characterization confirms the transport properties of an intermediate band material/Si substrate junction. High subbandgap absorption has been measured, obtaining an approximate value of 104 cm−1 in the photons energy range from 1.1 to 0.6 eV.

Utilizing the Internet of Things to promote energy awareness and efficiency at discrete production processes: Practices and methodology

El actual contexto de fabricación, con incrementos en los precios de la energía, una creciente preocupación medioambiental y cambios continuos en los comportamientos de los consumidores, fomenta que los responsables prioricen la fabricación respetuosa con el medioambiente. El paradigma del Internet de las Cosas (IoT) promete incrementar la visibilidad y la atención prestada al consumo de energía gracias tanto a sensores como a medidores inteligentes en los niveles de máquina y de línea de producción. En consecuencia es posible y sencillo obtener datos de consumo de energía en tiempo real proveniente de los procesos de fabricación, pero además es posible analizarlos para incrementar su importancia en la toma de decisiones. Esta tesis pretende investigar cómo utilizar la adopción del Internet de las Cosas en el nivel de planta de producción, en procesos discretos, para incrementar la capacidad de uso de la información proveniente tanto de la energía como de la eficiencia energética. Para alcanzar este objetivo general, la investigación se ha dividido en cuatro sub-objetivos y la misma se ha desarrollado a lo largo de cuatro fases principales (en adelante estudios). El primer estudio de esta tesis, que se apoya sobre una revisión bibliográfica comprehensiva y sobre las aportaciones de expertos, define prácticas de gestión de la producción que son energéticamente eficientes y que se apoyan de un modo preeminente en la tecnología IoT. Este primer estudio también detalla los beneficios esperables al adoptar estas prácticas de gestión. Además, propugna un marco de referencia para permitir la integración de los datos que sobre el consumo energético se obtienen en el marco de las plataformas y sistemas de información de la compañía. Esto se lleva a cabo con el objetivo último de remarcar cómo estos datos pueden ser utilizados para apalancar decisiones en los niveles de procesos tanto tácticos como operativos. Segundo, considerando los precios de la energía como variables en el mercado intradiario y la disponibilidad de información detallada sobre el estado de las máquinas desde el punto de vista de consumo energético, el segundo estudio propone un modelo matemático para minimizar los costes del consumo de energía para la programación de asignaciones de una única máquina que deba atender a varios procesos de producción. Este modelo permite la toma de decisiones en el nivel de máquina para determinar los instantes de lanzamiento de cada trabajo de producción, los tiempos muertos, cuándo la máquina debe ser puesta en un estado de apagada, el momento adecuado para rearrancar, y para pararse, etc. Así, este modelo habilita al responsable de producción de implementar el esquema de producción menos costoso para cada turno de producción. En el tercer estudio esta investigación proporciona una metodología para ayudar a los responsables a implementar IoT en el nivel de los sistemas productivos. Se incluye un análisis del estado en que se encuentran los sistemas de gestión de energía y de producción en la factoría, así como también se proporcionan recomendaciones sobre procedimientos para implementar IoT para capturar y analizar los datos de consumo. Esta metodología ha sido validada en un estudio piloto, donde algunos indicadores clave de rendimiento (KPIs) han sido empleados para determinar la eficiencia energética. En el cuarto estudio el objetivo es introducir una vía para obtener visibilidad y relevancia a diferentes niveles de la energía consumida en los procesos de producción. El método propuesto permite que las factorías con procesos de producción discretos puedan determinar la energía consumida, el CO2 emitido o el coste de la energía consumida ya sea en cualquiera de los niveles: operación, producto o la orden de fabricación completa, siempre considerando las diferentes fuentes de energía y las fluctuaciones en los precios de la misma. Los resultados muestran que decisiones y prácticas de gestión para conseguir sistemas de producción energéticamente eficientes son posibles en virtud del Internet de las Cosas. También, con los resultados de esta tesis los responsables de la gestión energética en las compañías pueden plantearse una aproximación a la utilización del IoT desde un punto de vista de la obtención de beneficios, abordando aquellas prácticas de gestión energética que se encuentran más próximas al nivel de madurez de la factoría, a sus objetivos, al tipo de producción que desarrolla, etc. Así mismo esta tesis muestra que es posible obtener reducciones significativas de coste simplemente evitando los períodos de pico diario en el precio de la misma. Además la tesis permite identificar cómo el nivel de monitorización del consumo energético (es decir al nivel de máquina), el intervalo temporal, y el nivel del análisis de los datos son factores determinantes a la hora de localizar oportunidades para mejorar la eficiencia energética. Adicionalmente, la integración de datos de consumo energético en tiempo real con datos de producción (cuando existen altos niveles de estandarización en los procesos productivos y sus datos) es esencial para permitir que las factorías detallen la energía efectivamente consumida, su coste y CO2 emitido durante la producción de un producto o componente. Esto permite obtener una valiosa información a los gestores en el nivel decisor de la factoría así como a los consumidores y reguladores. ABSTRACT In today‘s manufacturing scenario, rising energy prices, increasing ecological awareness, and changing consumer behaviors are driving decision makers to prioritize green manufacturing. The Internet of Things (IoT) paradigm promises to increase the visibility and awareness of energy consumption, thanks to smart sensors and smart meters at the machine and production line level. Consequently, real-time energy consumption data from the manufacturing processes can be easily collected and then analyzed, to improve energy-aware decision-making. This thesis aims to investigate how to utilize the adoption of the Internet of Things at shop floor level to increase energy–awareness and the energy efficiency of discrete production processes. In order to achieve the main research goal, the research is divided into four sub-objectives, and is accomplished during four main phases (i.e., studies). In the first study, by relying on a comprehensive literature review and on experts‘ insights, the thesis defines energy-efficient production management practices that are enhanced and enabled by IoT technology. The first study also explains the benefits that can be obtained by adopting such management practices. Furthermore, it presents a framework to support the integration of gathered energy data into a company‘s information technology tools and platforms, which is done with the ultimate goal of highlighting how operational and tactical decision-making processes could leverage such data in order to improve energy efficiency. Considering the variable energy prices in one day, along with the availability of detailed machine status energy data, the second study proposes a mathematical model to minimize energy consumption costs for single machine production scheduling during production processes. This model works by making decisions at the machine level to determine the launch times for job processing, idle time, when the machine must be shut down, ―turning on‖ time, and ―turning off‖ time. This model enables the operations manager to implement the least expensive production schedule during a production shift. In the third study, the research provides a methodology to help managers implement the IoT at the production system level; it includes an analysis of current energy management and production systems at the factory, and recommends procedures for implementing the IoT to collect and analyze energy data. The methodology has been validated by a pilot study, where energy KPIs have been used to evaluate energy efficiency. In the fourth study, the goal is to introduce a way to achieve multi-level awareness of the energy consumed during production processes. The proposed method enables discrete factories to specify energy consumption, CO2 emissions, and the cost of the energy consumed at operation, production and order levels, while considering energy sources and fluctuations in energy prices. The results show that energy-efficient production management practices and decisions can be enhanced and enabled by the IoT. With the outcomes of the thesis, energy managers can approach the IoT adoption in a benefit-driven way, by addressing energy management practices that are close to the maturity level of the factory, target, production type, etc. The thesis also shows that significant reductions in energy costs can be achieved by avoiding high-energy price periods in a day. Furthermore, the thesis determines the level of monitoring energy consumption (i.e., machine level), the interval time, and the level of energy data analysis, which are all important factors involved in finding opportunities to improve energy efficiency. Eventually, integrating real-time energy data with production data (when there are high levels of production process standardization data) is essential to enable factories to specify the amount and cost of energy consumed, as well as the CO2 emitted while producing a product, providing valuable information to decision makers at the factory level as well as to consumers and regulators.

Hybridization Processes: The case of the urban game: Hybrid Hunt: Petrified

The proposal highlights certain design strategies and a case study that can link the material urban space to digital emerging realms. The composite nature of urban spaces ?material/ digital- is understood as an opportunity to reconfigure public urban spaces without high-cost, difficult to apply interventions and, furthermore, to reactivate them by inserting dynamic, interactive and playful conditions that engage people and re-establish their relations to the cities. The structuring of coexisting and interconnected material and digital aspects in public urban spaces is proposed through the implementation of hybridization processes. Hybrid spaces can fascinate and provoke the public and especially younger people to get involved and interact with physical aspects of urban public spaces as well as digital representations or interpretations of those. Digital game?s design in urban public spaces can be comprehended as a tool that allows architects to understand and to configure hybrids of material and digital conceptions and project all in one, as an inseparable totality. Digital technologies have for a long time now intervened in our perception of traditional dipoles such as subject - environment. Architects, especially in the past, have been responsible for material mediations and tangible interfaces that permit subjects to relate to their physical environments in a controlled and regulated manner; but, nowadays, architects are compelled to embody in design, the transition that is happening in all aspects of everyday life, that is, from material to digital realities. In addition, the disjunctive relation of material and digital realms is ceding and architects are now faced with the challenge that supposes the merging of both in a single, all-inclusive reality. The case study is a design project for a game implemented simultaneously in a specific urban space and on the internet. This project developed as the spring semester course New Media in Architecture at the Department of Architecture, Democritus University of Thrace, Greece is situated at the city of Xanthi. Composite cities can use design strategies and technological tools to configure augmented and appealing urban spaces that articulate and connect different realms in a single engaging reality.