Laser-assisted deposition of thin films from photoexcited vapour phases

Laser-assisted chemical vapour deposition (LCVD) has been extensively studied in the last two decades. A vast range of applications encompass various areas such as microelectronics, micromechanics, microelectromechanics and integrated optics, and a variety of metals, semiconductors and insulators have been grown by LCVD. In this article, we review briefly the LCVD process and present two case studies of thin film deposition related to laser thermal excitation (e.g., boron carbide) and non-thermal excitation (e.g., CrO(2)) of the gas phase.

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.

Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach

In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. (C) 2012 Elsevier Ltd. All rights reserved.

Comparison of deposited surface area of airborne ultrafine particles generated from two welding processes

This article describes work performed on the assessment of the levels of airborne ultrafine particles emitted in two welding processes metal-active gas (MAG) of carbon steel and friction-stir welding (FSW) of aluminium in terms of deposited area in alveolar tract of the lung using a nanoparticle surface area monitor analyser. The obtained results showed the dependence from process parameters on emitted ultrafine particles and clearly demonstrated the presence of ultrafine particles, when compared with background levels. The obtained results showed that the process that results on the lower levels of alveolar-deposited surface area is FSW, unlike MAG. Nevertheless, all the tested processes resulted in important doses of ultrafine particles that are to be deposited in the human lung of exposed workers.

Determination of airborne nanoparticles from welding operations

The aim of this study is to assess the levels of airborne ultrafine particles emitted in welding processes (tungsten inert gas [TIG], metal active gas [MAG] of carbon steel, and friction stir welding [FSW] of aluminum) in terms of deposited area in pulmonary alveolar tract using a nanoparticle surface area monitor (NSAM) analyzer. The obtained results showed the dependence of process parameters on emitted ultrafine particles and demonstrated the presence of ultrafine particles compared to background levels. Data indicated that the process that resulted in the lowest levels of alveolar deposited surface area (ADSA) was FSW, followed by TIG and MAG. However, all tested processes resulted in significant concentrations of ultrafine particles being deposited in humans lungs of exposed workers.

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.

Hybrid Wavelet-PSO-ANFIS Approach for Short-Term Electricity Prices Forecasting

A novel hybrid approach, combining wavelet transform, particle swarm optimization, and adaptive-network-based fuzzy inference system, is proposed in this paper for short-term electricity prices forecasting in a competitive market. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Finally, conclusions are duly drawn.

Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

A hybrid intelligent system for distributed dynamic scheduling

This chapter addresses the resolution of dynamic scheduling by means of meta-heuristic and multi-agent systems. Scheduling is an important aspect of automation in manufacturing systems. Several contributions have been proposed, but the problem is far from being solved satisfactorily, especially if scheduling concerns real world applications. The proposed multi-agent scheduling system assumes the existence of several resource agents (which are decision-making entities based on meta-heuristics) distributed inside the manufacturing system that interact with other agents in order to obtain optimal or near-optimal global performances.

Scheduling maintenance activities of electric power transmission networks using an hybrid constraint method

In this paper we present a Constraint Logic Programming (CLP) based model, and hybrid solving method for the Scheduling of Maintenance Activities in the Power Transmission Network. The model distinguishes from others not only because of its completeness but also by the way it models and solves the Electric Constraints. Specifically we present a efficient filtering algorithm for the Electrical Constraints. Furthermore, the solving method improves the pure CLP methods efficiency by integrating a type of Local Search technique with CLP. To test the approach we compare the method results with another method using a 24 bus network, which considerers 42 tasks and 24 maintenance periods.

Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems

This paper proposes a new methodology to reduce the probability of occurring states that cause load curtailment, while minimizing the involved costs to achieve that reduction. The methodology is supported by a hybrid method based on Fuzzy Set and Monte Carlo Simulation to catch both randomness and fuzziness of component outage parameters of transmission power system. The novelty of this research work consists in proposing two fundamentals approaches: 1) a global steady approach which deals with building the model of a faulted transmission power system aiming at minimizing the unavailability corresponding to each faulted component in transmission power system. This, results in the minimal global cost investment for the faulted components in a system states sample of the transmission network; 2) a dynamic iterative approach that checks individually the investment’s effect on the transmission network. A case study using the Reliability Test System (RTS) 1996 IEEE 24 Buses is presented to illustrate in detail the application of the proposed methodology.

Hybrid fuzzy Monte Carlo and logic programming model for distribution network reconfiguration in the presence of outages

This paper presents a methodology for distribution networks reconfiguration in outage presence in order to choose the reconfiguration that presents the lower power losses. The methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. Once obtained the system states by Monte Carlo simulation, a logical programming algorithm is applied to get all possible reconfigurations for every system state. In order to evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation a distribution power flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology to a practical case, the paper includes a case study that considers a real distribution network.

A hybrid recommendation approach for a tourism system

Many current e-commerce systems provide personalization when their content is shown to users. In this sense, recommender systems make personalized suggestions and provide information of items available in the system. Nowadays, there is a vast amount of methods, including data mining techniques that can be employed for personalization in recommender systems. However, these methods are still quite vulnerable to some limitations and shortcomings related to recommender environment. In order to deal with some of them, in this work we implement a recommendation methodology in a recommender system for tourism, where classification based on association is applied. Classification based on association methods, also named associative classification methods, consist of an alternative data mining technique, which combines concepts from classification and association in order to allow association rules to be employed in a prediction context. The proposed methodology was evaluated in some case studies, where we could verify that it is able to shorten limitations presented in recommender systems and to enhance recommendation quality.