Inkjet Printing of Functional Inks for Smart Products

Inkjet printing is a recent promising technology for direct patterning of solution-based materials over different substrates. It is particularly interesting for applications in the flexible electronics field and smart products manufacturing, as it allows for rapid prototyping, design freedom, and is compatible with conductive, semiconductive, and dielectric inks that can be cured at low temperatures over several types of substrates. Moreover, the inkjet process allows for ink economization, since great electrical conductivity can be achieved despite the deposition of small volumes of ink. This chapter describes the overall process, the main inks and their features, the critical process variables, and its limitations. Applications related to inkjet printing of functional materials and smart products are highlighted. New technology advancements and trends are finally addressed

Printing Technologies on Flexible Substrates for Printed Electronics

Printing technologies have been demonstrated to be highly efficient and compatible with polymeric materials (both inks and substrates) enabling a new generation of flexible electronics applications. Conductive flexible polymers are a new class of materials that are prepared for a wide range of applications, such as photovoltaic solar cells, transistors molecular devices, and sensors and actuators. There are many possible printing techniques. This chapter provides an opportunity to review the most common printing techniques used at the industrial level, the most commonly used substrates and electronic materials, giving an overall vision for a better understanding and evaluation of their different features. Several technological solutions (contact/noncontact) and its critical challenges are also presented. Inkjet Printing Technology (IPT) has been receiving a great attention and therefore higher focus is given to this technology. An overview of IPT is presented to evidence its importance and potential as a key-technology on the research field for printed electronics development, as well as on large scale industrial manufacturing. A background and a review on prior work are presented along with used materials, developed applications and potential of IPT technology. The main features of the different printing technologies, advantages and main challenges are also compared

Deficiências minerais em bovinos de Roraima, Brasil. IV. Magnésio, sódio e potássio

An experiment was conducted to verify the mineral levels in beef cattle from six regions of northeast Roraima Federal Territory, Brazil. The soil, forage, and bovine tissue (blood, bone) were collected during the wet and dry seasons of the year. Only the soil from Surrão region showed medium level of Mg (0.500 meq/100g) all the others presented low levels. Soil K was at medium level in Caumé region (65 ppm), and low in all the other five regions. Soil Na levels were in a range from 47 ppm to 102 ppm. Forage Mg was sufficient to meet the requirements of growing and finishing steers, but was apparently deficient for lactating cows in five of six regions studied. Forage Na and K levels were low in all six regions. The levels of Mg, Na and K in the forages were significantly (P<0.05) lower during the dry season than during the wet season. In cultivated forage Mg levels, were sufficient to meet the requirements of beef cattle and in the native species were adequate only for growing and finishing steers. Magnesium plasma levels in cattle were normal in both seasons. Rib bone ash Mg means were low and ranged from 0.32% to 0.44% in the lactating cows and form 0.28% to 0.47% in the other animals.Foi realizado um estudo das deficiências minerais de bovinos em seis regiões localizadas ao nordeste do Território Federal de Roraima, onde foram amostrados solo, forrageiras e tecido animal (sangue e osso) durante as épocas seca e chuvosa. Teor médio de Mg no solo foi encontrado apenas na região do Surrão (0,500 meq/100 g). Todas as outras regiões apresentaram níveis baixos. Nível médio de K também foi observado em apenas uma região, a de Caumé, com 65 ppm. Nas demais regiões os níveis de K no solo foram baixos. Os níveis de Na no solo variaram de 47 ppm a 102 ppm entre regiões. As forrageiras apresentaram teores de Mg adequados para bovinos de corte em crescimento e terminação, porém aparentemente inadequados para vacas em lactação, em cinco das seis regiões estudadas. Os níveis de Na e K nas forrageiras foram deficientes em todas as regiões. Os níveis de Mg, Na e K nas forrageiras foram significativamente menores (P<0,05) na época seca. As gramíneas melhoradas apresentaram teores de Mg adequados a todas as categorias de bovinos de corte e as espécies nativas mostraram níveis adequados deste elemento apenas para bovinos de corte em crescimento e terminação. Os níveis de Mg plasmáticos dos bovinos foram normais nas duas épocas do ano. Nas cinzas dos ossos das costelas os teores de Mg foram baixos, variando de 0,32% a 0,44% nas vacas em lactação e de 0,28% a 0,47% nos bovinos jovens.

Operational Load Monitoring of a Composite Panel Using Artificial Neural Networks

Operational Load Monitoring consists of the real-time reading and recording of the number and level of strains and stresses during load cycles withstood by a structure in its normal operating environment, in order to make more reliable predictions about its remaining lifetime in service. This is particularly important in aeronautical and aerospace industries, where it is very relevant to extend the components useful life without compromising flight safety. Sensors, like strain gauges, should be mounted on points of the structure where highest strains or stresses are expected. However, if the structure in its normal operating environment is subjected to variable exciting forces acting in different points over time, the number of places where data will have be acquired largely increases. The main idea presented in this paper is that instead of mounting a high number of sensors, an artificial neural network can be trained on the base of finite element simulations in order to estimate the state of the structure in its most stressed points based on data acquired just by a few sensors. The model should also be validated using experimental data to confirm proper predictions of the artificial neural network. An example with an omega-stiffened composite structural panel (a typical part used in aerospace applications) is provided. Artificial neural network was trained using a high-accuracy finite element model of the structure to process data from six strain gauges and return information about the state of the panel during different load cases. The trained neural network was tested in an experimental stand and the measurements confirmed the usefulness of presented approach

Networked embedded systems for active flow control in aircraft

Aerodynamic drag is known to be one of the factors contributing more to increased aircraft fuel consumption. The primary source of skin friction drag during flight is the boundary layer separation. This is the layer of air moving smoothly in the immediate vicinity of the aircraft. In this paper we discuss a cyber-physical system approach able of performing an efficient suppression of the turbulent flow by using a dense sensing deployment to detect the low pressure region and a similarly dense deployment of actuators to manage the turbulent flow. With this concept, only the actuators in the vicinity of a separation layer are activated, minimizing power consumption and also the induced drag