Laser scanned photodiodes (LSPs) for image sensing

An optimized ZnO:Al/a-pin SixC1-x:H/Al configuration for the laser scanned photodiode (LSP) imaging detector is proposed and the read-out parameters improved. The effect of the sensing element structure, cell configuration and light source flux are investigated and correlated with the sensor output characteristics. Data reveals that for sensors with wide band gap doped layers an increase on the image signal optimized to the blue is achieved with a dynamic range of two orders of magnitude, a responsivity of 6 mA W-1 and a sensitivity of 17 muW cm(-2) at 530 nm. The main output characteristics such as image responsivity, resolution, linearity and dynamic range were analyzed under reverse, forward and short circuit modes. The results show that the sensor performance can be optimized in short circuit mode. A trade-off between the scan time and the required resolution is needed since the spot size limits the resolution due to the cross-talk between dark and illuminated regions leading to blurring effects.

Optical confinement and colour separation in a double colour laser scanned photodiode (D/CLSP)

Large area n-i-p-n-i-p a-SiC:H heterostructures are used as sensing element in a double colour laser scanned photodiode image sensor (D/CLSP). This work aims to clarify possible improvements, physical limits and performance of CLSP image sensor when used as non-pixel image reader. Here, the image capture device and the scanning reader are optimized and the effects of the sensor structure on the output characteristics discussed. The role of the design of the sensing element, the doped layer composition and thickness, the read-out parameters (applied voltage and scanner frequency) on the image acquisition and the colour detection process are analysed. A physical model is presented and supported by a numerical simulation of the output characteristics of the sensor.

Optical confinement and colour separation in a double colour laser scanned photodiode (D/CLSP)

Large area n-i-p-n-i-p a-SiC:H heterostructures are used as sensing element in a Double Color Laser Scanned Photodiode image sensor (D/CLSP). This work aims to clarify possible improvements, physical limits and performance of CLSP image sensor when used as non-pixel image reader. Here, the image capture device and the scanning reader are optimized and the effects of the sensor structure on the output characteristics discussed. The role of the design of the sensing element, the doped layer composition and thickness, the read-out parameters (applied voltage and scanner frequency) on the image acquisition and the color detection process are analyzed. A physical model is presented and supported by a numerical simulation of the output characteristics of the sensor.

Cr2O3 thin films grown at room temperature by low pressure laser chemical vapour deposition

Chromia (Cr2O3) has been extensively explored for the purpose of developing widespread industrial applications, owing to the convergence of a variety of mechanical, physical and chemical properties in one single oxide material. Various methods have been used for large area synthesis of Cr2O3 films. However, for selective area growth and growth on thermally sensitive materials, laser-assisted chemical vapour deposition (LCVD) can be applied advantageously. Here we report on the growth of single layers of pure Cr2O3 onto sapphire substrates at room temperature by low pressure photolytic LCVD, using UV laser radiation and Cr(CO)(6) as chromium precursor. The feasibility of the LCVD technique to access selective area deposition of chromia thin films is demonstrated. Best results were obtained for a laser fluence of 120 mJ cm(-2) and a partial pressure ratio of O-2 to Cr(CO)(6) of 1.0. Samples grown with these experimental parameters are polycrystalline and their microstructure is characterised by a high density of particles whose size follows a lognormal distribution. Deposition rates of 0.1 nm s(-1) and mean particle sizes of 1.85 mu m were measured for these films. (C) 2011 Elsevier B.V. All rights reserved.

KrF pulsed laser deposition of chromium oxide thin films from Cr8O21 targets

Chromium oxides, CrxOy, are of great interest due to the wide variety of their technological applications. Among them, CrO2 has been extensively investigated in recent years because it is an attractive compound for use in spintronic heterostructures. However, its synthesis at low temperatures has been a difficult task due to the metastable nature of this oxide. This is indeed essential to ensure interface quality and the ability to coat thermal-sensitive materials such as those envisaged in spintronic devices. Pulsed Laser Deposition (PLD) is a technique that has the potential to meet the requirements stated above. In this work, we describe our efforts to grow chromium oxide thin films by PLD from Cr8O21 targets, using a KrF excimer laser. The as-deposited films were investigated by X-ray diffraction and Rutherford backscattering spectrometry. Structural and chemical composition studies showed that the films consist of a mixture of amorphous chromium oxides exhibiting different stoichiometries depending on the processing parameters, where nanocrystals of mainly Cr2O3 are dispersed. The analyses do not exclude the possibility of co-deposition of Cr2O3 and a low fraction of CrO2.

Femtosecond laser ablation of dentin

The surface morphology, structure and composition of human dentin treated with a femtosecond infrared laser (pulse duration 500 fs, wavelength 1030 nm, fluences ranging from 1 to 3 J cm(-2)) was studied by scanning electron microscopy, x-ray diffraction, x-ray photoelectron spectroscopy and Fourier transform infrared spectroscopy. The average dentin ablation threshold under these conditions was 0.6 +/- 0.2 J cm(-2) and the ablation rate achieved in the range 1 to 2 mu m/pulse for an average fluence of 3 J cm(-2). The ablation surfaces present an irregular and rugged appearance, with no significant traces of melting, deformation, cracking or carbonization. The smear layer was entirely removed by the laser treatment. For fluences only slightly higher than the ablation threshold the morphology of the laser-treated surfaces was very similar to the dentin fracture surfaces and the dentinal tubules remained open. For higher fluences, the surface was more porous and the dentin structure was partially concealed by ablation debris and a few resolidified droplets. Independently on the laser processing parameters and laser processing method used no sub-superficial cracking was observed. The dentin constitution and chemical composition was not significantly modified by the laser treatment in the processing parameter range used. In particular, the organic matter is not preferentially removed from the surface and no traces of high temperature phosphates, such as the beta-tricalcium phosphate, were observed. The achieved results are compatible with an electrostatic ablation mechanism. In conclusion, the high beam quality and short pulse duration of the ultrafast laser used should allow the accurate preparation of cavities, with negligible damage of the underlying material.

KrP laser CVD of chromium oxide by photodissociation of Cr(CO)(6)

This work reports on the synthesis of chromium oxide thin films prepared by photodissociation of Cr(CO)(6) in an oxidizing atmosphere, using a pulsed UV laser (KrF, lambda = 248 nm). The experimental conditions, which should enable the synthesis of CrO2, are discussed and results on the deposition of CrxOy films on Al2O3 (0001) substrates are presented.

Morphological and structural characterization of CrO2/Cr2O3 films grown by laser-CVD

This work reports on the synthesis of chromium (III, IV) oxides films by KrF laser-assisted CVD. Films were deposited onto sapphire substrates at room temperature by the photodissociation of Cr(CO)(6) in dynamic atmospheres containing oxygen and argon. A study of the processing parameters has shown that partial pressure ratio Of O-2 to Cr(CO)(6) and laser fluence are the prominent parameters that have to be accurately controlled in order to co-deposit both the crystalline oxide phases. Films consistent with such a two-phase system were synthesised for a laser fluence of 75 mJ cm(-2) and a partial pressure ratio of about 1. (c) 2005 Elsevier B.V. All rights reserved.

Organization knowledge management change from a complex adaptive systems perpective with ability for ambidexeterity

We are working on the confluence of knowledge management, organizational memory and emergent knowledge with the lens of complex adaptive systems. In order to be fundamentally sustainable organizations search for an adaptive need for managing ambidexterity of day-to-day work and innovation. An organization is an entity of a systemic nature, composed of groups of people who interact to achieve common objectives, making it necessary to capture, store and share interactions knowledge with the organization, this knowledge can be generated in intra-organizational or inter-organizational level. The organizations have organizational memory of knowledge of supported on the Information technology and systems. Each organization, especially in times of uncertainty and radical changes, to meet the demands of the environment, needs timely and sized knowledge on the basis of tacit and explicit. This sizing is a learning process resulting from the interaction that emerges from the relationship between the tacit and explicit knowledge and which we are framing within an approach of Complex Adaptive Systems. The use of complex adaptive systems for building the emerging interdependent relationship, will produce emergent knowledge that will improve the organization unique developing.

Ageing effects on the wettability behavior of laser textured silicon

In the present work we investigate the ageing of acid cleaned femtosecond laser textured < 100 > silicon surfaces. Changes in the surface structure and chemistry were analysed by Rutherford backscattering spectrometry (RBS) and X-ray photoelectron spectroscopy (XPS), in order to explain the variation with time of the water contact angles of the laser textured surfaces. It is shown that highly hydrophobic silicon surfaces are obtained immediately after laser texturing and cleaning with acid solutions (water contact angle >120 degrees). However these surfaces are not stable and ageing leads to a decrease of the water contact angle which reaches a value of 80 degrees. XPS analysis of the surfaces shows that the growth of the native oxide layer is most probably responsible for this behavior. (C) 2010 Elsevier B.V. All rights reserved.

Application of adaptive neuro-fuzzy inference for wind power short-term forecasting

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. In this paper, an adaptive neuro-fuzzy inference approach is proposed for short-term wind power forecasting. Results from a real-world case study are presented. A thorough comparison is carried out, taking into account the results obtained with other approaches. Numerical results are presented and conclusions are duly drawn. (C) 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Adaptive tool for automatic data collection of real electricity markets

The study of electricity markets operation has been gaining an increasing importance in last years, as result of the new challenges that the electricity markets restructuring produced. This restructuring increased the competitiveness of the market, but with it its complexity. The growing complexity and unpredictability of the market’s evolution consequently increases the decision making difficulty. Therefore, the intervenient entities are forced to rethink their behaviour and market strategies. Currently, lots of information concerning electricity markets is available. These data, concerning innumerous regards of electricity markets operation, is accessible free of charge, and it is essential for understanding and suitably modelling electricity markets. This paper proposes a tool which is able to handle, store and dynamically update data. The development of the proposed tool is expected to be of great importance to improve the comprehension of electricity markets and the interactions among the involved entities.

Adaptive learning in multiagent systems: a forecasting methodology based on error analysis

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simu-lator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.

Multiagent system for adaptive strategy formulation in electricity markets

Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is multiagent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal.

Cost dependent strategy for electricity markets bidding based on adaptive reinforcement learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM provides several dynamic strategies for agents’ behavior. This paper presents a method that aims to provide market players with strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible bids. These bids are defined accordingly to the cost function that each producer presents.