Publications

Metal Oxide (MOX) gas sensors rely on chemical reactions that occur efficiently at high temperatures, resulting in too-demanding power requirements for certain applications. Operating the sensor under a Pulsed-Temperature Operation (PTO), by which the sensor heater is switched ON and OFF periodically, is a common practice to reduce the power consumption. However, the sensor performance is degraded as the OFF periods become larger. Other research works studied, generally, PTO schemes applying waveforms to the heater with time periods of seconds and duty cycles above 20%. Here, instead, we explore the behaviour of PTO sensors working under aggressive schemes, reaching power savings of 99% and beyond with respect to continuous heater stimulation. Using sensor sensitivity and the limit of detection, we evaluated four Ultra Low Power (ULP) sensors under different PTO schemes exposed to ammonia, ethylene, and acetaldehyde. Results show that it is possible to operate the sensors with total power consumption in the range of microwatts. Despite the aggressive power reduction, sensor sensitivity suffers only a moderate decline and the limit of detection may degrade up to a factor five. This is, however, gas-dependent and should be explored on a case-by-case basis since, for example, the same degradation has not been observed for ammonia. Finally, the run-in time, i.e., the time required to get a stable response immediately after switching on the sensor, increases when reducing the power consumption, from 10 minutes to values in the range of 10–20 hours for power consumptions smaller than 200 microwatts.

JTD Keywords: Robot sensing systems, Temperature sensors, Heating systems, Gas detectors, Power demand, Sensitivity, Electronic nose, gas sensors, low-power operation, machine olfaction, pulsed-temperature operation, temperature modulation

The limit of detection (LOD) is a key figure of merit in chemical sensing. However, the estimation of this figure of merit is hindered by the non-linear calibration curve characteristic of semiconductor gas sensor technologies such as, metal oxide (MOX), gasFETs or thermoelectric sensors. Additionally, chemical sensors suffer from cross-sensitivities and temporal stability problems. The application of the International Union of Pure and Applied Chemistry (IUPAC) recommendations for univariate LOD estimation in non-linear semiconductor gas sensors is not straightforward due to the strong statistical requirements of the IUPAC methodology (linearity, homoscedasticity, normality). Here, we propose a methodological approach to LOD estimation through linearized calibration models. As an example, the methodology is applied to the detection of low concentrations of carbon monoxide using MOX gas sensors in a scenario where the main source of error is the presence of uncontrolled levels of humidity.

JTD Keywords: Semiconductor gas sensors, Metal-oxide sensors, Limit of detection, Non-linear, Humidity interference, Temperature modulation

Metal oxide semiconductor (MOX) sensors are usually temperature-modulated and calibrated with multivariate models such as Partial Least Squares (PLS) to increase the inherent low selectivity of this technology. The multivariate sensor response patterns exhibit heteroscedastic and correlated noise, which suggests that maximum likelihood methods should outperform PLS. One contribution of this paper is the comparison between PLS and maximum likelihood principal components regression (MLPCR) in MOX sensors. PLS is often criticized by the lack of interpretability when the model complexity increases beyond the chemical rank of the problem. This happens in MOX sensors due to cross-sensitivities to interferences, such as temperature or humidity and non-linearity. Additionally, the estimation of fundamental figures of merit, such as the limit of detection (LOD), is still not standardized in multivariate models. Orthogonalization methods, such as Orthogonal Projection to Latent Structures (O-PLS), have been successfully applied in other fields to reduce the complexity of PLS models. In this work, we propose a LOD estimation method based on applying the well-accepted univariate LOD formulas to the scores of the first component of an orthogonal PLS model. The resulting LOD is compared to the multivariate LOD range derived from error-propagation. The methodology is applied to data extracted from temperature-modulated MOX sensors (FIS SB-500-12 and Figaro TGS 3870-A04), aiming at the detection of low concentrations of carbon monoxide in the presence of uncontrolled humidity (chemical noise). We found that PLS models were simpler and more accurate than MLPCR models. Average LOD values of 0.79 ppm (FIS) and 1.06 ppm (Figaro) were found using the approach described in this paper. These values were contained within the LOD ranges obtained with the error-propagation approach. The mean LOD increased to 1.13 ppm (FIS) and 1.59 ppm (Figaro) when considering validation samples collected two weeks after calibration, which represents a 43% and 46% degradation, respectively. The orthogonal score-plot was a very convenient tool to visualize MOX sensor data and to validate the LOD estimates.

JTD Keywords: Metal oxide sensors, Partial least squares, Orthogonal projection to latent structures, Maximum likelihood principal component regression, Limit of detection, Temperature modulation

Metal oxide semiconductor sensors are limited by their low selectivity, high power consumption and temporal drift. This paper proposes a novel discontinuous temperature modulation operation mode characterized by on-demand measurements and periodic warm-up cycles. The performance of two sets of FIS SB-500-12 sensors, one group continuously operated and the other group discontinuously operated, was compared in a scenario of carbon monoxide detection at low concentrations for five consecutive days. Results showed that the discontinuous operating mode moderately increased the prediction error and the limit of detection but was advantageous in terms of energy savings (up to 60% with respect to the continuous temperature modulation mode).

JTD Keywords: Discontinuous operation, Duty-cycling, Low power, MOX sensors, Temperature modulation

Abstract Shifts in working temperature are an important issue that prevents the successful transfer of calibration models from one chemical instrument to another. This effect is of special relevance when working with gas sensor arrays modulated in temperature. In this paper, we study the use of multivariate techniques to transfer the calibration model from a temperature modulated gas sensor array to another when a global change of temperature occurs. To do so, we built 12 identical master sensor arrays composed of three different types of commercial Figaro sensors and acquired a dataset of sensor responses to three pure substances (ethanol, acetone and butanone) dosed at 7 concentrations. The master arrays are then shifted in temperature (from −50 to 50 °C, ΔT = 10 °C) and considered as slave arrays. Data correction is performed for an increasing number of transfer samples with 4 different calibration transfer techniques: Direct Standardization, Piece-wise Direct Standardization, Orthogonal Signal Correction and Generalized Least Squares Weighting. In order to evaluate the performance of the calibration transfer, we compare the Root Mean Square Error of Prediction (RMSEP) of master and slave arrays, for each instrument correction. Best results are obtained from Piece-wise Direct standardization, which exhibits the lower RMSEP values after correction for the smaller number of transfer samples.

JTD Keywords: Calibration transfer, Gas sensor array, MOX, Temperature modulation

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. Results are obtained in real frigorific storage conditions: that is, at low measurement temperatures with variations of relative humidity.

JTD Keywords: Gas sensors, Electronic nose, Spoilage process, Temperature modulation, Bream sparus-aurata, Electronic nose, Freshness, Quality, Sardines, Storage

Metal oxide (MOX) gas sensors have been widely used for years. Temperature modulation of gas sensors is as an alternative to increase their sensitivity and selectivity to different gas species. In order to enhance the extraction of useful information from this kind of signals, data processing techniques are needed. In this work, the use of self-modelling curve resolution techniques, in particular multivariate curve resolution-alternating least squares (MCR-ALS), is presented for the analysis of these signals. First, the performance of MCR in a synthetic dataset generated from temperature-modulated gas sensor response models has been evaluated, showing good results both in the resolution of gas mixtures and in the determination of concentration/sensitivity profiles. Secondly, experimental confirmation of previously obtained conclusions is attempted using temperature-modulated MOX sensors together with MCR-ALS for the analysis of carbon monoxide (CO) and methane (CH4) gas mixtures in dry air. Results allow confirming the possibility of using the proposed approach as a quantitative technique for gas mixtures analysis, and also reveal some limitations.

JTD Keywords: Temperature modulation, Multivariate curve resolution, MCR-ALS, Metal oxide sensors

This paper presents a chemical sensing system that takes inspiration from the combination of sensory diversity and redundancy at the olfactory epithelium to enhance the chemical information obtained from the odorants. The system is based on commercial MOS sensors and achieves, first, diversity trough different types of MOS along with modulation of their temperatures, and second redundancy including 12 MOS sensors for each type (12×8) combined with a high-speed multiplexing system that allows connecting 16 load resistors with each and every one of the 96 sensors in about two seconds. Exposition of the system to ethanol, ammonia, and acetone at different concentrations shows how the system is able to capture a large amount of information of the identity and the concentration of the odorant.

JTD Keywords: Gas sensor array, Biologically inspired system, Redundancy, Diversity, MOX sensors, Temperature modulation