Epitaxially grown graphene based gas sensors for ultra sensitive NO2 detection

Epitaxially grown single layer and multi layer graphene on SiC devices were fabricated and compared for response towards NO₂. Due to electron donation from SiC, single layer graphene is n-type with a very low carrier concentration. The choice of substrate is demonstrated to enable tailoring of the electronic properties of graphene, with a SiC substrate realising simple resistive devices tuned for extremely sensitive NO₂ detection. The gas exposed uppermost layer of the multi layer device is screened from the SiC by the intermediate layers leading to a p-type nature with a higher concentration of charge carriers and therefore, a lower gas response. The single layer graphene device is thought to undergo an n-p transition upon exposure to increasing concentrations of NO₂ indicated by a change in response direction. This transition is likely to be due to the transfer of electrons to NO₂ making holes the majority carriers.     

Diesel engine dynamometer testing of impedancemetric NOx sensors

Prototype solid-state electrochemical sensors using a dense gold sensing electrode, porous yttria-stabilized zirconia (YSZ) electrolyte, and a platinum counter electrode (Au/YSZ/Pt) were evaluated for measuring NO_x (NO and NO₂) in diesel exhaust. Both electrodes were exposed to the test gas (i.e., there was no reference gas for the counter electrode). An impedancemetric method was used for NO_x measurements, where the phase angle was used as the response signal. A portion of the tailpipe exhaust from the dynamometer test stand was extracted and fed into a furnace containing the experimental sensor. The prototype sensor was tested along with a commercially available NO_x sensor. Simultaneous measurements for NO_x, O₂, CO₂, H₂O, CO, and CH₄ in a separate feed stream were made using Fourier transform infrared (FTIR) spectroscopy and an oxygen paramagnetic analyzer. The experimental sensor showed very good measurement capability for NO in the range of 25-250 ppm, with a response paralleling that of the FTIR and commercial sensor. The prototype sensor showed better sensitivity to NO_x at the lower concentration ranges. O₂ is an interferent for the experimental sensor, resulting in decreased sensitivity for measurement of NO_x. Methods to overcome this interference are discussed.     

Bioluminescent sensor for naphthalene in air: Cell immobilization and evaluation with a dynamic standard atmosphere generator

A dynamic atmosphere generator with a naphthalene emission source has been constructed and used for the development and evaluation of a bioluminescence sensor based on the bacteria Pseudomonas fluorescens HK44 immobilized in 2% agar gel (10⁷ cell mL⁻¹) placed in sampling tubes. A steady naphthalene emission rate (around 7.3 nmol min⁻¹ at 27 °C and 7.4 mL min⁻¹ of purified air) was obtained by covering the diffusion unit containing solid naphthalene with a PTFE filter membrane. The time elapsed from gelation of the agar matrix to analyte exposure (“maturation time”) was found relevant for the bioluminescence assays, being most favorable between 1.5 and 3 h. The maximum light emission, observed after 80 min, is dependent on the analyte concentration and the exposure time (evaluated between 5 and 20 min), but not on the flow rate of naphthalene in the sampling tube, over the range of 1.8–7.4 nmol min⁻¹. A good linear response was obtained between 50 and 260 nmol L⁻¹ with a limit of detection estimated in 20 nmol L⁻¹ far below the recommended threshold limit value for naphthalene in air.     

A novel microbial biosensor based on Circinella sp. modified carbon paste electrode and its voltammetric application

Microbial biosensors have been developed for voltammetric determination of various substances. This paper describes the development of a new biosorption based microbial biosensor for determination of Cu²⁺. The developed biosensor is based on carbon paste electrode consisting of whole cells of Circinella sp. Cu²⁺ was preconcentrated on the electrode surface at open circuit and then cathodically detected with the reduction of Cu²⁺. The voltammetric responses were evaluated with respect to percentage cell loading in the carbon paste, preconcentration time, pH of preconcentration solution, scan rate and interferences. The optimum response was realized by biosensor constructed using 5 mg of dry cell weight per 100 mg of carbon paste in pH 5.5 preconcentration solution. Under the optimum experimental conditions, the developed microbial biosensor exhibited an excellent current response to Cu²⁺ over a linear range from 5.0 × 10⁻⁷ to 1.0 × 10⁻⁵ M (r² = 0.9938) with a detection limit of 5.4 × 10⁻⁸ M (S/N = 3). The microbial biosensor had good sensitivity and reproducibility (R.S.D. 4.3%, n = 6). Finally, the applicability of the proposed microbial biosensor to voltammetric determination of Cu²⁺ in real sample was also demonstrated and validated with atomic absorption spectrophotometric (AAS) method.     

Room temperature ammonia sensors based on zinc oxide and functionalized graphite and multi-walled carbon nanotubes

In this work, different techniques are proposed to realize ammonia (NH₃) sensors working at room temperature and a preliminary electrical characterization under water vapor and in NH₃ atmospheres is presented. Three families of ceramic planar sensors based on a zinc oxide (ZnO) layer overlapped by screen-printed Pd-doped carboxyl groups functionalized multi-walled carbon nanotubes (Pd-COOH-MWCNTs) or by blocks of vertically aligned MWCNTs or by graphite as such and functionalized with fluorinated or nitrogenous functional groups were studied.These sensors were almost insensitive to humidity, while all of them gave a good response in NH₃ atmosphere, starting from about 45 ppm in the case of zinc oxide with fluorinated or nitrogenous MWCNTs and graphite or 50 ppm for Pd-COOH-MWCNTs sensors. These results are not actually as good as those reported in the literature, but this preliminary work proposes simpler and cheaper processes to realize NH₃ sensor for room temperature applications.     

Differential pulse voltammetric determination of N-acetylcysteine by the electrocatalytic oxidation at the surface of carbon nanotube-paste electrode modified with cobalt salophen complexes

The preparation and electrochemical performance of the carbon nanotube-paste electrode modified with salophen complexes of cobalt(III) perchlorate, with various substituents on the salophen ligand, as well as their electrocatalytic activity toward the oxidation of N-acetylcysteine (NAC) is investigated. Several Schiff base complexes containing various nucleophilic and electrophilic functional groups were prepared, and their electrochemical characteristics for the electro-oxidation of NAC were evaluated using cyclic and differential pulse voltammetry (CV and DPV). The results revealed, the modified electrodes show an efficient and selective electrocatalytic activity toward the anodic oxidation of NAC among biologically important compounds in buffered solutions at pH of 7.0. The best voltammetric responses were obtained for a carbon-paste electrode (CPE) modified with a salophen complex containing para-methoxy groups on its salicylaldehyde ring. The analytical response of the modified electrode for response to other sulfhydryl compounds (e.g., cysteine, penicillamine, captopril and mercaptopropionyl glycine) in comparison to NAC was investigated by CV and DPV methods. The DPV method was applied as a sensitive method for the quantitative detection of the trace amounts of NAC. A linear dynamic range from 1 × 10⁻⁷ to 1 × 10⁻⁴ M with calibration sensitivity of 0.0646 μA/μM is resulted for NAC in DPV measurements. The detection limit was 5 × 10⁻⁸ M, which is remarkably lower than those reported previously for NAC using other modified electrodes. The results of voltammetric determinations show a very good reproducibility, and the R.S.D. for the slope of the calibration curve, based on 10 measurements in a period of two months, was <3.9%. The detection system provides very stable electrochemical responses toward NAC, makes it very suitable for using in pharmaceutical and clinical measurements.     

Welding current and arc voltage control in a GMAW process using ARMarkov based MPC

A predictive functional controller based on ARMarkov model structure has been designed to control welding current and arc voltage in a GMAW process. The closed loop system performance is investigated through computer simulations and is compared by those achieved from implementing two commonly used controllers i.e. PI and feedback linearization based PID. The local stability of the closed loop system is analyzed in the presence of uncertainties in the linearized model of the process as well as the control parameters. Finally it is shown that the proposed controller performs like a PI controller along with a pre-filter compensator.     

Rapid differentiation between E. coli and Salmonella Typhimurium using metal oxide sensors integrated with pattern recognition

A rapid method to differentiate between E coli and Salmonella Typhimurium was developed. E. coli and S. Typhimurium were separately grown in super broth and incubated at 37 °C. Super broth without inoculation of E. coli or S. Typhimurium was used as control. Numbers of E. coli and S. Typhimurium were followed using a colony counting method. Identification of the volatile metabolites produced by E. coli and S. Typhimurium was determined using solid-phase microextraction coupled with gas chromatography/mass spectrometry. An electronic nose with 12 non-specific metal oxide sensors was used to monitor the volatile profiles produced by E. coli and S. Typhimurium. Principal component analysis (PCA) and back-propagation neural network (BPNN) were used as pattern recognition tools. PCA was used for data exploration and dimensional reduction. PCA could visualize class separation between sample subgroups. The BPNN was shown to be capable of predicting the number of E. coli and S. Typhimurium. Good prediction was possible as measured by a regression coefficient (R² = 0.96) between true and predicted data. Using metal oxide sensors and pattern recognition techniques, it was possible to discriminate between samples containing E. coli from those containing S. Typhimurium.     

Development and application of micromachined Pd/SnO2 gas sensors with zeolite coatings

Zeolite A (LTA)-coated micromachined sensors have been prepared and used in the sensing of individual gases (H₂, CH₄, C₂H₅OH, C₃H₈ and CO, in the 10–1000 ppm range) and gas mixtures. Unlike previous works with conventional sensors, a hydrothermal synthesis was not used to prepare a zeolite film. Instead, a zeolite coating was formed on top of the Pd/SnO₂ surface by microdropping from a zeolite suspension. In spite of this, the response of the sensor with zeolite is significantly different from that of unmodified sensors, and essentially reproduces the performance of zeolite-coated conventional sensors. By avoiding the use of a hydrothermal synthesis the integrity of the sensor is better preserved, and the resulting non-continuous zeolite film has the added advantage of a strong reduction in response times.     

Necked ZnO nanoparticle-based NO2 sensors with high and fast response

The NO₂ gas sensing characteristics of semiconductor type gas sensors with channels composed of necked ZnO nanoparticles (NPs) were investigated in this study. The heat treatment of the NPs at 400 °C led to their necking and coarsening. The response of the necked-NP-based sensors was as high as 100 when exposed to 0.2 ppm of NO₂ at 200 °C. As the concentration of NO₂ increased to 5 ppm, their response was enhanced to approximately 400. During the repeated injection of NO₂ gas with a concentration of 0.4 ppm, the sensors exhibited stable response characteristics. Furthermore, the 90% response and recovery times of the gas sensor were as fast as 13 and 10 s, respectively. These observations indicate that the non-agglomerated necking of the NPs induced by the heat treatment significantly enhances the gas sensing characteristics of the NP-based gas sensors.     

A new optochemical chlorine gas sensor based on the application of amphiphilic co-networks as matrices

A sensor for chlorine gas detection, consisting of an amphiphilic polymer co-network with an immobilised oxidation indicator, o-tolidine, is described. Data describing gas sensing properties and long-term stability will be presented. This study focuses on APCN thin films as a matrix for indicator immobilisation.Thin films of poly(2-hydroxyethyl acrylate)-l-polydimethylsiloxane PHEA-l-PDMS were prepared as immobilisation matrices for o-tolidine.We present a simple, non-expensive, but highly sensitive optical sensor for chlorine gas detection. The thin film response is reproducible and irreversible. With our kinetic-optical method rapid response times were achieved. The determination of chlorine is performed on the basis of the oxidation of o-tolidine as the chromogenic reagent to a coloured product which can be monitored at 650 nm. The results reveal a fast response to chlorine gas down to concentrations of 0.01 ppm.     

Eigenvectors of tridiagonal matrices of Sylvester type

Eigenvectors of the tridiagonal matrices of Sylvester type are explicitly determined. These are closely related to orthogonal polynomials named after Krawtchouk, (dual) Hahn and Racah as well as to q-Racah polynomials.      

(J, J′)-lossless factorization based on conjugation

This paper is concerned with a derivation of the state-space form of the (J, J′)-lossless factorization which contains both the inner-outer factorization and the spectral factorization of positive matrices as special cases. Also, the (J, J′)-lossless factorization gives a unified framework of H^∞ control theory. We use the method of conjugation which makes the derivation much simpler than the previous literature, most of which used the technique of (J, J′)-spectral factorization. A necessary and sufficient condition is represented in terms of two Riccati equations one of which is degenerated.     

Direct electrochemistry of cytochrome c and biosensing for hydrogen peroxide on polyaniline grafted multi-walled carbon nanotube electrode

Cytochrome c (cyt c) was immobilized into a matrix consisting of polyaniline (PANI) and multi-walled carbon nanotubes (MWNT) by a new strategy. First, PANI chains were grafted onto MWNT through electropolymerization. Second, the amine groups in PANI chains were oxidized at an applied potential of +0.80 V to acquire positive charges that would effectively immobilize negatively charged cyt C. The ITO/MWNT-g-PANI(O)/cyt c electrode exhibited a pair of redox peaks with a peak potential separation (anodic to cathodic) of 0.25 V (vs Ag/AgCl) in 0.1 M phosphate buffer (pH 7.0). The results demonstrated that ITO/MWNT-g-PANI(O)/cyt c promoted direct electron transfer between cyt c and electrode with a high electron transfer rate constant (17 s⁻¹). The ITO/MWNT-g-PANI(O)/cyt c electrode catalyzes the reduction of H₂O₂. The ITO/MWNT-g-PANI(O)/cyt c biosensor displays an amperometric response to H₂O₂ with a linear concentration range from 0.5 μM to 1.5 mM (r = 0.99, n = 12), a high sensitivity (32.2 μAm M⁻¹) and fast response (9 s) and detection limit of 0.3 μM (S/N = 3).     

Bryophyte cover estimation in a boreal black spruce forest using airborne lidar and multispectral sensors

Bryophytes are the dominant ground cover vegetation layer in many boreal forests and in some of these forests the net primary production of bryophytes exceeds the overstory. Therefore it is necessary to quantify their spatial coverage and species composition in boreal forests to improve boreal forest carbon budget estimates. We present results from a small exploratory test using airborne lidar and multispectral remote sensing data to estimate the percentage of ground cover for mosses in a boreal black spruce forest in Manitoba, Canada. Multiple linear regression was used to fit models that combined spectral reflectance data from CASI and indices computed from the SLICER canopy height profile. Three models explained 63-79% of the measured variation of feathermoss cover while three models explained 69-92% of the measured variation of sphagnum cover. Root mean square errors ranged from 3-15% when predicting feathermoss, sphagnum, and total moss ground cover. The results from this case study warrant further testing for a wider range of boreal forest types and geographic regions.     

Conduction mechanisms in SnO2 based polycrystalline thick film gas sensors exposed to CO and H2 in different oxygen backgrounds

The conduction mechanism in polycrystalline SnO₂ thick sensing films was modeled and experimentally investigated by means of simultaneous DC electrical resistance and work function changes measurements under CO and H₂ exposure in different oxygen backgrounds. It was shown that, according to the composition of the ambient atmosphere, the conduction changes from the case in which it is controlled by the surface depletion layers to a situation in which the main contribution comes from free charge transport in the surface accumulation layer. This is significant for the interpretation of work function changes measurements results because the relation between the different measured electrical resistance and surface band bending depends on the conduction model. Furthermore, the CO sensing mechanism dependence on the oxygen amount in the ambient was explained.     

Structural and properties of nanocrystalline WO3/TiO2-based humidity sensors elements prepared by high energy activation

Nanocrystalline WO₃/TiO₂-based powders have been prepared by the high energy activation method with WO₃ concentration ranging from 1 to 10 mol%. The samples were thermal treated in a microwave oven at 600 °C for 20 min and their structural and micro-structural characteristics were evaluated by X-ray diffraction, Raman spectroscopy, EXAFS measurements at the Ti K-edge, and transmission electron microscopy. Nitrogen adsorption isotherms and H₂ Temperature Programmed Reduction were also carried out for physical characterization. The crystallite and particle mean sizes ranged from 30 to 40 nm and from 100 to 190 nm, respectively. Good sensor response was obtained for samples with at least 5 mol% WO₃ activated for at least 80 min. Ceramics heat-treated in microwave oven for 20 min have shown similar sensor response as those prepared in conventional oven for 120 min, which is highly cost effective. These results indicate that WO₃/TiO₂ ceramics can be used as a humidity sensor element.     

基于分布式传感器信息融合的辐射源识别

针对辐射源识别中基本概率赋值函数(BPAF)获取的难题,提出基于模糊集、灰关联分析和特征参数相似度的3种BPAF获取法,推演了获取BPAF的数学关系,建立了基于分布式传感器数种基本概率赋值获取法的信息融合辐射源识别模型,利用该模型进行了识别实验.识别过程中进行了多周期时域融合与分布式传感器窄域融合,并在不同信噪比下与模板匹配法作识别率比较.实验对比结果表明,分布式传感器信息融合识别法是有效的,辐射源平均识别率超过90%.     

Decision tree approach for classification and dimensionality reduction of electronic nose data

This paper presents a decision tree approach using two different tree models, C4.5 and CART, for use in the classification and dimensionality reduction of electronic nose (EN) data. The decision tree is a tree structure consisting of internal and terminal nodes which process the data to ultimately yield a classification. The decision tree is proficient at both maintaining the role of dimensionality reduction and at organizing optimally sized classification trees, and therefore it could be a promising approach to analyze EN data. In the experiments conducted, six sensor response parameters were extracted from the dynamic sensor responses of each of the four metal oxide gas sensors. The six parameters observed were the rising time (T_r), falling time (T_f), total response time (T_t), normalized peak voltage change (y_p,n), normalized curve integral (C_I), and triangle area (T_A). One sensor parameter from each metal oxide sensor was used for the classification trees, and the best classification accuracy of 97.78% was achieved by CART using the C_I parameter. However, the accuracy of CART was improved using all of the sensor parameters as inputs to the classification tree. The improved results of CART, having an accuracy of 98.89%, was comparable to that of two popular classifiers, the multilayer perceptron (MLP) neural network and the fuzzy ARTMAP network (accuracy of 98.89%, and 100%, respectively). Furthermore, as a dimensionality reduction method the decision tree has shown a better discrimination accuracy of 100% for the MLP classifier and 98.89% for the fuzzy ARTMAP classifier as compared to those achieved with principle component analysis (PCA) giving 81.11% and 97.78%, and a variable selection method giving 92.22% and 93.33% (for the same MLP and fuzzy ARTMAP classifiers). Therefore, a decision tree could be a promising technique for a pattern recognition system for EN data in terms of two functions; as classifier which is an optimally organized classification tree, and as dimensionality reduction method for other pattern recognition techniques.     

Text document clustering based on neighbors

Clustering is a very powerful data mining technique for topic discovery from text documents. The partitional clustering algorithms, such as the family of k-means, are reported performing well on document clustering. They treat the clustering problem as an optimization process of grouping documents into k clusters so that a particular criterion function is minimized or maximized. Usually, the cosine function is used to measure the similarity between two documents in the criterion function, but it may not work well when the clusters are not well separated. To solve this problem, we applied the concepts of neighbors and link, introduced in [S. Guha, R. Rastogi, K. Shim, ROCK: a robust clustering algorithm for categorical attributes, Information Systems 25 (5) (2000) 345–366], to document clustering. If two documents are similar enough, they are considered as neighbors of each other. And the link between two documents represents the number of their common neighbors. Instead of just considering the pairwise similarity, the neighbors and link involve the global information into the measurement of the closeness of two documents. In this paper, we propose to use the neighbors and link for the family of k-means algorithms in three aspects: a new method to select initial cluster centroids based on the ranks of candidate documents; a new similarity measure which uses a combination of the cosine and link functions; and a new heuristic function for selecting a cluster to split based on the neighbors of the cluster centroids. Our experimental results on real-life data sets demonstrated that our proposed methods can significantly improve the performance of document clustering in terms of accuracy without increasing the execution time much.