by Keyword: Limit of detection
Burgués, J., Jiménez-Soto, J. M., Marco, S., (2018). Estimation of the limit of detection in semiconductor gas sensors through linearized calibration models Analytica Chimica Acta 1013, 13-25
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.
Keywords: Semiconductor gas sensors, Metal-oxide sensors, Limit of detection, Non-linear, Humidity interference, Temperature modulation
Burgués, Javier, Marco, Santiago, (2018). Multivariate estimation of the limit of detection by orthogonal partial least squares in temperature-modulated MOX sensors Analytica Chimica Acta 1019, 49-64
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.
Keywords: Metal oxide sensors, Partial least squares, Orthogonal projection to latent structures, Maximum likelihood principal component regression, Limit of detection, Temperature modulation
Fonollosa, Jordi, Vergara, Alexander, Huerta, R., Marco, Santiago, (2014). Estimation of the limit of detection using information theory measures Analytica Chimica Acta 810, 1-9
Abstract Definitions of the limit of detection (LOD) based on the probability of false positive and/or false negative errors have been proposed over the past years. Although such definitions are straightforward and valid for any kind of analytical system, proposed methodologies to estimate the LOD are usually simplified to signals with Gaussian noise. Additionally, there is a general misconception that two systems with the same LOD provide the same amount of information on the source regardless of the prior probability of presenting a blank/analyte sample. Based upon an analogy between an analytical system and a binary communication channel, in this paper we show that the amount of information that can be extracted from an analytical system depends on the probability of presenting the two different possible states. We propose a new definition of LOD utilizing information theory tools that deals with noise of any kind and allows the introduction of prior knowledge easily. Unlike most traditional LOD estimation approaches, the proposed definition is based on the amount of information that the chemical instrumentation system provides on the chemical information source. Our findings indicate that the benchmark of analytical systems based on the ability to provide information about the presence/absence of the analyte (our proposed approach) is a more general and proper framework, while converging to the usual values when dealing with Gaussian noise.
Keywords: Limit of detection, Information theory, Mutual information, Heteroscedasticity, False positive/negative errors, Gas discrimination and quantification
Fonollosa, Jordi, Fernérndez, Luis, Huerta, Ramón, Gutiérrez-Gálvez, Agustín, Marco, Santiago, (2013). Temperature optimization of metal oxide sensor arrays using Mutual Information Sensors and Actuators B: Chemical Elsevier 187, (0), 331-339
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.
Keywords: MOX gas sensor, Temperature optimization, Limit of detection, Mutual Information, E-nose, Sensor array, Information Theory, Chemical sensing
Caballero, D., Martinez, E., Bausells, J., Errachid, A., Samitier, J., (2012). Impedimetric immunosensor for human serum albumin detection on a direct aldehyde-functionalized silicon nitride surface Analytica Chimica Acta 720, 43-48
In this work we report the fabrication and characterization of a label-free impedimetric immunosensor based on a silicon nitride (Si 3N 4) surface for the specific detection of human serum albumin (HSA) proteins. Silicon nitride provides several advantages compared with other materials commonly used, such as gold, and in particular in solid-state physics for electronic-based biosensors. However, few Si 3N 4-based biosensors have been developed; the lack of an efficient and direct protocol for the integration of biological elements with silicon-based substrates is still one of its the main drawbacks. Here, we use a direct functionalization method for the direct covalent binding of monoclonal anti-HSA antibodies on an aldehyde-functionalized Si-p/SiO 2/Si 3N 4 structure. This methodology, in contrast with most of the protocols reported in literature, requires less chemical reagents, it is less time-consuming and it does not need any chemical activation. The detection capability of the immunosensor was tested by performing non-faradaic electrochemical impedance spectroscopy (EIS) measurements for the specific detection of HSA proteins. Protein concentrations within the linear range of 10 -13-10 -7M were detected, showing a sensitivity of 0.128Î©Î¼M -1 and a limit of detection of 10 -14M. The specificity of the sensor was also addressed by studying the interferences with a similar protein, bovine serum albumin. The results obtained show that the antibodies were efficiently immobilized and the proteins detected specifically, thus, establishing the basis and the potential applicability of the developed silicon nitride-based immunosensor for the detection of proteins in real and more complex samples.
Keywords: Aldehyde, Electrochemical impedance spectroscopy, Human serum albumin, Immunosensor, Silicon nitride, Bovine serum albumins, Chemical reagents, Complex samples, Covalent binding, Detection capability, Electrochemical impedance, Electrochemical impedance spectroscopy measurements, Functionalizations, Human serum albumins, Impedimetric immunosensors, Label free, Limit of detection, Linear range, Protein concentrations, Silicon-based, Specific detection, Aldehydes