Agrégation de tensioactifs anioniques à une interface solide-aqueux induite par l'oxydation d'une monocouche auto-assemblée de ferrocenylalkanethiolates

L'oxydoréduction des monocouches auto-assemblées («Self-assembled monolayers ou SAMs) de ferrocenyldodecanethiolates sur une surface d'or (Fc(CH2)12SAu) dans des solutions aqueuses de n-alkyle sulfate de sodium (6, 8, 10 et 12 atomes de carbone) est étudiée par spectroscopie de résonance des plasmons de surface («Surface Plasmons Resonance ou SPR) couplée avec de la voltampérométrie cyclique (VC). La technique SPR est utilisée pour suivre en temps réel l'adsorption des tensioactifs en fonction du potentiel appliqué. Elle permet de quantifier l'épaisseur et le recouvrement des molécules adsorbées pour déterminer l'organisation des tensioactifs anioniques sur la SAM. La VC est utilisée afin de caractériser l'oxydation du groupement ferrocène en présence des n-alkyle sulfate de sodium qui s'associent à la SAM grâce à l'appariement entre le ferrocénium et le groupement sulfate. Des mélanges binaires d'alkylesulfates de différentes compositions sont utilisés dans le but de déterminer l'organisation induite par une réaction d'oxydoréduction. L'effet de la longueur de la chaîne d'hydrocarbures sur la quantité de tensioactifs anioniques adsorbés ainsi que les affinités relatives d'appariement des anions alkyle sulfate aux ferrocéniums sont rapportés dans ce mémoire. Ces surfaces électrosensibles permettront la détection de molécules amphiphiles et la compréhension du comportement de mélanges binaires de tensioactifs. Ainsi, ces travaux apporteront une avancée sur la modulation électrochimique de l'organisation de matériaux sur des substrats solides basée sur l'appariement d'ions.

Singlet Oxygen in Microporous Silica Xerogel:Quantum Yield and Oxidation at the Gas–Solid Interface

The quantum yields of singlet oxygen production and lifetimes at the gas–solid interface in silica gel material are determined. Different photosensitizers (PS) are encapsulated in parallelepipedic xerogel monoliths (PS-SG). PS were chosen according to their known photooxidation properties: 9,10-dicyanoanthracene (DCA), 9,10-anthraquinone (ANT), and a benzophenone derivative, 4-benzoyl benzoic acid (4BB). These experiments are mainly based on time-resolved 1O2 phosphorescence detection, and the obtained FD and tD values are compared with those of a reference sensitizer for production, 1H-phenalen-1- one (PN), included in the same xerogel. The trend between their ability to oxidize organic pollutants in the gas phase and their efficiency for production is investigated through photooxidation experiments of a test pollutant dimethylsulfide (DMS). The FD value is high for DCA-SG relative to the PN reference, whereas it is slightly lower for 4BB-SG and for ANT-SG. FD is related to the production of sulfoxide and sulfone as the main oxidation products for DMS photosensitized oxidation. Additional mechanisms, leading to C!S bond cleaveage, appear to mainly occur for the less efficient singlet oxygen sensitizers 4BB-SG and ANTSG.

Analysis and Design of an Adaptive Polynomial Predistorter with the Loop Delay Estimator

Most adaptive linearization circuits for the nonlinear amplifier have a feedback loop that returns the output signal oj'tne eunplifier to the lineurizer. The loop delay of the linearizer most be controlled precisely so that the convergence of the linearizer should be assured lot this Letter a delay control circuit is presented. It is a delay lock loop (ULL) with it modified early-lute gate and can he easily applied to a DSP implementation. The proposed DLL circuit is applied to an adaptive linearizer with the use of a polynomial predistorter, and the simulalion for a 16-QAM signal is performed. The simulation results show that the proposed DLL eliminates the delay between the reference input signal and the delayed feedback signal of the linearizing circuit perfectly, so that the predistorter polynomial coefficients converge into the optimum value and a high degree of linearization is achieved

Monte Carlo simulation of interface alloying

An Ising-like model, with interactions ranging up to next-nearest-neighbor pairs, is used to simulate the process of interface alloying. Interactions are chosen to stabilize an intermediate "antiferromagnetic" ordered structure. The dynamics proceeds exclusively by atom-vacancy exchanges. In order to characterize the process, the time evolution of the width of the intermediate ordered region and the diffusion length is studied. Both lengths are found to follow a power-law evolution with exponents depending on the characteristic features of the model.

Energy Management in Wireless Sensor Networks: A Crosslayer,Channel Adaptive Approach Towards Performance Optimization

The proliferation of wireless sensor networks in a large spectrum of applications had been spurered by the rapid advances in MEMS(micro-electro mechanical systems )based sensor technology coupled with low power,Low cost digital signal processors and radio frequency circuits.A sensor network is composed of thousands of low cost and portable devices bearing large sensing computing and wireless communication capabilities. This large collection of tiny sensors can form a robust data computing and communication distributed system for automated information gathering and distributed sensing.The main attractive feature is that such a sensor network can be deployed in remote areas.Since the sensor node is battery powered,all the sensor nodes should collaborate together to form a fault tolerant network so as toprovide an efficient utilization of precious network resources like wireless channel,memory and battery capacity.The most crucial constraint is the energy consumption which has become the prime challenge for the design of long lived sensor nodes.

Freezing of 4He and its liquid-solid interface from density functional theory

We show that, at high densities, fully variational solutions of solidlike types can be obtained from a density functional formalism originally designed for liquid 4He . Motivated by this finding, we propose an extension of the method that accurately describes the solid phase and the freezing transition of liquid 4He at zero temperature. The density profile of the interface between liquid and the (0001) surface of the 4He crystal is also investigated, and its surface energy evaluated. The interfacial tension is found to be in semiquantitative agreement with experiments and with other microscopic calculations. This opens the possibility to use unbiased density functional (DF) methods to study highly nonhomogeneous systems, like 4He interacting with strongly attractive impurities and/or substrates, or the nucleation of the solid phase in the metastable liquid.

Speech sample estimation from composite zerocrossings and encoding via adaptive switching of transforms

This thesis investigates the potential use of zerocrossing information for speech sample estimation. It provides 21 new method tn) estimate speech samples using composite zerocrossings. A simple linear interpolation technique is developed for this purpose. By using this method the A/D converter can be avoided in a speech coder. The newly proposed zerocrossing sampling theory is supported with results of computer simulations using real speech data. The thesis also presents two methods for voiced/ unvoiced classification. One of these methods is based on a distance measure which is a function of short time zerocrossing rate and short time energy of the signal. The other one is based on the attractor dimension and entropy of the signal. Among these two methods the first one is simple and reguires only very few computations compared to the other. This method is used imtea later chapter to design an enhanced Adaptive Transform Coder. The later part of the thesis addresses a few problems in Adaptive Transform Coding and presents an improved ATC. Transform coefficient with maximum amplitude is considered as ‘side information’. This. enables more accurate tfiiz assignment enui step—size computation. A new bit reassignment scheme is also introduced in this work. Finally, sum ATC which applies switching between luiscrete Cosine Transform and Discrete Walsh-Hadamard Transform for voiced and unvoiced speech segments respectively is presented. Simulation results are provided to show the improved performance of the coder

MgO/Ag(001) interface structure and STM images from first principles

The interface of MgO/Ag(001) has been studied with density functional theory applied to slabs. We have found that regular MgO films show a small adhesion to the silver substrate, the binding can be increased in off-stoichiometric regimes, either by the presence of O vacancies at the oxide film or by a small excess of O atoms at the interface between the ceramic to the metal. By means of theoretical methods, the scanning tunneling microscopy signatures of these films is also analyzed in some detail. For defect free deposits containing 1 or 2 ML and at low voltages, tunnelling takes place from the surface Ag substrate, and at large positive voltages Mg atoms are imaged. If defects, oxygen vacancies, are present on the surface of the oxide they introduce much easier channels for tunnelling resulting in big protrusions and controlling the shape of the image, the extra O stored at the interface can also be detected for very thin films.

Modified Block Adaptive Predictive Coder For Speech Processing

This thesis investigated the potential use of Linear Predictive Coding in speech communication applications. A Modified Block Adaptive Predictive Coder is developed, which reduces the computational burden and complexity without sacrificing the speech quality, as compared to the conventional adaptive predictive coding (APC) system. For this, changes in the evaluation methods have been evolved. This method is as different from the usual APC system in that the difference between the true and the predicted value is not transmitted. This allows the replacement of the high order predictor in the transmitter section of a predictive coding system, by a simple delay unit, which makes the transmitter quite simple. Also, the block length used in the processing of the speech signal is adjusted relative to the pitch period of the signal being processed rather than choosing a constant length as hitherto done by other researchers. The efficiency of the newly proposed coder has been supported with results of computer simulation using real speech data. Three methods for voiced/unvoiced/silent/transition classification have been presented. The first one is based on energy, zerocrossing rate and the periodicity of the waveform. The second method uses normalised correlation coefficient as the main parameter, while the third method utilizes a pitch-dependent correlation factor. The third algorithm which gives the minimum error probability has been chosen in a later chapter to design the modified coder The thesis also presents a comparazive study beh-cm the autocorrelation and the covariance methods used in the evaluaiicn of the predictor parameters. It has been proved that the azztocorrelation method is superior to the covariance method with respect to the filter stabf-it)‘ and also in an SNR sense, though the increase in gain is only small. The Modified Block Adaptive Coder applies a switching from pitch precitzion to spectrum prediction when the speech segment changes from a voiced or transition region to an unvoiced region. The experiments cont;-:ted in coding, transmission and simulation, used speech samples from .\£=_‘ajr2_1a:r1 and English phrases. Proposal for a speaker reecgnifion syste: and a phoneme identification system has also been outlized towards the end of the thesis.

An adaptive cluster based routing scheme for mobile wireless sensor networks

Clustering schemes improve energy efficiency of wireless sensor networks. The inclusion of mobility as a new criterion for the cluster creation and maintenance adds new challenges for these clustering schemes. Cluster formation and cluster head selection is done on a stochastic basis for most of the algorithms. In this paper we introduce a cluster formation and routing algorithm based on a mobility factor. The proposed algorithm is compared with LEACH-M protocol based on metrics viz. number of cluster head transitions, average residual energy, number of alive nodes and number of messages lost

Short-Term Load Forecast Of A Low Loadfactor Power System For Optimization Of Merit Order Dispatch Using Adaptive Learning Algorithm

Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year

Image Denoising Using Sure-Based Adaptive Thresholding In Directionlet Domain

The standard separable two dimensional wavelet transform has achieved a great success in image denoising applications due to its sparse representation of images. However it fails to capture efficiently the anisotropic geometric structures like edges and contours in images as they intersect too many wavelet basis functions and lead to a non-sparse representation. In this paper a novel de-noising scheme based on multi directional and anisotropic wavelet transform called directionlet is presented. The image denoising in wavelet domain has been extended to the directionlet domain to make the image features to concentrate on fewer coefficients so that more effective thresholding is possible. The image is first segmented and the dominant direction of each segment is identified to make a directional map. Then according to the directional map, the directionlet transform is taken along the dominant direction of the selected segment. The decomposed images with directional energy are used for scale dependent subband adaptive optimal threshold computation based on SURE risk. This threshold is then applied to the sub-bands except the LLL subband. The threshold corrected sub-bands with the unprocessed first sub-band (LLL) are given as input to the inverse directionlet algorithm for getting the de-noised image. Experimental results show that the proposed method outperforms the standard wavelet-based denoising methods in terms of numeric and visual quality

Influence of Interface Surface Geometries In The Tensile Characteristics Of Friction Welded Joints From Aluminium Alloys

Friction welding is a solid state joining process that produces coalescence in materials, using the heat developed between surfaces through a combination of mechanical induced rubbing motion and applied load. In rotary friction welding technique heat is generated by the conversion of mechanical energy into thermal energy at the interface of the work pieces during rotation under pressure. Traditionally friction welding is carried out on a dedicated machine because of its adaptability to mass production. In the present work, steps were made to modify a conventional lathe to rotary friction welding set up to obtain friction welding with different interface surface geometries at two different speeds and to carry out tensile characteristic studies. The surface geometries welded include flat-flat, flat-tapered, tapered-tapered, concave-convex and convex-convex. A comparison of maximum load, breaking load and percentage elongation of different welded geometries has been realized through this project. The maximum load and breaking load were found to be highest for weld formed between rotating flat and stationary tapered at 500RPM and the values were 19.219kN and 14.28 kN respectively. The percentage elongation was found to be highest for weld formed between rotating flat and stationary flat at 500RPM and the value was 21.4%. Hence from the studies it is cleared that process parameter like “interfacing surface geometries” of weld specimens have strong influence on tensile characteristics of friction welded joints

Development of Directionally Adaptive Techniques for Single Image Super-Resolution

Super Resolution problem is an inverse problem and refers to the process of producing a High resolution (HR) image, making use of one or more Low Resolution (LR) observations. It includes up sampling the image, thereby, increasing the maximum spatial frequency and removing degradations that arise during the image capture namely aliasing and blurring. The work presented in this thesis is based on learning based single image super-resolution. In learning based super-resolution algorithms, a training set or database of available HR images are used to construct the HR image of an image captured using a LR camera. In the training set, images are stored as patches or coefficients of feature representations like wavelet transform, DCT, etc. Single frame image super-resolution can be used in applications where database of HR images are available. The advantage of this method is that by skilfully creating a database of suitable training images, one can improve the quality of the super-resolved image. A new super resolution method based on wavelet transform is developed and it is better than conventional wavelet transform based methods and standard interpolation methods. Super-resolution techniques based on skewed anisotropic transform called directionlet transform are developed to convert a low resolution image which is of small size into a high resolution image of large size. Super-resolution algorithm not only increases the size, but also reduces the degradations occurred during the process of capturing image. This method outperforms the standard interpolation methods and the wavelet methods, both visually and in terms of SNR values. Artifacts like aliasing and ringing effects are also eliminated in this method. The super-resolution methods are implemented using, both critically sampled and over sampled directionlets. The conventional directionlet transform is computationally complex. Hence lifting scheme is used for implementation of directionlets. The new single image super-resolution method based on lifting scheme reduces computational complexity and thereby reduces computation time. The quality of the super resolved image depends on the type of wavelet basis used. A study is conducted to find the effect of different wavelets on the single image super-resolution method. Finally this new method implemented on grey images is extended to colour images and noisy images