Metal Oxide Sensors Research Articles

Temperature optimization of metal oxide sensor arrays using Mutual Information

The sensitivity and selectivity of metal oxide (MOX) gas sensors change significantly when the sensors operate at different temperatures. While previous investigations have presented systematic approaches to optimize the operating temperature of a single MOX sensor, in this paper we present a methodology to select the optimal operating temperature of all the MOX sensors constituent of a gas sensor array based on the multivariate response of all the sensing elements. Our approach estimates a widely used Information Theory measure, the so-called Mutual Information (MI), which quantifies the amount of information that the state of one random variable (response of the gas sensor array) can provide from the state of another random variable representing the gas quality. More specifically, our methodology builds sensor models from experimental data to solve the technical problem of populating the joint probability distribution for the MI estimation. We demonstrate the relevance of our approach by maximizing the MI and selecting the best operating temperatures of a four-sensor array sampled at 94 different temperatures to optimize the discrimination task of ethanol, acetic acid, 2-butanone, and acetone. In addition to being applicable in principle to sensor arrays of any size, our approach gives precise information on the ability of the system to discriminate odors according to the temperature of the MOX sensors, for either the optimal set of temperatures or the temperatures that may render inefficient operation of the system itself.

Nanostructured Metal Oxide Gas Sensors, a Survey of Applications Carried out at SENSOR Lab, Brescia (Italy) in the Security and Food Quality Fields

In this work we report on metal oxide (MOX) based gas sensors, presenting the work done at the SENSOR laboratory of the CNR-IDASC and University of Brescia, Italy since the 80s up to the latest results achieved in recent times. In particular we report the strategies followed at SENSOR during these 30 years to increase the performance of MOX sensors through the development of different preparation techniques, from Rheotaxial Growth Thermal Oxidation (RGTO) to nanowire technology to address sensitivity and stability, and the development of electronic nose systems and pattern recognition techniques to address selectivity. We will show the obtained achievement in the context of selected applications such as safety and security and food quality control.

Standardization of metal oxide sensor array using artificial neural networks through experimental design

Abstract The shift in sensor signal measured by identical gas sensor array system (commonly called an electronic nose) makes the analysis of merged measurement data difficult. This would grossly affect the gas quantification accuracy of such electronic nose (E-nose) instruments. Thus, a real-time calibration transfer based on reference alcohol projection transfer model (RAPT) was designed in this paper which aims to project onto the hazardous gas and set up a “bridge” to transfer from instrument to instrument through three artificial neural networks (ANN), and attempt to solve the problem of signal shift between E-nose instruments of identical sensor array. Besides, principal component analysis (PCA) is also used for validation of different models in component space. For comparison, previous four models including univariate direct standardization (UDS), partial least square (PLS), neural, and global affine transformation based on robust weighted least square (GAT-RWLS) are also presented. Qualitative and quantitative results demonstrate that the proposed RAPT model is competitive in E-nose signal shift standardization.

Investigations on irreversible- and reversible-type gas sensing for ZnO and Mg0.5Zn0.5Fe2O4 chemi-resistive sensors

Semiconducting metal oxides are attractive material candidates for combustible gas sensors. Little or marginal base resistance drift of these metal oxide sensors is desirable during repeated response and recovery cycles. However, due to the partial recovery, often a significant drift in base resistance is observed. The gas sensing is termed irreversible when there is a partial recovery of base resistance, whereas for reversible sensing the base resistance is fully recovered. For reducing gas (hydrogen and carbon monoxide) sensing we have reported reversible and irreversible resistance transients for magnesium zinc ferrite and zinc oxide sensing elements, respectively. For a wide range of gas concentrations and operating temperatures, the response transients for these sensing elements are modelled using the Langmuir–Hinshelwood reaction mechanism. It is revealed that for irreversible-type sensing, the response time is reduced with the increase in test gas concentration. On the other hand, for reversible-type sensing, the response time is found to be independent of the gas concentration. Based on the estimation of pore size, pore size distribution and specific surface area of the calcined powder together with the analyses of the surface morphology of the sensing elements we have argued that due to the porous morphology of the magnesium zinc ferrite sensing element the oxidized product can easily desorb from the sensor during recovery. Therefore, irrespective of the test gas concentration, the base resistance of the magnesium zinc ferrite sensor recovers fully during the recovery process.

Improving gas identification accuracy of a temperature-modulated gas sensor using an ensemble of classifiers

Data processing methods commonly used in conjunction with the array- and quasi-array-based gas identification systems generally include a dimension reduction followed by categorization using a classifier. Here, we have applied an ensemble of classifiers, directly to the high dimensional feature vectors and fused their verdicts by majority voting. The quasi-array investigated is a metal oxide sensor temperature-modulated with different rectangular heating voltage pulses. The experimental database was developed by recording the temporal responses obtained at different conditions to methanol, ethanol and 1-butanol vapors. Features related to each response were extracted by wavelet transform. The classification rates achieved with traditional methods were compared to that obtained using an ensemble of classifiers. The classification rate was improved by majority voting among the classifiers, each trained on different feature subsets, for the classification verdict.

Electronic Noses as Flexible Tools to Assess Food Quality and Safety: Should We Trust Them?

This paper presents three different applications of an electronic nose (EN) based on a metal oxide sensor array, in order to illustrate the broad spectrum of potential uses of the technique in food quality control. The following scenarios are considered: 1) the screening of a typical error that may occur during the processing of tomato pulp, which leads to sensory damage of the product; 2) the detection of microbial contamination by Alicyclobacillus spp. (ACB) affecting soft drinks; and 3) the proof of evidence of extra virgin olive oil fraudulently adulterated with hazelnut oil. In each case, the EN is able to identify the spoiled product by means of the alterations in the pattern of volatile compounds, reconstructed by principal component analysis of the sensor responses.

Towards high-dynamic range CMOS integrated interface circuits for gas sensors

This paper summarizes the results of our research activity in the field of gas-sensing systems, with particular focus on high dynamic-range (DR) integrated interface circuits. This activity was stimulated and strongly encouraged by Prof. Arnaldo D’Amico over the last ten years. The availability of large DR integrated interface circuits is absolutely necessary to turn metal-oxide chemoresistive sensors into effective gas-sensing systems. In this paper we overview different techniques for achieving read-out circuits with DR spanning from 140dB to 160dB and we present the experimental results obtained from three different test chips. The first and the second test chips implement a multi-scale auto-ranging read-out circuit and an oscillator-based read-out circuit, respectively, while the third test chip implements a complete gas-sensing system, including a sensor temperature control circuit as well as an oscillator-based read-out circuit. The results achieved demonstrate that metal-oxide chemoresistive sensors in combination with suitable integrated interface circuits are promising candidates for realizing low-cost portable gas-sensing systems.

Real-time look-up table-based color correction for still image stabilization of digital cameras without using frame memory

Digital cameras usually decrease exposure time to capture motion-blur-free images. However, this operation will generate an under-exposed image with a low-budget complementary metal-oxide semiconductor image sensor (CIS). Conventional color correction algorithms can efficiently correct under-exposed images; however, they are generally not performed in real time and need at least one frame memory if they are implemented by hardware. The authors propose a real-time look-up table-based color correction method that corrects under-exposed images with hardware without using frame memory. The method utilizes histogram matching of two preview images, which are exposed for a long and short time, respectively, to construct an improved look-up table (ILUT) and then corrects the captured under-exposed image in real time. Because the ILUT is calculated in real time before processing the captured image, this method does not require frame memory to buffer image data, and therefore can greatly save the cost of CIS. This method not only supports single image capture, but also bracketing to capture three images at a time. The proposed method was implemented by hardware description language and verified by a field-programmable gate array with a 5 M CIS. Simulations show that the system can perform in real time with a low cost and can correct the color of under-exposed images well.

An Electronic System to Heat MOX Sensors With Synchronized and Programmable Thermal Profiles

Metal oxide (MOX) sensors are widely used in several application fields: environmental monitoring, home automation, food control, and so on. Research activities in this topic are oriented toward new materials and nanotechnologies, thus requiring new instruments for the sensor characterization and management. Often, in order to improve selectivity, sensitivity, stability, the sensor is heated according to purposely designed profiles. The repeatability of the measurement conditions strongly depends on the ability to perform a sensor resistance measurement in a synchronous fashion with respect to the imposed thermal profile. This work proposes an electronic equipment for a complete management of a generic MOX sensor. The system is able to estimate the sensor resistance in a range varying from tens of kilohms up to tens of gigohms, while driving the sensor heater with a thermal profile designed by the user. Thanks to the short readout time (10 ms) and to the synchronism between the heater management and the sensor resistance measurement, the system is suitable for monitoring fast transients and thermal dynamics of the sensors. In addition, an estimation of the sensor parasitic capacitance, modeled in parallel with the resistive part and on the order of few picofarads, is provided for diagnostic purposes. Experimental results conducted on both commercial resistors/capacitors emulating the sensor, and on a real SnO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> nanowire-based sensor for carbon monoxide detection have demonstrated the validity of the proposed approach. Broad topic: 17. Measurement Techniques.

Measurement of Resistance and Capacitance of MOX Sensors With High Sampling Rate

Resistive chemical sensors, such as metal oxide (MOX) devices, usually exhibit resistance values within a wide range, from tens of kilohms to tens of gigohms. This is due, for example, to the different sensor material, manufacturing, working temperature, and so on. Electronic interfaces based on the resistance-to-time conversion (RTC) technique are widely used to handle such sensors, thanks to the low-cost, low-noise, and wide-range characteristics; in fact, time intervals are easier to measure within several decades without the need of scaling factors. However, the main limit of the RTC-based schemes is the variable and long measuring time, from microseconds (tens of kilohms) to quite a lot of seconds (tens of gigohms), impeding, for instance, a fine analysis of fast transients. This work proposes an innovative circuit based on the combination of the RTC method with the use of the least mean square interpolation algorithm. The implemented prototype allows the sensor resistance to be estimated with a constant measuring time of 10 ms within the range 10 kΩ ÷100 GΩ. The proposed implementation has shown a relative estimation error less than 10% (about 1% within 100 kΩ ÷100 GΩ). In addition, the system is capable to estimate the parasitic effect of the sensor (modeled with a capacitance up to 50 pF in parallel with the resistive component), showing a linearity error around 0.3% full scale (FS). A new tool has been also provided to estimate the uncertainty of the proposed approach due to rapid resistance changes, such as fast sensor transients. The simulation tool has been also used to prove performance improvement in the capacitance estimation, with respect to previously proposed solutions. Experimental results conducted using different real MOX sensors show the suitability of the proposed system for applications in which the sensor behavior need to be accurately analyzed, even in presence of fast dynamics.

High Definition Image Pre-Processing System for Multi-Stripe Satellites' Image Sensors

High-resolution image sensors play an important role in today's satellites' remote sensing applications. This paper presents an image recombination and processing system for one-dimensional multi-strip complementary metal-oxide semiconductor image sensors (CISs.) The proposed system takes advantage of the satellites' linear moving property to control the exposure time of CIS and provides the real-time ability to generate 11 200× N high-resolution images for satellites' remote sensing. Using hardware accelerators coupled with versatile microprocessors, the architecture is able to offer processing capability as well as long-term maintainability for space-borne platforms. The details of hardware design to meet real-time requirement are presented. The prototype, which contains four strip CISs and field programmable gate array-based prototyping, was implemented to verify functionality and capability of real-time image acquisition and combination. The implementation results show that it is feasible to integrate the proposed system into a single chip.

Consumer acceptability of ovine cheese from ewes fed extruded linseed-enriched diets

The aim of this experiment was to study consumer acceptability and composition of Pecorino cheese obtained from ewes fed an extruded linseed-enriched diet. Sixty lactating Sarda ewes were randomly assigned to 3 dietary treatments: (1) control concentrate (CTR); (2) concentrate enriched with 100g/kg of extruded linseed (EL-10); (3) concentrate enriched with 200g/kg of extruded linseed (EL-20), that were all administered along with ad libitum alfalfa hay. Cheeses were made with the bulk milk obtained from the 3 groups. The results showed that the diet affected cheese composition after 60days of ripening. Linseed supplementation decreased protein and fat content while it increased the concentration of monounsaturated, polyunsaturated and long-chain fatty acids in both EL-10 and EL-20 cheeses. The extruded linseed-enriched diets improved the n-3 fatty acid and conjugated linoleic acid contents and decreased the n-6/n-3 fatty acid ratio. A consumer panel evaluated the cheeses for color, eyeness, toughness, Pecorino cheese odor, Pecorino cheese flavor, extraneous odors and flavors and overall acceptability. Although EL-10 and EL-20 cheeses differed from the CTR cheese for some sensory profile attributes, all groups proved similar for overall acceptability and presence of extraneous odors and flavors. A triangle test showed no differences among dietary treatments. Furthermore, when a MOS sensor array, composed of six metal oxide sensors, was used to evaluate the three types of cheeses, no differences were found among groups. Extruded linseed supplementation seems therefore a possible strategy for improving the nutritional quality of lipids in Pecorino cheese without affecting its sensory properties.

Rapid discrimination of Chinese red ginseng and Korean ginseng using an electronic nose coupled with chemometrics

Red ginseng is a precious and widely used traditional Chinese medicine. At present, Chinese red ginseng and Korean ginseng are both commonly found on the market. To rapidly and nondestructively discriminate between Chinese red ginseng and Korean ginseng, an electronic nose coupled with chemometrics was developed. Different red ginseng samples, including Chinese red ginseng (n=30) and Korean ginseng (South Korean red ginseng and North Korean red ginseng n=26), were collected. The metal oxide sensors on an electronic nose were used to measure the red ginseng samples. Multivariate statistical analyses, including principal component analysis (PCA), discriminant factorial analysis (DFA) and soft independent modeling of class analogy (SIMCA), were employed. All of the samples were analyzed by PCA. Most of the samples were used to set up DFA and SIMCA models, and then the remaining samples (Nos. 9, 10, 17, 18, 29, 30, 34, 43, 44, 50, and 51) were projected onto the DFA and SIMCA models in the form of black dots to validate the models. The results indicated that Chinese red ginseng and Korean ginseng were successfully discriminated using the electronic nose coupled with PCA, DFA and SIMCA. The checking scores of the DFA and SIMCA models were 100. The samples projected onto the DFA and SIMCA models were all correctly discriminated. The DFA and SIMCA models were robust. Electronic nose technology is a rapid, accurate, sensitive and nondestructive method to discriminate between Chinese red ginseng and Korean ginseng.

Functionalised zinc oxide nanowire gas sensors: Enhanced NO2 gas sensor response by chemical modification of nanowire surfaces

Surface coating with an organic self-assembled monolayer (SAM) can enhance surface reactions or the absorption of specific gases and hence improve the response of a metal oxide (MOx) sensor toward particular target gases in the environment. In this study the effect of an adsorbed organic layer on the dynamic response of zinc oxide nanowire gas sensors was investigated. The effect of ZnO surface functionalisation by two different organic molecules, tris(hydroxymethyl)aminomethane (THMA) and dodecanethiol (DT), was studied. The response towards ammonia, nitrous oxide and nitrogen dioxide was investigated for three sensor configurations, namely pure ZnO nanowires, organic-coated ZnO nanowires and ZnO nanowires covered with a sparse layer of organic-coated ZnO nanoparticles. Exposure of the nanowire sensors to the oxidising gas NO2 produced a significant and reproducible response. ZnO and THMA-coated ZnO nanowire sensors both readily detected NO2 down to a concentration in the very low ppm range. Notably, the THMA-coated nanowires consistently displayed a small, enhanced response to NO2 compared to uncoated ZnO nanowire sensors. At the lower concentration levels tested, ZnO nanowire sensors that were coated with THMA-capped ZnO nanoparticles were found to exhibit the greatest enhanced response. ΔR/R was two times greater than that for the as-prepared ZnO nanowire sensors. It is proposed that the ΔR/R enhancement in this case originates from the changes induced in the depletion-layer width of the ZnO nanoparticles that bridge ZnO nanowires resulting from THMA ligand binding to the surface of the particle coating. The heightened response and selectivity to the NO2 target are positive results arising from the coating of these ZnO nanowire sensors with organic-SAM-functionalised ZnO nanoparticles.

Effectiveness of electronic nose systems to detect bergamot (Citrus bergamia Risso et Poiteau) essential oil quality and genuineness

The quality of an essential oil is determined by its composition as well as by the complex aroma features. The aim of this work was to analyze the effectiveness of electronic nose (e-nose) systems to detect quality and genuineness of bergamot essential oils (BEOs). Tested methods included volatile analysis with the e-nose based on metal-oxide semiconductor sensors and analysis of chemical composition of essential oil by chromatography (GC/FID, GC/MS). The paper reports preliminary results on the potential of an e-nose to discriminate natural cold-pressed bergamot oil (BEO C-P) from those deterpenated and bergapten-free; between samples obtained from different cultivars; from samples obtained from fruit grown in the Protected Denomination of Origin (PDO) area and those outside the PDO; and finally from synthetic essential oils (SEO). This feasibility study has confirmed that an e-nose demonstrates the ability to supply a concrete support to BEO quality control. The e-noses, with subsequent DFA treatment of data, offer the advantages of rapidity and reliability. Further validation studies are currently under way with the aim of enriching and updating the databases of reference for BEOs. In order to broaden the range of e-nose use, tests on sensors chiral comportment are in progress, in order to bring this same approach in the study of adulteration of BEOs.

ChemInform Abstract: Vacuum Technology Applied to Solid State Chemical Sensors, Processing, Characterization and Applications

AbstractReview: 31 refs.

Use of electronic nose and GC-MS in detection and monitoring some VOC

The aim of this study was to evaluate the use of an electronic nose (e-nose) as on-line, rapid method to quantify the MSW composting gases. Changes in selected VOCs (limonene, β-pinene, 2-butanone, undecane, toluene and dimethyl disulfide) during composting were studied and quantified by means of two different analytical methods (GC-MS and e-nose). The results of this study indicate that it is possible to differentiate and quantify the main gases emitted during Municipal Solid Waste- Legume Trimming Residues composting using an electronic nose equipped with 10 Metal Oxide Sensors. The electronic nose was able to detect a clear difference in volatile compounds profile of emitted gases in composting, using Principal Component Analysis (PCA) analysis. PCA successfully reduced the data sets from the sensors to two principal components, which accounted for 74.5%, 68.8% and 62.8% of the total variance by using patterns for initial, thermophilic and mesophilic composting phases respectively.

Application of a miniaturised packed gas chromatography column and a SnO2 gas detector for analysis of low molecular weight hydrocarbons with focus on ethylene detection

In this paper the combination and application of a silicon based miniaturised gas chromatography (GC) column packed with Carboxen 1000 and a gas detector based on a commercial SnO2 metal oxide sensor are described. Target analytes are gas mixtures containing hydrocarbons with low molecular weight from C1 and C2 and ethylene as main target gas. The detector achieved a resolution of at least 1ppmv related to ethylene gas. The combination of the detector with the miniaturised GC-column provides a linear behaviour between the injected ethylene gas volume and the related peak area in the chromatogram with a resolution of 2nl. Examination of the GC-performance gave HEPT-values of about 0.7mm and chromatographic resolutions of 100% in most cases using a gas mixture containing CO2, nitrogen, acetylene, ethylene, methane and ethane with synthetic air as carrier gas.

Nanoparticle Langmuir-Blodgett Arrays for Sensing of CO and NO2 Gases

Metal oxide sensors with active Fe2O3 and CoFe2O4 nanoparticle arrays were studied. Sensing nanoparticle films from 1, 2, 4 or 7 monolayers were deposited by Langmuir-Blodgett technique. Sensors are formed on the alumina substrates equipped with heating meander. Langmuir-Blodgett layers were heated or UV irradiated to remove the insulating surfactant. Sensing properties were studied towards CO or NO2 gases in concentrations between 0.5 and 100 ppm in mixture with the dry air. Best response values Igas/Iair were obtained with CoFe2O4 device being 3 for 100 ppm of CO and with Fe2O3 device being (38) -1 for 0.5 ppm of NO2.

Gas Chromatograph based on Packed μGC-Columns and μ-Preconcentrator Devices for Ethylene Detection in Fruit Logistic Applications

Abstract A miniaturised preconcentrator device (μPCD) filled with Carbosieve S-II was coupled with a miniaturised gas chromatograph (μGC) and was tested with focus on ethylene gas measurement. The application of the μPCD results in an increase of the system sensitivity by a factor of 23 from 140 ppmv to 6 ppmv using an ethylene detector based on a metal oxide sensor.