Direct electrochemistry of the Desulfovibrio gigas aldehyde oxidoreductase

Eur. J. Biochem. 271, 1329–1338 (2004)

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

ECG Biometrics: A Template Selection Approach

Electrocardiography (ECG) biometrics is emerging as a viable biometric trait. Recent developments at the sensor level have shown the feasibility of performing signal acquisition at the fingers and hand palms, using one-lead sensor technology and dry electrodes. These new locations lead to ECG signals with lower signal to noise ratio and more prone to noise artifacts; the heart rate variability is another of the major challenges of this biometric trait. In this paper we propose a novel approach to ECG biometrics, with the purpose of reducing the computational complexity and increasing the robustness of the recognition process enabling the fusion of information across sessions. Our approach is based on clustering, grouping individual heartbeats based on their morphology. We study several methods to perform automatic template selection and account for variations observed in a person's biometric data. This approach allows the identification of different template groupings, taking into account the heart rate variability, and the removal of outliers due to noise artifacts. Experimental evaluation on real world data demonstrates the advantages of our approach.

Mechanical and tribological characterization of TiB2 thin films

Titanium Diboride (TiB2) presents high mechanical and physical properties. Some wear studies were also carried out in order to evaluate its tribological properties. One of the most popular wear tests for thin films is the ball-cratering configuration. This work was focused on the study of the tribological properties of TiB2 thin films using micro-abrasion tests and following the BS EN 1071-6: 2007 standard. Due to high hardness usually patented by these films, diamond was selected as abrasive on micro-abrasion tests. Micro-abrasion wear tests were performed under five different durations, using the same normal load, speed rotation and ball. Films were deposited by unbalanced magnetron sputtering Physical Vapour Deposition (PVD) technique using TiB2 targets. TiB2 films were characterized using different methods as Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDS), Atomic Force Microscopy (AFM), X-ray Diffraction (XRD), Electron Probe Micro-Analyser (EPMA), Ultra Micro Hardness and Scratch-test Analysis, allowing to confirm that TiB2 presents adequate mechanical and physical properties. Ratio between hardness (coating and abrasive particles), wear resistance and wear coefficient were studied, showing that TiB2 films shows excellent properties for tribological applications.

Lightweight amorphous silicon photovoltaic modules on flexible plastic substrate

Solar cells on lightweight and flexible substrates have advantages over glass-or wafer-based photovoltaic devices in both terrestrial and space applications. Here, we report on development of amorphous silicon thin film photovoltaic modules fabricated at maximum deposition temperature of 150 degrees C on 100 mu m thick polyethylene-naphtalate plastic films. Each module of 10 cm x 10 cm area consists of 72 a-Si:H n-i-p rectangular structures with transparent conducting oxide top electrodes with Al fingers and metal back electrodes deposited through the shadow masks. Individual structures are connected in series forming eight rows with connection ports provided for external blocking diodes. The design optimization and device performance analysis are performed using a developed SPICE model.

Analysis of the nano-surface of a modified glassy carbon electrode by pseudo phase plane method

This paper presents the Pseudo phase plane (PPP) method for detecting the existence of a nanofilm on the nitroazobenzene-modified glassy carbon electrode (NAB-GC) system. This modified electrode systems and nitroazobenze-nanofilm were prepared by the electrochemical reduction of diazonium salt of NAB at the glassy carbon electrodes (GCE) in nonaqueous media. The IR spectra of the bare glassy carbon electrodes (GCE), the NAB-GC electrode system and the organic NAB film were recorded. The IR data of the bare GC, NAB-GC and NAB film were categorized into five series consisting of FILM1, GC-NAB1, GC1; FILM2, GC-NAB2, GC2; FILM3, GC-NAB3, GC3 and FILM4, GC-NAB4, GC4 respectively. The PPP approach was applied to each group of the data of unmodified and modified electrode systems with nanofilm. The results provided by PPP method show the existence of the NAB film on the modified GC electrode.

Role of abrasive material on micro-abrasion wear tests

Micro-abrasion wear tests with ball-cratering configuration are widely used. Sources of variability are already studied by different authors and conditions for testing are parameterized by BS EN 1071-6: 2007 standard which refers silicon carbide as abrasive. However, the use of other abrasives is possible and allowed. In this work, ball-cratering wear tests were performed using four different abrasive particles of three dissimilar materials: diamond, alumina and silicon carbide. Tests were carried out under the same conditions on a steel plate provided with TiB2 hard coating. For each abrasive, five different test durations were used allowing understanding the initial wear phenomena. Composition and shape of abrasive particles were investigated by SEM and EDS. Scar areas were observed by optical and electronic microscopy in order to understand the wear effects caused by each of them. Scar geometry and grooves were analyzed and compared. Wear coefficient was calculated for each situation. It was observed that diamond particles produce well-defined and circular wear scars. Different silicon carbide particles presented dissimilar results as consequence of distinct particle shape and size distribution.

Experimental apparatus for finger ECG biometrics

Current Electrocardiographic (ECG) signal acquisition methods are generally highly intrusive, as they involve the use of pre-gelled electrodes and cabled sensors placed directly on the person, at the chest or limbs level. Moreover, systems that make use of alternative conductive materials to overcome this issue, only provide heart rate information and not the detailed signal itself. We present a comparison and evaluation of two types of dry electrodes as interface with the skin, targeting wearable and low intrusiveness applications, which enable ECG measurement without the need for any apparatus permanently fitted to the individual. In particular, our approach is targeted at ECG biometrics using signals collected at the hand or finger level. A custom differential circuit with virtual ground was also developed for enhanced usability. Our work builds upon the current stateof-the-art in sensoring devices and processing tools, and enables novel data acquisition settings through the use of dry electrodes. Experimental evaluation was performed for Ag/AgCl and Electrolycra materials, and results show that both materials exhibit adequate performance for the intended application.

Adhesion and wear behaviour of NCD coatings on Si3N4 by micro-abrasion tests

Nanocrystalline diamond (NCD) coatings offer an excellent alternative for tribological applications, preserving most of the intrinsic mechanical properties of polycrystalline CVD diamond and adding to it an extreme surface smoothness. Silicon nitride (Si3N4) ceramics are reported to guarantee high adhesion levels to CVD microcrystalline diamond coatings, but the NCD adhesion to Si3N4 is not yet well established. Micro-abrasion tests are appropriate for evaluating the abrasive wear resistance of a given surface, but they also provide information on thin film/substrate interfacial resistance, i.e., film adhesion. In this study, a comparison is made between the behaviour of NCD films deposited by hot-filament chemical vapour deposition (HFCVD) and microwave plasma assisted chemical vapour deposition (MPCVD) techniques. Silicon nitride (Si3N4) ceramic discs were selected as substrates. The NCD depositions by HFCVD and MPCVD were carried out using H2–CH4 and H2–CH4–N2 gas mixtures, respectively. An adequate set of growth parameters was chosen for each CVD technique, resulting in NCD films having a final thickness of 5 m. A micro-abrasion tribometer was used, with 3 m diamond grit as the abrasive slurry element. Experiments were carried out at a constant rotational speed (80 r.p.m.) and by varying the applied load in the range of 0.25–0.75 N. The wear rate for MPCVD NCD (3.7±0.8 × 10−5 m3N−1m−1) is compatible with those reported for microcrystalline CVD diamond. The HFCVD films displayed poorer adhesion to the Si3N4 ceramic substrates than the MPCVD ones. However, the HFCVD films show better wear resistance as a result of their higher crystallinity according to the UV Raman data, despite evidencing premature adhesion failure.

Influence of the abrasive particles size in the micro-abrasion wear tests of TiAlSiN thin coatings

Ball rotating micro-abrasion tribometers are commonly used to carry out wear tests on thin hard coatings. In these tests, different kinds of abrasives were used, as alumina (Al2O3), silicon carbide (SiC) or diamond. In each kind of abrasive, several particle sizes can be used. Some studies were developed in order to evaluate the influence of the abrasive particle shape in the micro-abrasion process. Nevertheless, the particle size was not well correlated with the material removed amount and wear mechanisms. In this work, slurry of SiC abrasive in distilled water was used, with three different particles size. Initial surface topography was accessed by atomic force microscopy (AFM). Coating hardness measurements were performed with a micro-hardness tester. In order to evaluate the wear behaviour, a TiAlSiN thin hard film was used. The micro-abrasion tests were carried out with some different durations. The abrasive effect of the SiC particles was observed by scanning electron microscopy (SEM) both in the films (hard material) as in the substrate (soft material), after coating perforation. Wear grooves and removed material rate were compared and discussed.

Development of fractional order capacitors based on electrolyte processes

In recent years, significant research in the field of electrochemistry was developed. The performance of electrical devices, depending on the processes of the electrolytes, was described and the physical origin of each parameter was established. However, the influence of the irregularity of the electrodes was not a subject of study and only recently this problem became relevant in the viewpoint of fractional calculus. This paper describes an electrolytic process in the perspective of fractional order capacitors. In this line of thought, are developed several experiments for measuring the electrical impedance of the devices. The results are analyzed through the frequency response, revealing capacitances of fractional order that can constitute an alternative to the classical integer order elements. Fractional order electric circuits are used to model and study the performance of the electrolyte processes.

Write-erase and read paper memory transistor

Applied Physics Letters, Vol.93, issue 20

ALS-Sence: sistema de aquisição e processamento de electromiogramas para pacientes com ALS

Dissertação para obtenção do grau de Mestre em Engenharia de Eletrónica e Computadores

alpha-Co(OH)(2)/carbon nanofoam composite as electrochemical capacitor electrode operating at 2 V in aqueous medium

In this work, alpha-Co(OH)(2) is electrodeposited onto carbon nanofoam forming a composite electrode operating in a potential window of 2 V in aqueous medium. Prior to electrodeposition, the carbon nanofoam substrate is subjected to a functionalization process, which leads to an increase of about 40% in its specific capacitance value. Formation of cobalt hydroxide clusters onto the functionalized carbon nanofoam by pulse electrodeposition further enhances the specific capacitance of the electrode. The combination of these factors with an enlarged working potential window, results in a material with specific capacitance close to 300 F g(-1) at current density of 1 A g(-1), considering the total mass loading of the composite. This suggests the potential application of the prepared composites in high energy density electrochemical supercapacitors. (c) 2015 Elsevier B.V. All rights reserved.

Preliminary study of synthesis gas production from water electrolysis, using the ELECTROFUEL (R) concept

This paper describes preliminary work on the generation of synthesis gas from water electrolysis using graphite electrodes without the separation of the generated gases. This is an innovative process, that has no similar work been done earlier. Preliminary tests allowed to establish correlations between the applied current to the electrolyser and flow rate and composition of the generated syngas, as well as a characterisation of generated carbon nanoparticles. The obtained syngas can further be used to produce synthetic liquid fuels, for example, methane, methanol or DME (dimethyl ether) in a catalytic reactor, in further stages of a present ongoing project, using the ELECTROFUEL® concept. The main competitive advantage of this project lies in the built-in of an innovative technology product, from RE (renewable energy) power in remote locations, for example, islands, villages in mountains as an alternative for energy storage for mobility constraints.