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Sensors, Volume 13, Issue 9 (September 2013), Pages 11167-12743

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Open AccessArticle Crop Biometric Maps: The Key to Prediction
Sensors 2013, 13(9), 12698-12743; https://doi.org/10.3390/s130912698
Received: 24 June 2013 / Revised: 6 September 2013 / Accepted: 17 September 2013 / Published: 23 September 2013
Cited by 5 | PDF Full-text (3084 KB) | HTML Full-text | XML Full-text
Abstract
The sustainability of agricultural production in the twenty-first century, both in industrialized and developing countries, benefits from the integration of farm management with information technology such that individual plants, rows, or subfields may be endowed with a singular “identity.” This approach approximates the
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The sustainability of agricultural production in the twenty-first century, both in industrialized and developing countries, benefits from the integration of farm management with information technology such that individual plants, rows, or subfields may be endowed with a singular “identity.” This approach approximates the nature of agricultural processes to the engineering of industrial processes. In order to cope with the vast variability of nature and the uncertainties of agricultural production, the concept of crop biometrics is defined as the scientific analysis of agricultural observations confined to spaces of reduced dimensions and known position with the purpose of building prediction models. This article develops the idea of crop biometrics by setting its principles, discussing the selection and quantization of biometric traits, and analyzing the mathematical relationships among measured and predicted traits. Crop biometric maps were applied to the case of a wine-production vineyard, in which vegetation amount, relative altitude in the field, soil compaction, berry size, grape yield, juice pH, and grape sugar content were selected as biometric traits. The enological potential of grapes was assessed with a quality-index map defined as a combination of titratable acidity, sugar content, and must pH. Prediction models for yield and quality were developed for high and low resolution maps, showing the great potential of crop biometric maps as a strategic tool for vineyard growers as well as for crop managers in general, due to the wide versatility of the methodology proposed. Full article
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Open AccessArticle Static Hyperspectral Fluorescence Imaging of Viscous Materials Based on a Linear Variable Filter Spectrometer
Sensors 2013, 13(9), 12687-12697; https://doi.org/10.3390/s130912687
Received: 25 June 2013 / Revised: 29 August 2013 / Accepted: 13 September 2013 / Published: 23 September 2013
Cited by 7 | PDF Full-text (279 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a low-cost hyperspectral measurement setup in a new application based on fluorescence detection in the visible (Vis) wavelength range. The aim of the setup is to take hyperspectral fluorescence images of viscous materials. Based on these images, fluorescent and non-fluorescent
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This paper presents a low-cost hyperspectral measurement setup in a new application based on fluorescence detection in the visible (Vis) wavelength range. The aim of the setup is to take hyperspectral fluorescence images of viscous materials. Based on these images, fluorescent and non-fluorescent impurities in the viscous materials can be detected. For the illumination of the measurement object, a narrow-band high-power light-emitting diode (LED) with a center wavelength of 370 nm was used. The low-cost acquisition unit for the imaging consists of a linear variable filter (LVF) and a complementary metal oxide semiconductor (CMOS) 2D sensor array. The translucent wavelength range of the LVF is from 400 nm to 700 nm. For the confirmation of the concept, static measurements of fluorescent viscous materials with a non-fluorescent impurity have been performed and analyzed. With the presented setup, measurement surfaces in the micrometer range can be provided. The measureable minimum particle size of the impurities is in the nanometer range. The recording rate for the measurements depends on the exposure time of the used CMOS 2D sensor array and has been found to be in the microsecond range. Full article
(This article belongs to the Special Issue Optomechatronics)
Open AccessArticle A Relevance Vector Machine-Based Approach with Application to Oil Sand Pump Prognostics
Sensors 2013, 13(9), 12663-12686; https://doi.org/10.3390/s130912663
Received: 18 June 2013 / Revised: 10 September 2013 / Accepted: 12 September 2013 / Published: 18 September 2013
Cited by 13 | PDF Full-text (697 KB) | HTML Full-text | XML Full-text
Abstract
Oil sand pumps are widely used in the mining industry for the delivery of mixtures of abrasive solids and liquids. Because they operate under highly adverse conditions, these pumps usually experience significant wear. Consequently, equipment owners are quite often forced to invest substantially
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Oil sand pumps are widely used in the mining industry for the delivery of mixtures of abrasive solids and liquids. Because they operate under highly adverse conditions, these pumps usually experience significant wear. Consequently, equipment owners are quite often forced to invest substantially in system maintenance to avoid unscheduled downtime. In this study, an approach combining relevance vector machines (RVMs) with a sum of two exponential functions was developed to predict the remaining useful life (RUL) of field pump impellers. To handle field vibration data, a novel feature extracting process was proposed to arrive at a feature varying with the development of damage in the pump impellers. A case study involving two field datasets demonstrated the effectiveness of the developed method. Compared with standalone exponential fitting, the proposed RVM-based model was much better able to predict the remaining useful life of pump impellers. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A 0.0016 mm2 0.64 nJ Leakage-Based CMOS Temperature Sensor
Sensors 2013, 13(9), 12648-12662; https://doi.org/10.3390/s130912648
Received: 1 August 2013 / Revised: 3 September 2013 / Accepted: 9 September 2013 / Published: 18 September 2013
Cited by 7 | PDF Full-text (1813 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a CMOS temperature sensor based on the thermal dependencies of the leakage currents targeting the 65 nm node. To compensate for the effect of process fluctuations, the proposed sensor realizes the ratio of two measures of the time it takes
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This paper presents a CMOS temperature sensor based on the thermal dependencies of the leakage currents targeting the 65 nm node. To compensate for the effect of process fluctuations, the proposed sensor realizes the ratio of two measures of the time it takes a capacitor to discharge through a transistor in the subthreshold regime. Furthermore, a novel charging mechanism for the capacitor is proposed to further increase the robustness against fabrication variability. The sensor, including digitization and interfacing, occupies 0.0016 mm2 and has an energy consumption of 47.7–633 pJ per sample. The resolution of the sensor is 0.28 °C, and the 3σ inaccuracy over the range 40–110 °C is 1.17 °C. Full article
Open AccessArticle Laser Doppler Blood Flow Imaging Using a CMOS Imaging Sensor with On-Chip Signal Processing
Sensors 2013, 13(9), 12632-12647; https://doi.org/10.3390/s130912632
Received: 25 July 2013 / Revised: 6 September 2013 / Accepted: 9 September 2013 / Published: 18 September 2013
Cited by 13 | PDF Full-text (2117 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The first fully integrated 2D CMOS imaging sensor with on-chip signal processing for applications in laser Doppler blood flow (LDBF) imaging has been designed and tested. To obtain a space efficient design over 64 × 64 pixels means that standard processing electronics used
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The first fully integrated 2D CMOS imaging sensor with on-chip signal processing for applications in laser Doppler blood flow (LDBF) imaging has been designed and tested. To obtain a space efficient design over 64 × 64 pixels means that standard processing electronics used off-chip cannot be implemented. Therefore the analog signal processing at each pixel is a tailored design for LDBF signals with balanced optimization for signal-to-noise ratio and silicon area. This custom made sensor offers key advantages over conventional sensors, viz. the analog signal processing at the pixel level carries out signal normalization; the AC amplification in combination with an anti-aliasing filter allows analog-to-digital conversion with a low number of bits; low resource implementation of the digital processor enables on-chip processing and the data bottleneck that exists between the detector and processing electronics has been overcome. The sensor demonstrates good agreement with simulation at each design stage. The measured optical performance of the sensor is demonstrated using modulated light signals and in vivo blood flow experiments. Images showing blood flow changes with arterial occlusion and an inflammatory response to a histamine skin-prick demonstrate that the sensor array is capable of detecting blood flow signals from tissue. Full article
(This article belongs to the collection Sensors for Globalized Healthy Living and Wellbeing)
Open AccessArticle Detection of Upscale-Crop and Partial Manipulation in Surveillance Video Based on Sensor Pattern Noise
Sensors 2013, 13(9), 12605-12631; https://doi.org/10.3390/s130912605
Received: 25 July 2013 / Revised: 20 August 2013 / Accepted: 6 September 2013 / Published: 18 September 2013
Cited by 9 | PDF Full-text (3040 KB) | HTML Full-text | XML Full-text
Abstract
In many court cases, surveillance videos are used as significant court evidence. As these surveillance videos can easily be forged, it may cause serious social issues, such as convicting an innocent person. Nevertheless, there is little research being done on forgery of surveillance
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In many court cases, surveillance videos are used as significant court evidence. As these surveillance videos can easily be forged, it may cause serious social issues, such as convicting an innocent person. Nevertheless, there is little research being done on forgery of surveillance videos. This paper proposes a forensic technique to detect forgeries of surveillance video based on sensor pattern noise (SPN). We exploit the scaling invariance of the minimum average correlation energy Mellin radial harmonic (MACE-MRH) correlation filter to reliably unveil traces of upscaling in videos. By excluding the high-frequency components of the investigated video and adaptively choosing the size of the local search window, the proposed method effectively localizes partially manipulated regions. Empirical evidence from a large database of test videos, including RGB (Red, Green, Blue)/infrared video, dynamic-/static-scene video and compressed video, indicates the superior performance of the proposed method. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Ontology Alignment Architecture for Semantic Sensor Web Integration
Sensors 2013, 13(9), 12581-12604; https://doi.org/10.3390/s130912581
Received: 18 June 2013 / Revised: 24 August 2013 / Accepted: 12 September 2013 / Published: 18 September 2013
Cited by 10 | PDF Full-text (370 KB) | HTML Full-text | XML Full-text
Abstract
Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental
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Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic Web technologies are becoming closely related with sensor networks. The linking of elements from Semantic Web technologies with sensor networks has been called Semantic Sensor Web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity). Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the Semantic Sensor Web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity’s names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI) tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle Analysis and Design of a 3rd Order Velocity-Controlled Closed-Loop for MEMS Vibratory Gyroscopes
Sensors 2013, 13(9), 12564-12580; https://doi.org/10.3390/s130912564
Received: 11 June 2013 / Revised: 30 July 2013 / Accepted: 27 August 2013 / Published: 18 September 2013
Cited by 2 | PDF Full-text (577 KB) | HTML Full-text | XML Full-text
Abstract
The time-average method currently available is limited to analyzing the specific performance of the automatic gain control-proportional and integral (AGC-PI) based velocity-controlled closed-loop in a micro-electro-mechanical systems (MEMS) vibratory gyroscope, since it is hard to solve nonlinear functions in the time domain when
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The time-average method currently available is limited to analyzing the specific performance of the automatic gain control-proportional and integral (AGC-PI) based velocity-controlled closed-loop in a micro-electro-mechanical systems (MEMS) vibratory gyroscope, since it is hard to solve nonlinear functions in the time domain when the control loop reaches to 3rd order. In this paper, we propose a linearization design approach to overcome this limitation by establishing a 3rd order linear model of the control loop and transferring the analysis to the frequency domain. Order reduction is applied on the built linear model’s transfer function by constructing a zero-pole doublet, and therefore mathematical expression of each control loop’s performance specification is obtained. Then an optimization methodology is summarized, which reveals that a robust, stable and swift control loop can be achieved by carefully selecting the system parameters following a priority order. Closed-loop drive circuits are designed and implemented using 0.35 μm complementary metal oxide semiconductor (CMOS) process, and experiments carried out on a gyroscope prototype verify the optimization methodology that an optimized stability of the control loop can be achieved by constructing the zero-pole doublet, and disturbance rejection capability (D.R.C) of the control loop can be improved by increasing the integral term. Full article
(This article belongs to the Special Issue Modeling, Testing and Reliability Issues in MEMS Engineering 2011)
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Open AccessArticle Experimental Investigation on Centrifugal Compressor Blade Crack Classification Using the Squared Envelope Spectrum
Sensors 2013, 13(9), 12548-12563; https://doi.org/10.3390/s130912548
Received: 18 July 2013 / Revised: 10 September 2013 / Accepted: 11 September 2013 / Published: 18 September 2013
Cited by 7 | PDF Full-text (463 KB) | HTML Full-text | XML Full-text
Abstract
Centrifugal compressors are a key piece of equipment for modern production. Among the components of the centrifugal compressor, the impeller is a pivotal part as it is used to transform kinetic energy into pressure energy. Blade crack condition monitoring and classification has been
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Centrifugal compressors are a key piece of equipment for modern production. Among the components of the centrifugal compressor, the impeller is a pivotal part as it is used to transform kinetic energy into pressure energy. Blade crack condition monitoring and classification has been broadly investigated in the industrial and academic area. In this research, a pressure pulsation (PP) sensor arranged in close vicinity to the crack area and the corresponding casing vibration signals are used to monitor blade crack information. As these signals cannot directly demonstrate the blade crack, the method employed in this research is based on the extraction of weak signal characteristics that are induced by blade cracking. A method for blade crack classification based on the signals monitored by using a squared envelope spectrum (SES) is presented. Experimental investigations on blade crack classification are carried out to verify the effectiveness of this method. The results show that it is an effective tool for blade crack classification in centrifugal compressors. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Model-Based Spike Detection of Epileptic EEG Data
Sensors 2013, 13(9), 12536-12547; https://doi.org/10.3390/s130912536
Received: 17 June 2013 / Revised: 6 September 2013 / Accepted: 13 September 2013 / Published: 17 September 2013
Cited by 20 | PDF Full-text (399 KB) | HTML Full-text | XML Full-text
Abstract
Accurate automatic spike detection is highly beneficial to clinical assessment of epileptic electroencephalogram (EEG) data. In this paper, a new two-stage approach is proposed for epileptic spike detection. First, the k-point nonlinear energy operator (k-NEO) is adopted to detect all possible spike candidates,
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Accurate automatic spike detection is highly beneficial to clinical assessment of epileptic electroencephalogram (EEG) data. In this paper, a new two-stage approach is proposed for epileptic spike detection. First, the k-point nonlinear energy operator (k-NEO) is adopted to detect all possible spike candidates, then a newly proposed spike model with slow wave features is applied to these candidates for spike classification. Experimental results show that the proposed system, using the AdaBoost classifier, outperforms the conventional method in both two- and three-class EEG pattern classification problems. The proposed system not only achieves better accuracy for spike detection, but also provides new ability to differentiate between spikes and spikes with slow waves. Though spikes with slow waves occur frequently in epileptic EEGs, they are not used in conventional spike detection. Identifying spikes with slow waves allows the proposed system to have better capability for assisting clinical neurologists in routine EEG examinations and epileptic diagnosis. Full article
(This article belongs to the Special Issue Biomedical Sensors and Systems)
Open AccessArticle Quantitative Assessment of Birefringent Skin Structures in Scattered Light Confocal Imaging Using Radially Polarized Light
Sensors 2013, 13(9), 12527-12535; https://doi.org/10.3390/s130912527
Received: 19 July 2013 / Revised: 14 August 2013 / Accepted: 11 September 2013 / Published: 17 September 2013
PDF Full-text (391 KB) | HTML Full-text | XML Full-text
Abstract
The polarization characteristics of birefringent tissues could be only partially obtained using linearly polarized light in polarization sensitive optical imaging. Here we analyze the change in polarization of backscattered light from birefringent structures versus the orientations of the incident polarizations using linearly, circularly
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The polarization characteristics of birefringent tissues could be only partially obtained using linearly polarized light in polarization sensitive optical imaging. Here we analyze the change in polarization of backscattered light from birefringent structures versus the orientations of the incident polarizations using linearly, circularly and radially polarized light in a cross-polarized confocal microscope. A spatially variable retardation plate composed of eight sectors of λ/2 wave plates was used to transform linearly polarized light into a radially polarized light. Based on the experimental data obtained from ex-vivo measurements on human scalp hairs and in-vivo measurements on hair and skin, we exemplify that the underestimation of the birefringence content resulting from the orientation related effects associated with the use of linearly polarized light for imaging tissues containing wavy birefringent structures could be minimized by using radially polarized light. Full article
(This article belongs to the Special Issue Photonic Sensors for Industrial, Environmental and Health Monitoring)
Open AccessArticle Stem Cell Enrichment with Selectin Receptors: Mimicking the pH Environment of Trauma
Sensors 2013, 13(9), 12516-12526; https://doi.org/10.3390/s130912516
Received: 16 July 2013 / Revised: 6 September 2013 / Accepted: 11 September 2013 / Published: 17 September 2013
Cited by 12 | PDF Full-text (543 KB) | HTML Full-text | XML Full-text
Abstract
The isolation of hematopoietic stem and progenitor cells (HSPCs) is critical for transplantation therapy and HSPC research, however current isolation techniques can be prohibitively expensive, time-consuming, and produce variable results. Selectin-coated microtubes have shown promise in rapidly isolating HSPCs from human bone marrow,
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The isolation of hematopoietic stem and progenitor cells (HSPCs) is critical for transplantation therapy and HSPC research, however current isolation techniques can be prohibitively expensive, time-consuming, and produce variable results. Selectin-coated microtubes have shown promise in rapidly isolating HSPCs from human bone marrow, but further purification of HSPCs remains a challenge. Herein, a biomimetic device for HSPC isolation is presented to mimic the acidic vascular microenvironment during trauma, which can enhance the binding frequency between L-selectin and its counter-receptor PSGL-1 and HSPCs. Under acidic pH conditions, L-selectin coated microtubes enhanced CD34+ HSPC adhesion, as evidenced by decreased cell rolling velocity and increased rolling flux. Dynamic light scattering was utilized as a novel sensor to confirm an L-selectin conformational change under acidic conditions, as previously predicted by molecular dynamics. These results suggest that mimicking the acidic conditions of trauma can induce a conformational extension of L-selectin, which can be utilized for flow-based, clinical isolation of HSPCs. Full article
(This article belongs to the Special Issue Biomimetic Receptors and Sensors)
Open AccessArticle Data Processing and Quality Evaluation of a Boat-Based Mobile Laser Scanning System
Sensors 2013, 13(9), 12497-12515; https://doi.org/10.3390/s130912497
Received: 7 August 2013 / Revised: 5 September 2013 / Accepted: 10 September 2013 / Published: 17 September 2013
Cited by 21 | PDF Full-text (1652 KB) | HTML Full-text | XML Full-text
Abstract
Mobile mapping systems (MMSs) are used for mapping topographic and urban features which are difficult and time consuming to measure with other instruments. The benefits of MMSs include efficient data collection and versatile usability. This paper investigates the data processing steps and quality
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Mobile mapping systems (MMSs) are used for mapping topographic and urban features which are difficult and time consuming to measure with other instruments. The benefits of MMSs include efficient data collection and versatile usability. This paper investigates the data processing steps and quality of a boat-based mobile mapping system (BoMMS) data for generating terrain and vegetation points in a river environment. Our aim in data processing was to filter noise points, detect shorelines as well as points below water surface and conduct ground point classification. Previous studies of BoMMS have investigated elevation accuracies and usability in detection of fluvial erosion and deposition areas. The new findings concerning BoMMS data are that the improved data processing approach allows for identification of multipath reflections and shoreline delineation. We demonstrate the possibility to measure bathymetry data in shallow (0–1 m) and clear water. Furthermore, we evaluate for the first time the accuracy of the BoMMS ground points classification compared to manually classified data. We also demonstrate the spatial variations of the ground point density and assess elevation and vertical accuracies of the BoMMS data. Full article
(This article belongs to the Section Remote Sensors)
Open AccessArticle A Multi-Fork Z-Axis Quartz Micromachined Gyroscope
Sensors 2013, 13(9), 12482-12496; https://doi.org/10.3390/s130912482
Received: 4 July 2013 / Revised: 19 August 2013 / Accepted: 11 September 2013 / Published: 17 September 2013
Cited by 5 | PDF Full-text (1750 KB) | HTML Full-text | XML Full-text
Abstract
A novel multi-fork z-axis gyroscope is presented in this paper. Different from traditional quartz gyroscopes, the lateral electrodes of the sense beam can be arranged in simple patterns; as a result, the fabrication is simplified. High sensitivity is achieved by the multi-fork design.
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A novel multi-fork z-axis gyroscope is presented in this paper. Different from traditional quartz gyroscopes, the lateral electrodes of the sense beam can be arranged in simple patterns; as a result, the fabrication is simplified. High sensitivity is achieved by the multi-fork design. The working principles are introduced, while the finite element method (FEM) is used to simulate the modal and sensitivity. A quartz fork is fabricated, and a prototype is assembled. Impedance testing shows that the drive frequency and sense frequency are similar to the simulations, and the quality factor is approximately 10,000 in air. The scale factor is measured to be 18.134 mV/(°/s) and the nonlinearity is 0.40% in a full-scale input range of ±250 °/s. Full article
(This article belongs to the Special Issue Modeling, Testing and Reliability Issues in MEMS Engineering 2013)
Open AccessArticle NO and NO2 Sensing Properties of WO3 and Co3O4 Based Gas Sensors
Sensors 2013, 13(9), 12467-12481; https://doi.org/10.3390/s130912467
Received: 23 July 2013 / Revised: 27 August 2013 / Accepted: 11 September 2013 / Published: 17 September 2013
Cited by 36 | PDF Full-text (2047 KB) | HTML Full-text | XML Full-text
Abstract
Semiconductor-based gas sensors that use n-type WO3 or p-type Co3O4 powder were fabricated and their gas sensing properties toward NO2 or NO (0.5–5 ppm in air) were investigated at 100 °C or 200 °C. The resistance of the
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Semiconductor-based gas sensors that use n-type WO3 or p-type Co3O4 powder were fabricated and their gas sensing properties toward NO2 or NO (0.5–5 ppm in air) were investigated at 100 °C or 200 °C. The resistance of the WO3-based sensor increased on exposure to NO2 and NO. On the other hand, the resistance of the Co3O4-based sensor varied depending on the operating temperature and the gas species. The chemical states of the surface of WO3 or those of the Co3O4 powder on exposure to 1 ppm NO2 and NO were investigated by diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy. No clear differences between the chemical states of the metal oxide surface exposed to NO2 or NO could be detected from the DRIFT spectra. Full article
(This article belongs to the Section Chemical Sensors)
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