Measurement uncertainty estimation in amperometric sensors: a tutorial review

Development and machine learning-based calibration of low-cost multiparametric stations for the measurement of CO2 and CH4 in air

The pressing issue of atmospheric pollution has prompted the exploration of affordable methods for measuring and monitoring air contaminants as complementary techniques to standard methods, able to produce high-density data in time and space. The main challenge of this low-cost approach regards the in-field accuracy and reliability of the sensors. This study presents the development of low-cost stations for high-time resolution measurements of CO2 and CH4 concentrations calibrated via an in-field machine learning-based method. The calibration models were built based on measurements parallelly performed with the low-cost sensors and a CRDS analyzer for CO2 and CH4 as reference instrument, accounting for air temperature and relative humidity as external variables. To ensure versatility across locations, diversified datasets were collected, consisting of measurements performed in various environments and seasons. The calibration models, trained with 70 % for modeling, 15 % for validation, and 15 % for testing, demonstrated robustness with CO2 and CH4 predictions achieving R2 values from 0.8781 to 0.9827 and 0.7312 to 0.9410, and mean absolute errors ranging from 3.76 to 1.95 ppm and 0.03 to 0.01 ppm, for CO2 and CH4, respectively. These promising results pave the way for extending these stations to monitor additional air contaminants, like PM, NOx, and CO through the same calibration process, integrating them with remote data transmission modules to facilitate real-time access, control, and processing for end-users.

Electrochemical Monitoring of Heterogeneous Peroxygenase Reactions Unravels LPMO Kinetics

Biological conversion of plant biomass depends on peroxygenases and peroxidases acting on insoluble polysaccharides and lignin. Among these are cellulose- and hemicellulose-degrading lytic polysaccharide monooxygenases (LPMOs), which have revolutionized our concept of biomass degradation. Major obstacles limiting mechanistic and functional understanding of these unique peroxygenases are their complex and insoluble substrates and the hard-to-measure H2O2 consumption, resulting in the lack of suitable kinetic assays. We report a versatile and robust electrochemical method for real-time monitoring and kinetic characterization of LPMOs and other H2O2-dependent interfacial enzymes based on a rotating disc electrode for the sensitive and selective quantitation of H2O2 at biologically relevant concentrations. The H2O2 sensor works in suspensions of insoluble substrates as well as in homogeneous solutions. Our characterization of multiple LPMOs provides unprecedented insights into the substrate specificity, kinetics, and stability of these enzymes. High turnover and total turnover numbers demonstrate that LPMOs are fast and durable biocatalysts.

Characterization of Fiber-Optic Vector Magnetic Field Sensors Based on the Magneto-Strictive Effect

Fiber-optic magnetic field sensors have garnered considerable attention in the field of marine monitoring due to their compact size, robust anti-electromagnetic interference capabilities, corrosion resistance, high sensitivity, ease of multiplexing and integration, and potential for large-scale sensing networks. To enable the detection of marine magnetic field vector information, we propose an optical fiber vector magnetic field sensor that integrates three single-axis sensors in an orthogonal configuration. Theoretical analysis and experimental verification are conducted to investigate its magnetic field and temperature sensing characteristics, and a sensitivity matrix is established to address the cross-sensitivity between the magnetic field and temperature; experimental tests were conducted to assess the vector response of the three-dimensional (3D) vector sensor across the three orthogonal axes; the obtained experimental results illustrate the commendable magnetic field vector response exhibited by the sensor in the orthogonal axes, enabling precise demodulation of vector magnetic field information. This sensor presents several advantages, including cost-effectiveness, easy integration, and reliability vectorially. Consequently, it holds immense potential for critical applications in marine magnetic field network detection.

A state-of-the-art review on the nanomaterial-based sensor for detection of venlafaxine

Venlafaxine (denoted as VFX), a member of the most extensively prescribed antidepressants, is used to handle major depressive disorder, panic disorder and anxiety. This medication affects brain chemistry, which could cause an imbalance in depressed people. VFX and its metabolites, on the other hand, are pollutants in the water environment. Through movement and transformation in several procedures like adsorption, photolysis, hydrolysis and biodegradation, they have harmed living creatures, resulting in the enhancement of diverse active chemicals found in the environment. As a result, determining VFX at modest concentrations with excellent sensitivity, specificity and repeatability are critical. To quantify VFX, various analytical methodologies have been developed. Electroanalytical processes, on the other hand, have piqued interest because of their superior benefits over traditional techniques such as speed, sensitivity, directness and affordability. Subsequently, the purpose of this article is to show how to determine VFX electrochemically using a wide range of electrodes, including CPE, GCE, MCE, SPE, PGE and ISE.

Development of Air Quality Boxes Based on Low-Cost Sensor Technology for Ambient Air Quality Monitoring

Analyses of the relationships between climate, air substances and health usually concentrate on urban environments because of increased urban temperatures, high levels of air pollution and the exposure of a large number of people compared to rural environments. Ongoing urbanization, demographic ageing and climate change lead to an increased vulnerability with respect to climate-related extremes and air pollution. However, systematic analyses of the specific local-scale characteristics of health-relevant atmospheric conditions and compositions in urban environments are still scarce because of the lack of high-resolution monitoring networks. In recent years, low-cost sensors (LCS) became available, which potentially provide the opportunity to monitor atmospheric conditions with a high spatial resolution and which allow monitoring directly at vulnerable people. In this study, we present the atmospheric exposure low-cost monitoring (AELCM) system for several air substances like ozone, nitrogen dioxide, carbon monoxide and particulate matter, as well as meteorological variables developed by our research group. The measurement equipment is calibrated using multiple linear regression and extensively tested based on a field evaluation approach at an urban background site using the high-quality measurement unit, the atmospheric exposure monitoring station (AEMS) for meteorology and air substances, of our research group. The field evaluation took place over a time span of 4 to 8 months. The electrochemical ozone sensors (SPEC DGS-O3: R²: 0.71-0.95, RMSE: 3.31-7.79 ppb) and particulate matter sensors (SPS30 PM1/PM2.5: R²: 0.96-0.97/0.90-0.94, RMSE: 0.77-1.07 µg/m³/1.27-1.96 µg/m³) showed the best performances at the urban background site, while the other sensors underperformed tremendously (SPEC DGS-NO2, SPEC DGS-CO, MQ131, MiCS-2714 and MiCS-4514). The results of our study show that meaningful local-scale measurements are possible with the former sensors deployed in an AELCM unit.

Improving the Quality of Measurements Made by Alphasense NO2 Non-Reference Sensors Using the Mathematical Methods

Conventional NO₂ monitoring devices are relatively cumbersome, expensive, and have a relatively high-power consumption that limits their use to fixed sites. On the other hand, they offer high-quality measurements. In contrast, the low-cost NO₂ sensors offer greater flexibility, are smaller, and allow greater coverage of the area with the measuring devices. However, their disadvantage is much lower accuracy. The main goal of this study was to investigate the measurement data quality of NO2-B43F Alphasense sensors. The measurement performance analysis of Alphasense NO2-B43F sensors was conducted in two research areas in Poland. Sensors were placed near fixed, professional air quality monitoring stations, carrying out measurements based on reference methods, in the following periods: July-November, and December-May. Results of the study show that without using sophisticated correction methods, the range of measured air pollution concentrations may be greater than their actual values in ambient air-measured in the field by fixed stations. In the case of summer months (with air temperature over 30 °C), the long-term mean absolute percentage error was over 150% and the sensors, using the methods recommended by the manufacturer, in the case of high temperatures could even show negative values. After applying the mathematical correction functions proposed in this article, it was possible to significantly reduce long-term errors (to 40-70% per month, regardless of the location of the measurements) and eliminate negative measurement values. The proposed method is based on the recalculation of the raw measurement, air temperature, and air RH and does not require the use of extensive analytical tools.

Experimental and Theoretical Study on the Internal Convective and Radiative Heat Transfer Coefficients for a Vertical Wall in a Residential Building

Experimental studies on internal convective (CHTC) and radiative (RHTC) heat transfer coefficients are very rarely conducted in real conditions during the normal use of buildings. This study presents the results of measurements of CHTC and RHTC for a vertical wall, taken in a selected room of a single-family building during its everyday use. Measurements were performed using HFP01 heat flux plates, Pt1000 sensors for internal air and wall surface temperatures and a globe thermometer for mean radiant temperature measured in 10 min intervals. Measured average CHTC and RHTC amounted to 1.15 W/m2K and 5.45 W/m2K, compared to the 2.50 W/m2K and 5.42 W/m2K recommended by the EN ISO 6946, respectively. To compare with calculated CHTC, 14 correlations based on the temperature difference were applied. Obtained values were from 1.31 W/m2K (given by Min et al.) to 3.33 W/m2K (Wilkes and Peterson), and in all cases were greater than the 1.15 W/m2K from measurements. The average value from all models amounted to 2.02 W/m2K, and was greater than measurements by 75.6%. The quality of models was also estimated using average absolute error (AAE), average biased error (ABE), mean absolute error (MAE) and mean bias error (MBE). Based on these techniques, the model of Fohanno and Polidori was identified as the best with AAE = 68%, ABE = 52%, MAE = 0.41 W/m2K and MBE = 0.12 W/m2K.

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.

Electrochemical biosensor for glycine detection in biological fluids

We present herein the very first amperometric biosensor for the quantitative determination of glycine in diverse biological fluids. The biosensor is based on a novel quinoprotein that catalyzes the oxidation of glycine with high specificity. This process is coupled to the redox conversion of Prussian blue in the presence of hydrogen peroxide originating from the enzymatic reaction. The optimized tailoring of the biosensor design consists of the effective encapsulation of the quinoprotein in a chitosan matrix with the posterior addition of an outer Nafion layer, which is here demonstrated to suppress matrix interference. This is particularly important in the case of ascorbic acid, which is known to influence the redox behavior of the Prussian blue. The analytical performance of the biosensor demonstrates fast response time (<7 s), acceptable reversibility, reproducibility, and stability (<6% variation) as well as a wide linear range of response (25-500 μM) that covers healthy (and even most unhealthy) physiological levels of glycine in blood/serum, urine and sweat. A total of 6 real samples from healthy patients and animals were analyzed: two serum, two urine and two sweat samples. The results were validated via commercially available fluorescence kit, displaying discrepancy of less than 9% in all the samples. The unique analytical features and effortless preparation of the new glycine biosensor position it at the forefront of current technologies towards decentralized clinical applications and sport performance monitoring.

Electrochemical nitrite sensing for urine nitrification

Sensing nitrite in-situ in wastewater treatment processes could greatly simplify process control, especially during treatment of high-strength nitrogen wastewaters such as digester supernatant or, as in our case, urine. The two technologies available today, i.e. an on-line nitrite analyzer and a spectrophotometric sensor, have strong limitations such as sample preparation, cost of ownership and strong interferences. A promising alternative is the amperometric measurement of nitrite, which we assessed in this study. We investigated the sensor in a urine nitrification reactor and in ex-situ experiments. Based on theoretical calculations as well as a practical approach, we determined that the critical nitrite concentrations for nitrite oxidizing bacteria lie between 12 and 30 mg_N/L at pH 6 to 6.8. Consequently, we decided that the sensor should be able to reliably measure concentrations up to 50 mg_N/L, which is about double the value of the critical nitrite concentration. We found that the influences of various ambient conditions, such as temperature, pH, electric conductivity and aeration rate, in the ranges expected in urine nitrification systems, are negligible. For low nitrite concentrations, as expected in municipal wastewater treatment, the tested amperometric nitrite sensor was not sufficiently sensitive. Nevertheless, the sensor delivered reliable measurements for nitrite concentrations of 5-50 mg_N/L or higher. This means that the amperometric nitrite sensor allows detection of critical nitrite concentrations without difficulty in high-strength nitrogen conversion processes, such as the nitrification of human urine.

A Microdroplet-Based Colorimetric Sensing Platform on a CMOS Imager Chip

Interest in mobile chemical sensors is on the rise, but significant challenges have restricted widespread adoption into commercial devices. To be useful these sensors need to have a predictable response, easy calibration, and be integrable with existing technology, preferably fitting on a single chip. With respect to integration, the CMOS imager makes an attractive template for an optoelectronic sensing platform. Demand for smartphones with cameras has driven down the price and size of CMOS imagers over the past decade. The low cost and accessibility of these powerful tools motivated us to print chemical sensing elements directly on the surface of the photodiode array. These printed colorimetric microdroplets are composed of a nonvolatile solvent so they remain in a uniform and homogeneous solution phase, an ideal medium for chemical interactions and optical measurements. By imaging microdroplets on the CMOS imager surface we eliminated the need for lenses, dramatically scaling down the size of the sensing platform to a single chip. We believe the technique is generalizable to many colorimetric formulations, and as an example we detected gaseous ammonia with Cu(II). Limits of detection as low as 27 ppb and sensor-to-sensor variation of less than 10% across multiple printed arrays demonstrated the high sensitivity and repeatability of this approach. Sensors generated this way could share a single calibration, greatly reducing the complexity of incorporating chemical sensors into mobile devices. Additional testing showed the sensor can be reused and has good selectivity; sensitivity and dynamic range can be tuned by controlling droplet size.

Recent Advances in the Electrochemical Sensing of Venlafaxine: An Antidepressant Drug and Environmental Contaminant

Venlafaxine (VEN), as one of the popular anti-depressants, is widely utilized for the treatment of major depressive disorder, panic disorder, as well as anxiety. This drug influences the chemicals in the brain, which may result in imbalance in depressed individuals. However, venlafaxine and its metabolites are contaminants in water. They have exerted an adverse influence on living organisms through their migration and transformation in various forms of adsorption, photolysis, hydrolysis, and biodegradation followed by the formation of various active compounds in the environment. Hence, it is crucial to determine VEN with low concentrations in high sensitivity, specificity, and reproducibility. Some analytical techniques have been practically designed to quantify VEN. However, electroanalytical procedures have been of interest due to the superior advantages in comparison to conventional techniques, because such methods feature rapidity, simplicity, sensitivity, and affordability. Therefore, this mini-review aims to present the electrochemical determination of VEN with diverse electrodes, such as carbon paste electrodes, glassy carbon electrodes, mercury-based electrodes, screen-printed electrodes, pencil graphite electrodes, and ion-selective electrodes.

A Study on the Uncertainty of a Laser Triangulator Considering System Covariances

A laser triangulation system, which is composed of a camera and a laser, calculates distances between objects intersected by the laser plane. Even though there are commercial triangulation systems, developing a new system allows the design to be adapted to the needs, in addition to allowing dimensions or processing times to be optimized; however the disadvantage is that the real accuracy is not known. The aim of the research is to identify and discuss the relevance of the most significant error sources in laser triangulator systems, predicting their error contribution to the final joint measurement accuracy. Two main phases are considered in this study, namely the calibration and measurement processes. The main error sources are identified and characterized throughout both phases, and a synthetic error propagation methodology is proposed to study the measurement accuracy. As a novelty in uncertainty analysis, the present approach encompasses the covariances of correlated system variables, characterizing both phases for a laser triangulator. An experimental methodology is adopted to evaluate the measurement accuracy in a laser triangulator, comparing it with the values obtained with the synthetic error propagation methodology. The relevance of each error source is discussed, as well as the accuracy of the error propagation. A linearity value of 40 µm and maximum error of 0.6 mm are observed for a 100 mm measuring range, with the camera calibration phase being the main error contributor.

Recent Developments of Flexible and Stretchable Electrochemical Biosensors

The skyrocketing popularity of health monitoring has spurred increasing interest in wearable electrochemical biosensors. Compared with the traditionally rigid and bulky electrochemical biosensors, flexible and stretchable devices render a unique capability to conform to the complex, hierarchically textured surfaces of the human body. With a recognition element (e.g., enzymes, antibodies, nucleic acids, ions) to selectively react with the target analyte, wearable electrochemical biosensors can convert the types and concentrations of chemical changes in the body into electrical signals for easy readout. Initial exploration of wearable electrochemical biosensors integrates electrodes on textile and flexible thin-film substrate materials. A stretchable property is needed for the thin-film device to form an intimate contact with the textured skin surface and to deform with various natural skin motions. Thus, stretchable materials and structures have been exploited to ensure the effective function of a wearable electrochemical biosensor. In this mini-review, we summarize the recent development of flexible and stretchable electrochemical biosensors, including their principles, representative application scenarios (e.g., saliva, tear, sweat, and interstitial fluid), and materials and structures. While great strides have been made in the wearable electrochemical biosensors, challenges still exist, which represents a small fraction of opportunities for the future development of this burgeoning field.

Review of the Performance of Low-Cost Sensors for Air Quality Monitoring

A growing number of companies have started commercializing low-cost sensors (LCS) that are said to be able to monitor air pollution in outdoor air. The benefit of the use of LCS is the increased spatial coverage when monitoring air quality in cities and remote locations. Today, there are hundreds of LCS commercially available on the market with costs ranging from several hundred to several thousand euro. At the same time, the scientific literature currently reports independent evaluation of the performance of LCS against reference measurements for about 110 LCS. These studies report that LCS are unstable and often affected by atmospheric conditions—cross-sensitivities from interfering compounds that may change LCS performance depending on site location. In this work, quantitative data regarding the performance of LCS against reference measurement are presented. This information was gathered from published reports and relevant testing laboratories. Other information was drawn from peer-reviewed journals that tested different types of LCS in research studies. Relevant metrics about the comparison of LCS systems against reference systems highlighted the most cost-effective LCS that could be used to monitor air quality pollutants with a good level of agreement represented by a coefficient of determination R2 > 0.75 and slope close to 1.0. This review highlights the possibility to have versatile LCS able to operate with multiple pollutants and preferably with transparent LCS data treatment.

Electrospun Nanofibers for Label-Free Sensor Applications

Electrospinning is a simple, low-cost and versatile method for fabricating submicron and nano size fibers. Due to their large surface area, high aspect ratio and porous structure, electrospun nanofibers can be employed in wide range of applications. Biomedical, environmental, protective clothing and sensors are just few. The latter has attracted a great deal of attention, because for biosensor application, nanofibers have several advantages over traditional sensors, including a high surface-to-volume ratio and ease of functionalization. This review provides a short overview of several electrospun nanofibers applications, with an emphasis on biosensor applications. With respect to this area, focus is placed on label-free sensors, pertaining to both recent advances and fundamental research. Here, label-free sensor properties of sensitivity, selectivity, and detection are critically evaluated. Current challenges in this area and prospective future work is also discussed.

Comparative validation of amperometric and optical analyzers of dissolved oxygen: a case study

A comprehensive comparative validation for two different types of dissolved oxygen (DO) analyzers, amperometric and optical, is presented on two representative commercial DO analyzers. A number of performance characteristics were evaluated including drift, intermediate precision, accuracy of temperature compensation, accuracy of reading (under different measurement conditions), linearity, flow dependence of the reading, repeatability (reading stability), and matrix effects of dissolved salts. The matrix effects on readings in real samples were evaluated by analyzing the dependence of the reading on salt concentration (at saturation concentration of DO). The analyzers were also assessed in DO measurements of a number of natural waters. The uncertainty contributions of the main influencing parameters were estimated under different experimental conditions. It was found that the uncertainties of results for both analyzers are quite similar but the contributions of the uncertainty sources are different. Our results imply that the optical analyzer might not be as robust as is commonly assumed; however, it has better reading stability, lower stirring speed dependence, and typically requires less maintenance. On the other hand, the amperometric analyzer has a faster response and wider linear range. Both analyzers seem to have issues with the accuracy of temperature compensation. The approach described in this work will be useful to practitioners carrying out DO measurements for ensuring reliability of their measurements.

Review of Portable and Low-Cost Sensors for the Ambient Air Monitoring of Benzene and Other Volatile Organic Compounds

This article presents a literature review of sensors for the monitoring of benzene in ambient air and other volatile organic compounds. Combined with information provided by stakeholders, manufacturers and literature, the review considers commercially available sensors, including PID-based sensors, semiconductor (resistive gas sensors) and portable on-line measuring devices as for example sensor arrays. The bibliographic collection includes the following topics: sensor description, field of application at fixed sites, indoor and ambient air monitoring, range of concentration levels and limit of detection in air, model descriptions of the phenomena involved in the sensor detection process, gaseous interference selectivity of sensors in complex VOC matrix, validation data in lab experiments and under field conditions.

Pyrene-Capped CdSe@ZnS Nanoparticles as Sensitive Flexible Oxygen Sensors in Non-Aqueous Media

A flexible, highly sensitive sensor of oxygen in non-aqueous solvents is described. It consists of CdSe/ZnS nanoparticles decorated with a considerable number of pyrene units, thus making the formation of the pyrene excimer possible. The emission of the pyrene excimer and that of the nanoparticle are suitably separated from each other and also from the excitation wavelength. This sensor can be applied as a ratiometric oxygen sensor by using the linear response of the pyrene excimer lifetime combined with the linear response of the nanoparticle excited state lifetime. This nanohybrid has been assayed in seven media with different dielectric constants and viscosities over the whole oxygen concentration range. In addition, the sensor versatility provides an easy way for monitoring oxygen diffusion through systems.

Non-obvious Problems in Clark Electrode Application at Elevated Temperature and Ways of Their Elimination

Well-known cause of frequent failures of closed oxygen sensors is the appearance of gas bubbles in the electrolyte. The problem is traditionally associated with insufficient sealing of the sensor that is not always true. Study of a typical temperature regime of measurement system based on Clark sensor showed that spontaneous release of the gas phase is a natural effect caused by periodic warming of the sensor to a temperature of the test liquid. The warming of the sensor together with the incubation medium causes oversaturation of electrolyte by dissolved gases and the allocation of gas bubbles. The lower rate of sensor heating in comparison with the medium reduces but does not eliminate the manifestation of this effect. It is experimentally established, that with each cycle of heating of measuring system up to 37°C followed by cooling the volume of gas phase in the electrolyte (KCl; 60 g/L; 400  μ L) increased by 0.6  μ L approximately. Thus, during just several cycles it can dramatically degrade the characteristics of the sensor. A method was developed in which the oxygen sensor is heated in contact with the liquid, (depleted of dissolved gases), allowing complete exclusion of the above-mentioned effect.