by Keyword: Chemical sensors

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Pomareda, V., Magrans, R., Jiménez-Soto, J., Martínez, D., Tresánchez, M., Burgués, J., Palacín, J., Marco, S., (2017). Chemical source localization fusing concentration information in the presence of chemical background noise Sensors 17, (4), 904

We present the estimation of a likelihood map for the location of the source of a chemical plume dispersed under atmospheric turbulence under uniform wind conditions. The main contribution of this work is to extend previous proposals based on Bayesian inference with binary detections to the use of concentration information while at the same time being robust against the presence of background chemical noise. For that, the algorithm builds a background model with robust statistics measurements to assess the posterior probability that a given chemical concentration reading comes from the background or from a source emitting at a distance with a specific release rate. In addition, our algorithm allows multiple mobile gas sensors to be used. Ten realistic simulations and ten real data experiments are used for evaluation purposes. For the simulations, we have supposed that sensors are mounted on cars which do not have among its main tasks navigating toward the source. To collect the real dataset, a special arena with induced wind is built, and an autonomous vehicle equipped with several sensors, including a photo ionization detector (PID) for sensing chemical concentration, is used. Simulation results show that our algorithm, provides a better estimation of the source location even for a low background level that benefits the performance of binary version. The improvement is clear for the synthetic data while for real data the estimation is only slightly better, probably because our exploration arena is not able to provide uniform wind conditions. Finally, an estimation of the computational cost of the algorithmic proposal is presented.

Keywords: Machine olfaction, Odor robots, Chemical sensors, Bayesian inference

Fonollosa, J., Fernández, L., Gutiérrez-Gálvez, A., Huerta, R., Marco, S., (2016). Calibration transfer and drift counteraction in chemical sensor arrays using Direct Standardization Sensors and Actuators B: Chemical 236, 1044-1053

Inherent variability of chemical sensors makes it necessary to calibrate chemical detection systems individually. This shortcoming has traditionally limited usability of systems based on metal oxide gas sensor arrays and prevented mass-production for some applications. Here, aiming at exploring calibration transfer between chemical sensor arrays, we exposed five twin 8-sensor detection units to different concentration levels of ethanol, ethylene, carbon monoxide, or methane. First, we built calibration models using data acquired with a master unit. Second, to explore the transferability of the calibration models, we used Direct Standardization to map the signals of a slave unit to the space of the master unit in calibration. In particular, we evaluated the transferability of the calibration models to other detection units, and within the same unit measuring days apart. Our results show that signals acquired with one unit can be successfully mapped to the space of a reference unit. Hence, calibration models trained with a master unit can be extended to slave units using a reduced number of transfer samples, diminishing thereby calibration costs. Similarly, signals of a sensing unit can be transformed to match sensor behavior in the past to mitigate drift effects. Therefore, the proposed methodology can reduce calibration costs in mass-production and delay recalibrations due to sensor aging. Acquired dataset is made publicly available.

Keywords: Calibration transfer, Chemical sensors, Direct Standardization, Electronic nose, MOX sensors, Public dataset

Huerta, R., Mosqueiro, T., Fonollosa, J., Rulkov, N.F., Rodríguez-Lujan, I., (2016). Online decorrelation of humidity and temperature in chemical sensors for continuous monitoring Chemometrics and Intelligent Laboratory Systems 157, 169-176

A method for online decorrelation of chemical sensor signals from the effects of environmental humidity and temperature variations is proposed. The goal is to improve the accuracy of electronic nose measurements for continuous monitoring by processing data from simultaneous readings of environmental humidity and temperature. The electronic nose setup built for this study included eight metal-oxide sensors, temperature and humidity sensors with a wireless communication link to external computer. This wireless electronic nose was used to monitor the air for two years in the residence of one of the authors and it collected data continuously during 537 days with a sampling rate of 1 sample per second. To estimate the effects of variations in air humidity and temperature on the chemical sensors' signals, we used a standard energy band model for an n-type metal-oxide (MOX) gas sensor. The main assumption of the model is that variations in sensor conductivity can be expressed as a nonlinear function of changes in the semiconductor energy bands in the presence of external humidity and temperature variations. Fitting this model to the collected data, we confirmed that the most statistically significant factors are humidity changes and correlated changes of temperature and humidity. This simple model achieves excellent accuracy with a coefficient of determination R2 close to 1. To show how the humidity–temperature correction model works for gas discrimination, we constructed a model for online discrimination among banana, wine and baseline response. This shows that pattern recognition algorithms improve performance and reliability by including the filtered signal of the chemical sensors.

Keywords: Electronic nose, Chemical sensors, Humidity, Temperature, Decorrelation, Wireless e-nose, MOX sensors, Energy band model, Home monitoring

Fonollosa, J., Sheik, S., Huerta, R., Marco, S., (2015). Reservoir computing compensates slow response of chemosensor arrays exposed to fast varying gas concentrations in continuous monitoring Sensors and Actuators B: Chemical 215, 618-629

Metal oxide (MOX) gas sensors arrays are a predominant technological choice to perform fundamental tasks of chemical detection. Yet, their use has been mainly limited to relatively controlled instrument configurations where the sensor array is placed within a closed measurement chamber. Usually, the experimental protocol is defined beforehand and it includes three stages: the array is first exposed to a gas reference, then to the gas sample, and finally to the reference again to recover the initial state. Such sampling procedure requires signal acquisition during the complete experimental protocol and usually delays the output prediction until the predefined measurement duration is complete. Due to the slow time response of chemical sensors, the completion of the measurement typically requires minutes. In this paper we propose the use of reservoir computing (RC) algorithms to overcome the slow temporal dynamics of chemical sensor arrays, allowing identification and quantification of chemicals of interest continuously and reducing measurement delays. We generated two datasets to test the ability of RC algorithms to provide accurate and continuous prediction to fast varying gas concentrations in real time. Both datasets - one generated with synthetic data and the other acquired from actual gas sensors - provide time series of MOX sensors exposed to binary gas mixtures where concentration levels change randomly over time. Our results show that our approach improves the time response of the sensory system and provides accurate predictions in real time, making the system specifically suitable for online monitoring applications. Finally, the collected dataset and developed code are made publicly available to the research community for further studies.

Keywords: Chemical sensors, Continuous gas prediction, Electronic nose, Real-time detection, Reservoir computing

Mir, M., Lugo, R., Tahirbegi, I. B., Samitier, J., (2014). Miniaturizable ion-selective arrays based on highly stable polymer membranes for biomedical applications Sensors 14, (7), 11844-11854

Poly(vinylchloride) (PVC) is the most common polymer matrix used in the fabrication of ion-selective electrodes (ISEs). However, the surfaces of PVC-based sensors have been reported to show membrane instability. In an attempt to overcome this limitation, here we developed two alternative methods for the preparation of highly stable and robust ion-selective sensors. These platforms are based on the selective electropolymerization of poly(3,4-ethylenedioxythiophene) (PEDOT), where the sulfur atoms contained in the polymer covalently interact with the gold electrode, also permitting controlled selective attachment on a miniaturized electrode in an array format. This platform sensor was improved with the crosslinking of the membrane compounds with poly(ethyleneglycol) diglycidyl ether (PEG), thus also increasing the biocompatibility of the sensor. The resulting ISE membranes showed faster signal stabilization of the sensor response compared with that of the PVC matrix and also better reproducibility and stability, thus making these platforms highly suitable candidates for the manufacture of robust implantable sensors.

Keywords: Biomedicine, Electrochemistry, Endoscope, Implantable device, Ion-selective electrode (ISE) sensor, Ischemia, pH detection, Biocompatibility, Chemical sensors, Electrochemistry, Electrodes, Electropolymerization, Endoscopy, Functional polymers, Implants (surgical), Ion selective electrodes, Medical applications, Polyvinyl chlorides, Stabilization, Biomedical applications, Biomedicine, Implantable devices, Ion selective sensors, Ischemia, Membrane instability, pH detection, Poly(3 ,4 ethylenedioxythiophene) (PEDOT), Ion selective membranes

Tahirbegi, I. B., Alvira, M., Mir, M., Samitier, J., (2014). Simple and fast method for fabrication of endoscopic implantable sensor arrays Sensors 14, (7), 11416-11426

Here we have developed a simple method for the fabrication of disposable implantable all-solid-state ion-selective electrodes (ISE) in an array format without using complex fabrication equipment or clean room facilities. The electrodes were designed in a needle shape instead of planar electrodes for a full contact with the tissue. The needle-shape platform comprises 12 metallic pins which were functionalized with conductive inks and ISE membranes. The modified microelectrodes were characterized with cyclic voltammetry, scanning electron microscope (SEM), and optical interferometry. The surface area and roughness factor of each microelectrode were determined and reproducible values were obtained for all the microelectrodes on the array. In this work, the microelectrodes were modified with membranes for the detection of pH and nitrate ions to prove the reliability of the fabricated sensor array platform adapted to an endoscope.

Keywords: Chemical sensors, Cyclic voltammetry, Electrochemistry, Endoscopy, Fabrication, Implants (surgical), Microelectrodes, Needles, Nitrates, Scanning electron microscopy, Biomedicine, Fabricated sensors, Fabrication equipment, Implantable devices, Implantable sensors, Optical interferometry, Planar electrode, Roughness factor, Ion selective electrodes

Marco, S., Gutiérrez-Gálvez, A., Lansner, A., Martinez, D., Rospars, J. P., Beccherelli, R., Perera, A., Pearce, T., Vershure, P., Persaud, K., (2013). Biologically inspired large scale chemical sensor arrays and embedded data processing Proceedings of SPIE - The International Society for Optical Engineering Smart Sensors, Actuators, and MEMS VI , SPIE Digital Library (Grenoble, France) 8763, 1-15

Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, to a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy, an efficient combinatorial coding along with unmatched chemical information processing mechanisms. The last decade has witnessed important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. EU Funded Project NEUROCHEM (Bio-ICT-FET- 216916) has developed novel computing paradigms and biologically motivated artefacts for chemical sensing taking inspiration from the biological olfactory pathway. To demonstrate this approach, a biomimetic demonstrator has been built featuring a large scale sensor array (65K elements) in conducting polymer technology mimicking the olfactory receptor neuron layer, and abstracted biomimetic algorithms have been implemented in an embedded system that interfaces the chemical sensors. The embedded system integrates computational models of the main anatomic building blocks in the olfactory pathway: The olfactory bulb, and olfactory cortex in vertebrates (alternatively, antennal lobe and mushroom bodies in the insect). For implementation in the embedded processor an abstraction phase has been carried out in which their processing capabilities are captured by algorithmic solutions. Finally, the algorithmic models are tested with an odour robot with navigation capabilities in mixed chemical plumes.

Keywords: Antennal lobes, Artificial olfaction, Computational neuroscience, Olfactory bulbs, Plume tracking, Abstracting, Actuators, Algorithms, Biomimetic processes, Chemical sensors, Conducting polymers, Data processing, Flavors, Odors, Robots, Smart sensors, Embedded systems

Marco, S., Gutierrez-Galvez, A., (2012). Signal and data processing for machine olfaction and chemical sensing: A review IEEE Sensors Journal 12, (11), 3189-3214

Signal and data processing are essential elements in electronic noses as well as in most chemical sensing instruments. The multivariate responses obtained by chemical sensor arrays require signal and data processing to carry out the fundamental tasks of odor identification (classification), concentration estimation (regression), and grouping of similar odors (clustering). In the last decade, important advances have shown that proper processing can improve the robustness of the instruments against diverse perturbations, namely, environmental variables, background changes, drift, etc. This article reviews the advances made in recent years in signal and data processing for machine olfaction and chemical sensing.

Keywords: Chemical sensors, Electronic nose, Intelligent sensors, Measurement techniques, Sensor arrays, Sensor systems

Colomer-Farrarons, J., Miribel-Catala, P. L., Samitier, J., Arundell, M., Rodriguez, I., (2009). Design of a miniaturized electrochemical instrument for in-situ O/sub 2/ monitoring Sensors and Signal Conditioning VLSI Circuits and Systems IV , SPIE (Desdren, Germany) 7363, 73630A

The authors are working toward the design of a device for the detection of oxygen, following a discrete and an integrated instrumentation implementation. The discrete electronics are also used for preliminary analysis, to confirm the validity of the conception of system, and its set-up would be used in the characterization of the integrated device, waiting for the chip fabrication. This paper presents the design of a small and portable potentiostat integrated with electrodes, which is cheap and miniaturized, which can be applied for on-site measurements for the simultaneous detection of O/sub 2/ and temperature in water systems. As a first approach a discrete PCB has been designed based on commercial discrete electronics and specific oxygen sensors. Dissolved oxygen concentration (DO) is an important index of water quality and the ability to measure the oxygen concentration and temperature at different positions and depths would be an important attribute to environmental analysis. Especially, the objective is that the sensor and the electronics can be integrated in a single encapsulated device able to be submerged in environmental water systems and be able to make multiple measurements. For our proposed application a small and portable device is developed, where electronics and sensors are miniaturized and placed in close proximity to each other. This system would be based on the sensors and electronics, forming one module, and connected to a portable notebook to save and analyze the measurements on-line. The key electronics is defined by the potentiostat amplifier, used to fix the voltage between the working (WE) and reference (RE) electrodes following an input voltage (Vin). Vin is a triangular signal, programmed by a LabView/sup c / interface, which is also used to represent the CV transfers. To obtain a smaller and compact solution the potentiostat amplifier has also been integrated defining a full custom ASIC amplifier, which is in progress, looking for a point-of-care device. These circuits have been designed with a 0.13 mu m technology from ST Microelectronics through the CMP-TIMA service.

Keywords: Amplifiers, Application specific integrated circuits, Chemical sensors, Electrodes, Portable instruments, Temperature measurement, Water sources

Perera, A., Pardo, A., Barrettino, D., Hierlermann, A., Marco, S., (2009). Evaluation of fish spoilage by means of a single metal oxide sensor under temperature modulation Olfaction and Electronic Nose: Proceedings of the 13th International Symposium on Olfaction and Electronic Nose 13th International Symposium on Olfaction and Electronic Nose (ed. Pardo, M., Sberveglieri, G.), Amer Inst Physics (Brescia, Italy) 1137, 483-486

In this paper the feasibility of using metal oxide gas sensor technology for evaluating spoilage process for sea bream (Sparus Aurata) is explored. It is shown that a single sensor under temperature modulation is able to find a correlation with the fish spoilage process

Keywords: Gas sensors, Electrochemical sensors, Chromatography

Marco, S., Gutierrez-Galvez, A., (2009). Recent developments in the application of biologically inspired computation to chemical sensing Olfaction Electronic Nose: Proceedings of the 13th International Symposium on Olfaction and Electronic Nose 13th International Symposium on Olfaction and the Electronic Nose (ed. Pardo, M., Sberveglieri, G.), Amer Inst Physics (Brescia, Italy) 1137, 151-154

Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, to a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy, an efficient combinatorial coding along with unmatched chemical information processing mechanisms. The last decade has witnessed important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. In this work, the state of the art concerning biologically inspired computation for chemical sensing will be reviewed. Instead of reviewing the whole body of computational neuroscience of olfaction, we restrict this review to the application of models to the processing of real chemical sensor data.

Keywords: Computational Intelligence, Chemical Sensors