Empiric Unsupervised Drifts Correction Method of Electrochemical Sensors for in Field Nitrogen Dioxide Monitoring.

This paper investigates the long term drift phenomenon affecting electrochemical sensors used in real environmental conditions to monitor the nitrogen dioxide concentration [NO2]. Electrochemical sensors are low-cost gas sensors able to detect pollutant gas at part per billion level and may be employed to enhance the air quality monitoring networks. However, they suffer from many forms of drift caused by climatic parameter variations, interfering gases and aging. Therefore, they require frequent, expensive and time-consuming calibrations, which constitute the main obstacle to the exploitation of these kinds of sensors. This paper proposes an empirical, linear and unsupervised drift correction model, allowing to extend the time between two successive full calibrations. First, a calibration model is established based on multiple linear regression. The influence of the air temperature and humidity is considered. Then, a correction model is proposed to solve the drift related to age issue. The slope and the intercept of the correction model compensate the change over time of the sensors' sensitivity and baseline, respectively. The parameters of the correction model are identified using particle swarm optimization (PSO). Data considered in this work are continuously collected onsite close to a highway crossing Metz City (France) during a period of 6 months (July to December 2018) covering almost all the climatic conditions in this region. Experimental results show that the suggested correction model allows maintaining an adequate [NO2] estimation accuracy for at least 3 consecutive months without needing any labeled data for the recalibration.

Development of an electrochemical biosensor for impedimetric detection of tetracycline in milk.

ABSTRACT: This study dealt with the fabrication of an impedimetric biosensor based on nanomaterial modified with pencil graphite electrode for the detection of tetracycline (TET) in milk samples. For response of the impedimetric aptasensor to be improved, the influence of different parameters (immobilization time of reduced grapheme oxide, time of aptamer, and TET binding, and concentration of aptamer) was optimized. In optimum conditions, the aptasensor provided a concentration range within 1 × 10-16 - 1 × 10-6 M and with a limit of detection of 3 × 10-17 M TET. The proposed impedimetric aptasensor was then used in milk samples analysis, and the acceptable recovery was achieved ranging from 92.8 to 102.1%. According to this study, the combination of an aptamer and electrochemical impedance spectroscopy is a promising method for detection of TET in milk samples with high reproducibility and stability.

An impedimetric aptasensor for ultrasensitive detection of Penicillin G based on the use of reduced graphene oxide and gold nanoparticles.

The authors describe an impedimetric aptasensor for Penicillin G (PEN) which is an important antibiotic. The method is based on the use of a pencil graphite electrode (PGE) modified with reduced graphene oxide (RGO) and gold nanoparticles (GNPs) for ultrasensitive detection of PEN. The morphology of a bare PGE, RGO/PGE, and GNP/RGO/PGE, and the functional groups on graphene oxide (GO) and RGO were studied using scanning electron microscopy and Fourier transform infrared spectroscopy. Electrochemical impedance spectroscopy was used for detection of PEN by measuring the charge transfer resistance (Rct). Also, cyclic voltammetry was recorded at potential range of 0.30 to +0.70 V for PGE treatment. This aptamer-based assay has a wide linear range that extends from 1.0 fM to 10 µM, and a limit of detection as low as 0.8 fM. The method was applied to the determination of PEN in spiked milk from cow, sheep, goat and water buffalo. Recoveries ranged from 92% to 104%. The assay is fast, ultrasensitive, high reproducible, and selective over antibiotics such as streptomycin, tetracycline, and sulfadiazine. Graphical abstract Schematic presentation of an impedimetric aptasensor for Penicillin G antibiotic using a pencil graphite electrode (PGE) modified with reduced graphene oxide (RGO) and gold nanoparticles (GNPs). This aptamer based assay has limit of detection as low as 0.8 fM.

Support Vector Machine Regression for Calibration Transfer between Electronic Noses Dedicated to Air Pollution Monitoring.

Recently, the emergence of low-cost sensors have allowed electronic noses to be considered for densifying the actual air pollution monitoring networks in urban areas. Electronic noses are affected by changes in environmental conditions and sensor drifts over time. Therefore, they need to be calibrated periodically and also individually because the characteristics of identical sensors are slightly different. For these reasons, the calibration process has become very expensive and time consuming. To cope with these drawbacks, calibration transfer between systems constitutes a satisfactory alternative. Among them, direct standardization shows good efficiency for calibration transfer. In this paper, we propose to improve this method by using kernel SPXY (sample set partitioning based on joint x-y distances) for data selection and support vector machine regression to match between electronic noses. The calibration transfer approach introduced in this paper was tested using two identical electronic noses dedicated to monitoring nitrogen dioxide. Experimental results show that our method gave the highest efficiency compared to classical direct standardization.

Enhanced response of a proteinase K-based conductometric biosensor using nanoparticles.

Proteinases are involved in a multitude of important physiological processes, such as protein metabolism. For this reason, a conductometric enzyme biosensor based on proteinase K was developed using two types of nanoparticles (gold and magnetic). The enzyme was directly adsorbed on negatively charged nanoparticles and then deposited and cross-linked on a planar interdigitated electrode (IDE). The biosensor was characterized with bovine serum albumin (BSA) as a standard protein. Higher sensitivity was obtained using gold nanoparticles. The linear range for BSA determination was then from 0.5 to 10 mg/L with a maximum response of 154 µs. These results are greater than that found without any nanoparticles (maximum response of 10 µs). The limit of detection (LOD) was 0.3 mg/L. An inter-sensor reproducibility of 3.5% was obtained.

Comparative study of conductometric glucose biosensor based on gold and on magnetic nanoparticles.

The aim of this study was to show the feasibility and the performances of nanoparticle biosensing. A glucose conductometric biosensor was developed using two types of nanoparticles (gold and magnetic), glucose oxidase (GOD) being adsorbed on PAH (poly(allylamine hydrochloride)) modified nanoparticles, deposited on a planar interdigitated electrode (IDEs). The best sensitivities for glucose detection were obtained with magnetic nanoparticles (70 µM/mM and 3 µM of detection limit) compared to 45 µM/mM and 9 µM with gold nanoparticles and 30 µM/mM and 50 µM with GOD directly cross-linked on IDEs. When stored in phosphate buffer (20 mM, pH 7.3) at 4 °C, the biosensor showed good stability for more than 12 days.

Electrosprayed metal oxide semiconductor films for sensitive and selective detection of hydrogen sulfide.

Semiconductor metal oxide films of copper-doped tin oxide (Cu-SnO(2)), tungsten oxide (WO(3)) and indium oxide (In(2)O(3)) were deposited on a platinum coated alumina substrate employing the electrostatic spray deposition technique (ESD). The morphology studied with scanning electron microscopy (SEM) and atomic force microscopy (AFM) shows porous homogeneous films comprising uniformly distributed aggregates of nano particles. The X-ray diffraction technique (XRD) proves the formation of crystalline phases with no impurities. Besides, the Raman cartographies provided information about the structural homogeneity. Some of the films are highly sensitive to low concentrations of H(2)S (10 ppm) at low operating temperatures (100 and 200 °C) and the best response in terms of R(air)/R(gas) is given by Cu-SnO(2) films (2500) followed by WO(3) (1200) and In(2)O(3) (75). Moreover, all the films exhibit no cross-sensitivity to other reducing (SO(2)) or oxidizing (NO(2)) gases.

Meat quality assessment by electronic nose (machine olfaction technology).

Over the last twenty years, newly developed chemical sensor systems (so called "electronic noses") have made odor analyses possible. These systems involve various types of electronic chemical gas sensors with partial specificity, as well as suitable statistical methods enabling the recognition of complex odors. As commercial instruments have become available, a substantial increase in research into the application of electronic noses in the evaluation of volatile compounds in food, cosmetic and other items of everyday life is observed. At present, the commercial gas sensor technologies comprise metal oxide semiconductors, metal oxide semiconductor field effect transistors, organic conducting polymers, and piezoelectric crystal sensors. Further sensors based on fibreoptic, electrochemical and bi-metal principles are still in the developmental stage. Statistical analysis techniques range from simple graphical evaluation to multivariate analysis such as artificial neural network and radial basis function. The introduction of electronic noses into the area of food is envisaged for quality control, process monitoring, freshness evaluation, shelf-life investigation and authenticity assessment. Considerable work has already been carried out on meat, grains, coffee, mushrooms, cheese, sugar, fish, beer and other beverages, as well as on the odor quality evaluation of food packaging material. This paper describes the applications of these systems for meat quality assessment, where fast detection methods are essential for appropriate product management. The results suggest the possibility of using this new technology in meat handling.