900 resultados para POLYELECTROLYTE MULTILAYER
Resumo:
Layer-by-layer (LBL) films of nickel tetrasulfonated phthalocyanine (NiTsPc) alternated with poly(allylamine hydrochloride) (PAH) have been prepared, whose surface charge has been evaluated using surface potential measurements. From adsorption kinetics results, we obtained the immersion time of similar to 40 s, which was used to assemble layers of NiTsPc. The effect of gold (Au) and aluminum (Al) electrodes on the charge behavior was examined. We found that the surface potential (i.e. surface charge) was inverted each time a layer of PAH was alternated with another of NiTsPc molecules for the two types of electrodes, which was attributed to charge overcompensation between positive charges of PAH molecules, and negative charges from NiTsPc molecules. (C) 2009 Elsevier B.V. All rights reserved.
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The electrostatic layer-by-layer technique has been exploited as an useful strategy for fabrication of nanostructured thin films, in which specific properties can be controlled at the molecular level. Ferrofluids consist of a colloidal suspension of magnetic grains (with only a few nanometers of diameter) with present interesting physical properties and applications, ranging from telecommunication to drug delivery systems. In this article, we developed a new strategy to manipulate ferrofluids upon their immobilization in nanostructured layered films in conjunction with conventional polyelectrolytes using the layer-by-layer technique. We investigated the morphological, optical, and magnetic properties of the immobilized ferrofluid as a function of number of bilayers presented in the films. Ferrofluid/polyelectrolyte multilayers homogeneously covered the substrates surface, and the magnetic and optical properties of films exhibited a linear dependence on the number of bilayers adsorbed.
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The adsorption behavior of several amphiphilic polyelectrolytes of poly(maleic anhydride-alt-styrene) functionalized with naphthyl and phenyl groups, onto amino-terminated silicon wafer has been studied by means of null- ellipsometry, atomic force microscopy (AFM) and contact angle measurements. The maximum of adsorption, Gamma(plateau), varies with the ionic strength, the polyelectrolyte structure and the chain length. Values of Gamma(plateau) obtained at low and high ionic strengths indicate that the adsorption follows the ""screening-reduced adsorption"" regime. Large aggregates were detected in solution by means of dynamic light scattering and fluorescence measurements. However. AFM indicated the formation of smooth layers and the absence of aggregates. A model based on a two-step adsorption behavior was proposed. In the first one, isolated chains in equilibrium with the aggregates in solution adsorbed onto amino-terminated surface. The adsorption is driven by electrostatic interaction between protonated surface and carboxylate groups. This first layer exposes naphtyl or phenyl groups to the solution. The second layer adsorption is now driven by hydrophobic interaction between surface and chains and exposes carboxylate groups to the medium, which repel the forthcoming chain by electrostatic repulsion. Upon drying some hydrophobic naphtyl or phenyl groups might be oriented to the air, as revealed by contact angle measurements. Such amphiphilic polyelectrolyte layers worked well for the building-up of multilayers with chitosan. (C) 2010 Elsevier Ltd. All rights reserved.
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The adsorption behavior of polycations at ionic strengths (1) ranging from 0.001 to 0.1 onto silicon wafers was studied by means of ellipsometry, contact angle measurements and atomic force microscopy (AFM). Polycations chosen were bromide salts of poly(4-vinylpyridine) N-alkyl quaternized with linear aliphatic chains of 2 and 5 carbon atoms, QPVP-C2 and QPVP-C5, respectively. Under 1 0.001 the reduction of screening effects led to low adsorbed amounts of QPVP-C2 or QPVP-C5 (1.0 +/- 0.1 mg/m(2)), arising from the adsorption of extended chains. Upon increasing l to 0.1, screening effects led to conformational changes of polyelectrolyte chains ill Solution and to higher adsorbed amount values (1.9 +/- 0.2 mg/m(2)). Advancing contact angle theta(a) measurements performed with water drops onto QPVP-C2 and QPVP-C5 adsorbed layers varied from (45 +/- 2)degrees to (50 +/- 5)degrees, evidencing the exposure of both hydrophobic alkyl groups and charged moieties. The adsorption of lysozyme (LYZ) molecules to QPVP-C5 layers was more pronounced than to QPVP-C2 films. Antimicrobial effect of LYZ bound to QPVP-C2 or QPVP-C5 layers or to Si wafers was evaluated with enzymatic assays using Micrococcus luteus as Substrates. The adsorption behavior of QPVP-C2 and QPVP-C5 at the water-air interface was studied by means Of surface tension measurements. Only QPVP-C5 was able to reduce water Surface tension. Mixtures of LYZ and QPVP-C5 were more efficient in reducing Surface tension than pure LYZ solution, evidencing co-adsorption at liquid-air interface. Moreover, antimicrobial action observed for mixtures of LYZ and QPVP-C5 was more pronounced than that measured for pure LYZ. Hydrophobic interaction between LYZ and QPVP-C5 ill Solution seems to drive the binding and to preserve LYZ secondary structure. (c) 2008 Elsevier Inc. All rights reserved.
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Thin films of MnO(2) nanoparticles were grown using the layer-by-layer method with poly (diallyldimetylammonium) as the intercalated layer. The film growth was followed by UV-vis, electrochemical quartz crystal microbalance (EQCM), and atomic force microscopy. Linear growth due to electrostatic immobilization of layers was observed up to 30 bilayers, but electrical connectivity was maintained only for 12 MnO(2)/PPDA bilayers. The electrochemical characterization of this film in 1-butyl-2,3-dimethyl-imidazolium (BMMI) bis(trifluoromethanesulfonyl)imide (TFSI) (BMMITFSI) with and without addition of a lithium salt indicated a higher electrochemical response of the nanostructured electrode in the lithium-containing electrolyte. On the basis of EQCM experiments, it was possible to confirm that the charge compensation process is achieved mainly by the TFSI anion at short times (<2 s) and by BMMI and lithium cations at longer times. The fact that large ions like TFSI and BMMI participate in the electroneutrality is attributed to the redox reaction that occurs at the superficial sites and to the high concentration of these species compared to that of lithium cations.
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The concern related to the environmental degradation and to the exhaustion of natural resources has induced the research on biodegradable materials obtained from renewable sources, which involves fundamental properties and general application. In this context, we have fabricated thin films of lignins, which were extracted from sugar cane bagasse via modified organosolv process using ethanol as organic solvent. The films were made using the vacuum thermal evaporation technique (PVD, physical vapor deposition) grown up to 120 nm. The main objective was to explore basic properties such as electrical and surface morphology and the sensing performance of these lignins as transducers. The PVD film growth was monitored via ultraviolet-visible (UV-vis) absorption spectroscopy and quartz crystal microbalance, revealing a linear relationship between absorbance and film thickness. The 120 nm lignin PVD film morphology presented small aggregates spread all over the film surface on the nanometer scale (atomic force microscopy, AFM) and homogeneous on the micrometer scale (optical microscopy). The PVD films were deposited onto Au interdigitated electrode (IDE) for both electrical characterization and sensing experiments. In the case of electrical characterization, current versus voltage (I vs V) dc measurements were carried out for the Au IDE coated with 120 nm lignin PVD film, leading to a conductivity of 3.6 x 10(-10) S/m. Using impedance spectroscopy, also for the Au IDE coated with the 120 nm lignin PVD film, dielectric constant of 8.0, tan delta of 3.9 x 10(-3)) and conductivity of 1.75 x 10(-9) S/m were calculated at 1 kHz. As a proof-of-principle, the application of these lignins as transducers in sensing devices was monitored by both impedance spectroscopy (capacitance vs frequency) and I versus time dc measurements toward aniline vapor (saturated atmosphere). The electrical responses showed that the sensing units are sensible to aniline vapor with the process being reversible. AFM images conducted directly onto the sensing units (Au IDE coated with 120 nm lignin PVD film) before and after the sensing experiments showed a decrease in the PVD film roughness from 5.8 to 3.2 nm after exposing to aniline.
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This work investigates neural network models for predicting the trypanocidal activity of 28 quinone compounds. Artificial neural networks (ANN), such as multilayer perceptrons (MLP) and Kohonen models, were employed with the aim of modeling the nonlinear relationship between quantum and molecular descriptors and trypanocidal activity. The calculated descriptors and the principal components were used as input to train neural network models to verify the behavior of the nets. The best model for both network models (MLP and Kohonen) was obtained with four descriptors as input. The descriptors were T(5) (torsion angle), QTS1 (sum of absolute values of the atomic charges), VOLS2 (volume of the substituent at region B) and HOMO-1 (energy of the molecular orbital below HOMO). These descriptors provide information on the kind of interaction that occurs between the compounds and the biological receptor. Both neural network models used here can predict the trypanocidal activity of the quinone compounds with good agreement, with low errors in the testing set and a high correctness rate. Thanks to the nonlinear model obtained from the neural network models, we can conclude that electronic and structural properties are important factors in the interaction between quinone compounds that exhibit trypanocidal activity and their biological receptors. The final ANN models should be useful in the design of novel trypanocidal quinones having improved potency.
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A variety of substrates have been used for fabrication of microchips for DNA extraction, PCR amplification, and DNA fragment separation, including the more conventional glass and silicon as well as alternative polymer-based materials. Polyester represents one such polymer, and the laser-printing of toner onto polyester films has been shown to be effective for generating polyester-toner (PeT) microfluidic devices with channel depths on the order of tens of micrometers. Here, we describe a novel and simple process that allows for the production of multilayer, high aspect-ratio PeT microdevices with substantially larger channel depths. This innovative process utilizes a CO(2) laser to create the microchannel in polyester sheets containing a uniform layer of printed toner, and multilayer devices can easily be constructed by sandwiching the channel layer between uncoated cover sheets of polyester containing precut access holes. The process allows the fabrication of deep channels, with similar to 270 mu m, and we demonstrate the effectiveness of multilayer PeT microchips for dynamic solid phase extraction (dSPE) and PCR amplification. With the former, we found that (i) more than 65% of DNA from 0.6 mu L of blood was recovered, (ii) the resultant DNA was concentrated to greater than 3 ng/mu L., (which was better than other chip-based extraction methods), and (iii) the DNA recovered was compatible with downstream microchip-based PCR amplification. Illustrative of the compatibility of PeT microchips with the PCR process, the successful amplification of a 520 bp fragment of lambda-phage DNA in a conventional thermocycler is shown. The ability to handle the diverse chemistries associated with DNA purification and extraction is a testimony to the potential utility of PeT microchips beyond separations and presents a promising new disposable platform for genetic analysis that is low cost and easy to fabricate.
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Carboxylic acid groups in PAH/PAA-based multilayers bind silver cations by ion exchange with the acid protons. The aggregation and spatial distribution of the nanoparticles proved to be dependent oil the process used to reduce the silver acetate aqueous solution. The reducing method with ambient light formed larger nanoparticles with diameters ranging from 4-50 nm in comparison with the reduction method using UV light, which gave particles with diameters of 2-4 nm The high toughness of samples reduced by ambient light is a result of two population distributions of particle sizes caused by different mechanisms when compared with the UV light process. According to these phenomena, a judicious choice of the spectral source call be used as a way to control the type and size of silver nanoparticles formed on PEMs. Depending on the energy of the light source, the Ag nanoparticles present cubic and/or hexagonal crystallographic structures, as confirmed by XRD. Beyond the kinetically controlled process of UV photoinduced cluster formation, the annealing produced by UV light allowed a second mechanism to modify the growth rates, spatial distribution, and phases.
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Condition monitoring of wooden railway sleepers applications are generallycarried out by visual inspection and if necessary some impact acoustic examination iscarried out intuitively by skilled personnel. In this work, a pattern recognition solutionhas been proposed to automate the process for the achievement of robust results. Thestudy presents a comparison of several pattern recognition techniques together withvarious nonstationary feature extraction techniques for classification of impactacoustic emissions. Pattern classifiers such as multilayer perceptron, learning cectorquantization and gaussian mixture models, are combined with nonstationary featureextraction techniques such as Short Time Fourier Transform, Continuous WaveletTransform, Discrete Wavelet Transform and Wigner-Ville Distribution. Due to thepresence of several different feature extraction and classification technqies, datafusion has been investigated. Data fusion in the current case has mainly beeninvestigated on two levels, feature level and classifier level respectively. Fusion at thefeature level demonstrated best results with an overall accuracy of 82% whencompared to the human operator.
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This dissertation is focused on theoretical and experimental studies of optical properties of materials and multilayer structures composing liquid crystal displays (LCDs) and electrochromic (EC) devices. By applying spectroscopic ellipsometry, we have determined the optical constants of thin films of electrochromic tungsten oxide (WOx) and nickel oxide (NiOy), the films’ thickness and roughness. These films, which were obtained at spattering conditions possess high transmittance that is important for achieving good visibility and high contrast in an EC device. Another application of the general spectroscopic ellipsometry relates to the study of a photo-alignment layer of a mixture of azo-dyes SD-1 and SDA-2. We have found the optical constants of this mixture before and after illuminating it by polarized UV light. The results obtained confirm the diffusion model to explain the formation of the photo-induced order in azo-dye films. We have developed new techniques for fast characterization of twisted nematic LC cells in transmissive and reflective modes. Our techniques are based on the characteristics functions that we have introduced for determination of parameters of non-uniform birefringent media. These characteristic functions are found by simple procedures and can be utilised for simultaneous determination of retardation, its wavelength dispersion, and twist angle, as well as for solving associated optimization problems. Cholesteric LCD that possesses some unique properties, such as bistability and good selective scattering, however, has a disadvantage – relatively high driving voltage (tens of volts). The way we propose to reduce the driving voltage consists of applying a stack of thin (~1µm) LC layers. We have studied the ability of a layer of a surface stabilized ferroelectric liquid crystal coupled with several retardation plates for birefringent color generation. We have demonstrated that in order to accomplish good color characteristics and high brightness of the display, one or two retardation plates are sufficient.
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Objective: To develop a method for objective quantification of PD motor symptoms related to Off episodes and peak dose dyskinesias, using spiral data gathered by using a touch screen telemetry device. The aim was to objectively characterize predominant motor phenotypes (bradykinesia and dyskinesia), to help in automating the process of visual interpretation of movement anomalies in spirals as rated by movement disorder specialists. Background: A retrospective analysis was conducted on recordings from 65 patients with advanced idiopathic PD from nine different clinics in Sweden, recruited from January 2006 until August 2010. In addition to the patient group, 10 healthy elderly subjects were recruited. Upper limb movement data were collected using a touch screen telemetry device from home environments of the subjects. Measurements with the device were performed four times per day during week-long test periods. On each test occasion, the subjects were asked to trace pre-drawn Archimedean spirals, using the dominant hand. The pre-drawn spiral was shown on the screen of the device. The spiral test was repeated three times per test occasion and they were instructed to complete it within 10 seconds. The device had a sampling rate of 10Hz and measured both position and time-stamps (in milliseconds) of the pen tip. Methods: Four independent raters (FB, DH, AJ and DN) used a web interface that animated the spiral drawings and allowed them to observe different kinematic features during the drawing process and to rate task performance. Initially, a number of kinematic features were assessed including ‘impairment’, ‘speed’, ‘irregularity’ and ‘hesitation’ followed by marking the predominant motor phenotype on a 3-category scale: tremor, bradykinesia and/or choreatic dyskinesia. There were only 2 test occasions for which all the four raters either classified them as tremor or could not identify the motor phenotype. Therefore, the two main motor phenotype categories were bradykinesia and dyskinesia. ‘Impairment’ was rated on a scale from 0 (no impairment) to 10 (extremely severe) whereas ‘speed’, ‘irregularity’ and ‘hesitation’ were rated on a scale from 0 (normal) to 4 (extremely severe). The proposed data-driven method consisted of the following steps. Initially, 28 spatiotemporal features were extracted from the time series signals before being presented to a Multilayer Perceptron (MLP) classifier. The features were based on different kinematic quantities of spirals including radius, angle, speed and velocity with the aim of measuring the severity of involuntary symptoms and discriminate between PD-specific (bradykinesia) and/or treatment-induced symptoms (dyskinesia). A Principal Component Analysis was applied on the features to reduce their dimensions where 4 relevant principal components (PCs) were retained and used as inputs to the MLP classifier. Finally, the MLP classifier mapped these components to the corresponding visually assessed motor phenotype scores for automating the process of scoring the bradykinesia and dyskinesia in PD patients whilst they draw spirals using the touch screen device. For motor phenotype (bradykinesia vs. dyskinesia) classification, the stratified 10-fold cross validation technique was employed. Results: There were good agreements between the four raters when rating the individual kinematic features with intra-class correlation coefficient (ICC) of 0.88 for ‘impairment’, 0.74 for ‘speed’, 0.70 for ‘irregularity’, and moderate agreements when rating ‘hesitation’ with an ICC of 0.49. When assessing the two main motor phenotype categories (bradykinesia or dyskinesia) in animated spirals the agreements between the four raters ranged from fair to moderate. There were good correlations between mean ratings of the four raters on individual kinematic features and computed scores. The MLP classifier classified the motor phenotype that is bradykinesia or dyskinesia with an accuracy of 85% in relation to visual classifications of the four movement disorder specialists. The test-retest reliability of the four PCs across the three spiral test trials was good with Cronbach’s Alpha coefficients of 0.80, 0.82, 0.54 and 0.49, respectively. These results indicate that the computed scores are stable and consistent over time. Significant differences were found between the two groups (patients and healthy elderly subjects) in all the PCs, except for the PC3. Conclusions: The proposed method automatically assessed the severity of unwanted symptoms and could reasonably well discriminate between PD-specific and/or treatment-induced motor symptoms, in relation to visual assessments of movement disorder specialists. The objective assessments could provide a time-effect summary score that could be useful for improving decision-making during symptom evaluation of individualized treatment when the goal is to maximize functional On time for patients while minimizing their Off episodes and troublesome dyskinesias.
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The present thesis focuses on characterisation of microstructure and the resulting mechanical and tribological properties of CVD and PVD coatings used in metal cutting applications. These thin and hard coatings are designed to improve the tribological performance of cutting tools which in metal cutting operations may result in improved cutting performance, lower energy consumption, lower production costs and lower impact on the environment. In order to increase the understanding of the tribological behaviour of the coating systems a number of friction and wear tests have been performed and evaluated by post-test microscopy and surface analysis. Much of the work has focused on coating cohesive and adhesive strength, surface fatigue resistance, abrasive wear resistance and friction and wear behaviour under sliding contact and metal cutting conditions. The results show that the CVD deposition of accurate crystallographic phases, e.g. α-Al2O3 rather than κ-Al2O3, textures and multilayer structures can increase the wear resistance of Al2O3. However, the characteristics of the interfaces, e.g. topography as well as interfacial porosity, have a strong impact on coating adhesion and consequently on the resulting properties. Through the deposition of well designed bonding and template layer structures the above problems may be eliminated. Also, the presence of macro-particles in PVD coatings may have a significant impact on the interfacial adhesive strength, increasing the tendency to coating spalling and lowering the surface fatigue resistance, as well as increasing the friction in sliding contacts. Finally, the CVD-Al2O3 coating topography influences the contact conditions in sliding as well as in metal cutting. In summary, the work illuminates the importance of understanding the relationships between deposition process parameters, composition and microstructure, resulting properties and tribological performance of CVD and PVD coatings and how this knowledge can be used to develop the coating materials of tomorrow.
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A challenge for the clinical management of advanced Parkinson’s disease (PD) patients is the emergence of fluctuations in motor performance, which represents a significant source of disability during activities of daily living of the patients. There is a lack of objective measurement of treatment effects for in-clinic and at-home use that can provide an overview of the treatment response. The objective of this paper was to develop a method for objective quantification of advanced PD motor symptoms related to off episodes and peak dose dyskinesia, using spiral data gathered by a touch screen telemetry device. More specifically, the aim was to objectively characterize motor symptoms (bradykinesia and dyskinesia), to help in automating the process of visual interpretation of movement anomalies in spirals as rated by movement disorder specialists. Digitized upper limb movement data of 65 advanced PD patients and 10 healthy (HE) subjects were recorded as they performed spiral drawing tasks on a touch screen device in their home environment settings. Several spatiotemporal features were extracted from the time series and used as inputs to machine learning methods. The methods were validated against ratings on animated spirals scored by four movement disorder specialists who visually assessed a set of kinematic features and the motor symptom. The ability of the method to discriminate between PD patients and HE subjects and the test-retest reliability of the computed scores were also evaluated. Computed scores correlated well with mean visual ratings of individual kinematic features. The best performing classifier (Multilayer Perceptron) classified the motor symptom (bradykinesia or dyskinesia) with an accuracy of 84% and area under the receiver operating characteristics curve of 0.86 in relation to visual classifications of the raters. In addition, the method provided high discriminating power when distinguishing between PD patients and HE subjects as well as had good test-retest reliability. This study demonstrated the potential of using digital spiral analysis for objective quantification of PD-specific and/or treatment-induced motor symptoms.
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In a global economy, manufacturers mainly compete with cost efficiency of production, as the price of raw materials are similar worldwide. Heavy industry has two big issues to deal with. On the one hand there is lots of data which needs to be analyzed in an effective manner, and on the other hand making big improvements via investments in cooperate structure or new machinery is neither economically nor physically viable. Machine learning offers a promising way for manufacturers to address both these problems as they are in an excellent position to employ learning techniques with their massive resource of historical production data. However, choosing modelling a strategy in this setting is far from trivial and this is the objective of this article. The article investigates characteristics of the most popular classifiers used in industry today. Support Vector Machines, Multilayer Perceptron, Decision Trees, Random Forests, and the meta-algorithms Bagging and Boosting are mainly investigated in this work. Lessons from real-world implementations of these learners are also provided together with future directions when different learners are expected to perform well. The importance of feature selection and relevant selection methods in an industrial setting are further investigated. Performance metrics have also been discussed for the sake of completion.