Conventional Reference Electrode Research Articles

Dual-Purpose Aptamer-Based Sensors for Real-Time, Multiplexable Monitoring of Metabolites in Cell Culture Media.

The availability of high-frequency, real-time measurements of the concentrations of specific metabolites in cell culture systems will enable a deeper understanding of cellular metabolism and facilitate the application of good laboratory practice standards in cell culture protocols. However, currently available approaches to this end either are constrained to single-time-point and single-parameter measurements or are limited in the range of detectable analytes. Electrochemical aptamer-based (EAB) biosensors have demonstrated utility in real-time monitoring of analytes in vivo in blood and tissues. Here, we characterize a pH-sensing capability of EAB sensors that is independent of the specific target analyte of the aptamer sequence. We applied this dual-purpose EAB to the continuous measurement of pH and phenylalanine in several in vitro cell culture settings. The miniature EAB sensor that we developed exhibits rapid response times, good stability, high repeatability, and biologically relevant sensitivity. We also developed and characterized a leak-free reference electrode that mitigates the potential cytotoxic effects of silver ions released from conventional reference electrodes. Using the resulting dual-purpose sensor, we performed hourly measurements of pH and phenylalanine concentrations in the medium superfusing cultured epithelial tumor cell lines (A549, MDA-MB-23) and a human fibroblast cell line (MRC-5) for periods of up to 72 h. Our scalable technology may be multiplexed for high-throughput monitoring of pH and multiple analytes in support of the broad metabolic qualification of microphysiological systems.

A Solid Electrolyte RHE for Electrode Diagnosis of Proton Exchange Membrane Water Electrolyzers.

Reference electrode is the foundation of electrochemical study; thus, most electrode materials are tested in a three-electrode mode to acquire potential-dependent kinetics. However, it is difficult to directly use conventional reference electrodes to detect potential information in solid electrolyte devices due to their compact assembly structure. Therefore, the kinetic study of an electrochemical device faces challenges in precise identification of specific problems originating from the anode or cathode. Here, focusing on proton exchange membrane water electrolysis, we design a solid electrolyte reversible hydrogen electrode (SE-RHE), which can be used for electrode diagnosis under various operating conditions. Compared to the reference electrodes reported in the literature, which are mainly based on liquid electrolyte, the SE-RHE is highly sensitive and compatible, as well as easy to assemble. The potential deviation is less than ±0.5 mV, and the cell voltage derived from the electrode potential well reproduces the value that was directly measured with a deviation less than 0.2%. The reference electrode developed in this work enables the kinetic study of a specific electrode rather than the entire cell. For instance, an interesting observation is that the cathode shows distinct stability under stable and fluctuating operations. Differing from the high stability under stable operation, the cathode degrades significantly under fluctuating operations.

(General Student Poster Award Winner, 1st Place) Accelerated Estimation of Chemical and Sensory Liquid Attributes Using an AI-Assisted Electrochemical Electronic Tongue

Electronic tongues based on arrays of potentiometric sensors bears promises for enabling portable and fast analysis of complex liquids by leveraging low-selectivity and high-sensitivity of the inherent sensing materials. Thus, they have been studied and developed to target multiple applications, including analysis of chemical compositions or for untargeted quality control in the food industry. A key element to enable practical use of electronic tongues, however, has often been the analysis and interpretation of their combinatorial response due to the cross-sensitivity of the employed sensors. Indeed, disentangling the effect of multiple liquid constituents on the potentiometric response is the main associated challenge. The present contribution aims at studying the feasibility and accuracy of employing this class of sensors to both the quantification of multiple analytes in water as well as prediction of sensory attributes in coffee samples. A proof-of-concept system comprises an integrated array of miniaturized polymeric sensors and an electronic board records 15 differential voltages, produced by the interaction with both ionic and organic constituents of liquids, and can transmit them via Bluetooth to an external device. An automated pipeline performs pre-processing, hand-crafted feature extraction and training of machine learning models that can be then deployed on the cloud or edge device (e.g., smartphone). The same array can be then reconfigured to address a new specific task by leveraging new potentiometric data collection and applying the automated data analysis. In particular, the device presented herein employed 16 polymeric sensors that were electrodeposited on conventional electroless nickel immersion gold (ENIG) electrodes. The conductive polymers (PEDOT, PPy, PANI and PAPBA) were synthesized by chronoamperometry or cyclic voltammetry and enriched with doping agents for enhanced sensitivity. Differential voltages between these polymeric sensors were measured during the transition of the sensor array from a reference solution to a test solution, thereby obviating the need for a conventional reference electrode. Indeed, the use of low-selective sensors for potentiometric measurements does not require integration of reference electrodes, which are known to be unpractical for remote sensing applications. The analysis of the potentiometric response revealed deviations from linear sensitivities, showing non-Nernstian voltage trends when varying concentration of target analytes. Training data were obtained by alternatively immersing the sensor array in reference (120 s) and test (60 s) solutions continuously using an automated test rig. In addition to the conventional approach of measuring the equilibrium potential after a certain settling time, the complete evolution of the potentiometric signal in time could provide richer information that could be useful for building calibration models. Hence, hand-crafted features were extracted from time series recorded during sensor training in order to reduce the dimension of data and describe the complete voltage perturbation of the sensor during transition between reference and test solution. If exposed to enough “known liquid examples”, the sensor array can learn patterns to perform accelerated qualitative and quantitative analysis. The device has demonstrated enhanced discrimination of various mixtures and was proved able to predict beverage sensory properties after intensive training with samples with known sensory attributes. Firstly, the sensitivity to multiple ionic species was estimated in model mixtures obtained following an Orthogonal Experimental Design (OED) for a set of four metal ions, including Al3+, Cu2+, Na+ and Fe3+, and another set comprising Ca2+, Mg2+ and Na+. The former experiment demonstrated that non-linear regression models, such as a Random Forest of Extra Trees, can cope with non-linearity of the sensor response and yielded better performances than widely used multivariate regression model i.e., Multiple Linear Regression (MLR). The mean relative quantification error varied between 1% for Fe3+ and 44% for Na+ in the concentration range 1-10 mg/L. The second mixture set was used instead to unveil the cross-sensitive response of the sensor array, build a quantification model to predict major cations in mineral water and proving the importance of feature selection for data-driven sensors. Overall, the sensor showed comparable accuracy to ICP-MS (MRE 12-24%) but with a drastic reduction of cost and processing time. Finally, the same sensor array configuration was also used to test 12 coffee samples, which were also evaluated by a sensory panel through 5 taste attributes. Regression models were built to map instrument response to sensory data and Extra-Tree algorithm yielded the highest performances with a MRE varying from 8% to 21% depending on coffee sample and validation scheme. Thus, it was demonstrated that data-driven sensor arrays could be also valuable alternative tools for accelerated evaluation of beverage sensory characteristics and support food innovation processes. Figure 1

Leveraging an AI-Assisted Electrochemical Sensor Array to Visualize Digital Fingerprints of Complex Liquids

Electrochemical sensor arrays have shown potential for fast and untargeted chemical analysis of multi-component media, enabling simultaneous quantification of multiple analytes and estimation of liquid properties that could correlate with human sensory perception. In particular, potentiometric electronic tongues (e-tongues) have been explored as promising alternative tools for chemical analysis in various applications, ranging from traceability of goods to characterization of food products for quality control and innovation processes. The reduced complexity of non-selective sensor fabrication and the ease of potentiometric transduction make these devices suitable for portable and decentralized chemical analysis. However, the interpretation of the sensor array response has always been a challenge due to the inherent cross-sensitivity of the sensing materials and the corresponding combinatorial signals arising upon sensor interaction with a liquid. Machine learning can help recognizing and mapping signal patterns and various data processing, unsupervised and supervised techniques have been proposed to calibrate e-tongue devices. These methods usually require exposing the sensor array to a set of liquids with known properties that serve as training base to build a calibration model. Therefore, the quality and quantity of tests is crucial to boost sensor performances. Nevertheless, performing an extensive number of measurements could be extremely time-consuming and results to be tedious to achieve in practice for certain use-cases. In this context, advances in deep learning and machine learning models have shown potential to accelerate chemical and materials discovery when combined with high-throughput experimentation, highlighting the benefits of AI-assisted research practices. Moreover, the recent advent of multi-domain and multi-task models trained by self-supervision, so-called foundation models, bears also promises for extending learnt representations across multiple fields, thus counteracting the reduced data availability in certain applications, and benefiting from information exchange across domains. Thus, in the present contribution we propose extending this approach to data-driven chemical sensors. More specifically, we leverage transfer learning based on fingerprints pretrained in other domains to model new instrument/sensor data representations. Herein, we demonstrate how the output of a model system comprising an integrated electrochemical sensor array for analysis of multi-component liquids can be encoded as image representations to leverage existing deep learning computer vision models pretrained on large collections of image data. The models effectively extract features from these representations and feed specific model heads to perform downstream tasks. Firstly, an integrated sensor array comprising 16 polymeric sensors was fabricated through electrodeposition on conventional electroless nickel immersion gold (ENIG) electrodes. The conductive polymers (PEDOT, PPy, PANI and PAPBA) were synthesized by chronoamperometry or cyclic voltammetry in a three-electrode configuration and were enriched with doping agents for enhanced sensitivity. 15 linearly independent differential voltages between these polymeric sensors were measured during the transition of the sensor array from a reference solution to a test solution, thereby obviating the need for a conventional reference electrode. Indeed, the use of low-selective polymeric sensors for potentiometric measurements does not necessarily require integration of reference electrodes, which are known to be unpractical for remote sensing applications. Training data were obtained by alternatively immersing the sensor array in reference (120 s) and test (60 s) solutions continuously using an automated test rig. The 15 raw time-series data from the sensor array were processed and concatenated to yield a spectral response, which was smoothed by means of the moving average technique and standardized using Standard Normal Variate (SNV). The obtained spectra were encoded into image representations using the Gramian Angular Summation Field transformation. Off-the-shelf features were generated leveraging pretrained neural networks developed to classify natural images and applied to the “sensor images”. Dimensionality reduction through Principal Component Analysis (PCA) yielded a set of features that could then be used to train machine learning classifiers and regressors. The pipeline was applied to generate visual fingerprints of multiple beverages, proving full discrimination of liquid types (mineral waters, coffees, fruit juices, soft beverages and wines). On a model dataset comprising 11 Italian red wines, it was demonstrated that image fingerprints of samples enabled class identification with a mean accuracy ~95%. The results demonstrate the successful creation of a new representation of the chemical sensing space which achieves comparable performance as domain-specific hand-crafted feature selection. The present contribution represents an example of integration of data processing techniques and publicly available libraries/models to support transfer of methodologies across domains. We believe this approach could be disruptive in the field of electrochemical sensor arrays, especially for processing e-tongues and e-noses response and enhancing capabilities of data-driven chemical sensors. Figure 1

Replacement of conventional reference electrode with platinum electrode for electronic tongue based analysis of dairy products

This work demonstrates the utility of platinum metal electrode as replacement for conventional Ag/AgCl reference electrode for voltammetric electronic tongue based analysis of edible dairy products. It overcomes the limitations of conventional silver-based reference electrode that presents a potential health hazard when employed for analysis of edible dairy products. Various dairy products like toned milk, Lassi and skimmed milk powder were tested using a cluster of platinum, gold and rhodium working electrodes. Responses of electrode cluster were captured using cyclic voltammetry. Comparative investigations were carried out between responses with platinum reference electrode and Ag/AgCl reference electrode. Repeatability and reproducibility of results have been examined. Our results suggest that platinum metal reference electrode can be reliably used for voltammetric electronic tongue based analysis of dairy products. Further this shall pave way for commercial development of electronic tongue technology in food sector adhering to hygienic and food safety regulations.

Response Mechanism of Polymeric Liquid Junction-Free Reference Electrodes Based on Organic Electrolytes.

To achieve a transition from conventional liquid-junction reference electrodes (LJF REs) to their all-solid-state alternatives, organic electrolytes are often introduced into the polymeric electrode membranes. In this article, we implement a theoretical approach to the explanation and quantification of the boundary potential stabilization phenomenon for the electrodes modified with organic electrolytes (Q+B-). For the first time, stabilization of the phase boundary potential due to the partition of lipophilic ions of the Q+B- electrolyte between the polymeric and aqueous phases is numerically simulated to predict the LJF electrodes behavior. The impact of the hydrophilic electrolyte on the potential stabilization is demonstrated both numerically and experimentally. The developed model predicted that the small additions of a traditional ion-exchanger enhance performance of the Q+B--based reference electrodes. For some specific cases, the optimal concentrations of Q+B- and ion-exchanger in the polymeric phase are suggested to provide stable electrode potential in a broad range of aqueous electrolyte concentrations. In addition, the efficiency of the stabilization was shown to be dependent on the overall Q+B- load in the polymeric membrane rather than on the closeness of the partition coefficients of the Q+ and B- ions; and on the volume of the aqueous phase. The model results are verified experimentally with poly(vinyl chloride) membranes containing ion-exchanger or hydrophilic electrolyte and Q+B- in various proportions. A good agreement between the measured electrode response and the theoretical results is observed in a broad range of solution concentrations. In particular, the cationic function of membranes containing KTpClPB is suppressed, and the electrodes begin to behave as REs starting from 50-60 mol. % of ETH500 electrolyte added to the membrane, relative to the total amount of salt.

The Integration of Reference Electrode for ISFET Ion Sensors Using Fluorothiophenol-Treated rGO

Ion-sensitive field-effect transistors (ISFETs) detect specific ions in solutions that enable straightforward, fast, and inexpensive sensors compared to other benchtop equipment. However, a conventional reference electrode (RE) such as Ag/AgCl is limited on the miniaturization of the sensor. We introduce reduced graphene oxide (rGO), which serves as a new RE, when fluorinated (F-rGO) using fluorothiophenol through the π-π interaction. The circular RE is integrated between a fabricated microscale two-channel ISFET, which is capable of detecting two kinds of ions on an indium tin oxide (ITO) thin-film substrate, using the photolithography process. F-rGO bound to this circular region to function as an RE in the ISFETs sensor, which operated stably in solution and showed a relatively high transconductance (gm) value (1.27 mS), low drift characteristic (3.2 mV), and low hysteresis voltage (±0.05 mV). It detected proton (H+) ions in a buffer solution with high sensitivity (67.1 mV/pH). We successfully detected Na+ (62.1 mV/dec) and K+ (57.6 mV/dec) ions in human patient urine using a two-channel ISFET with the F-rGO RE. The F-rGO RE will be a suitable component in the fabrication of low-cost, mass-produced, and disposable ISFETs sensors.

Detection of Marginally Discriminated Ions with Differential Solid Contact Ion-Selective Electrodes

A differential sensor is reported for decreasing the interference from multiple ionic and non-ionic species in droplet-sized samples, hence lowering the detection limit for ions that are particularly hard to measure by conventional ion-selective potentiometry. We believe that the proposed approach represents significant progress beyond state-of-the-art by making the application of ion-selective membranes possible for ions that do not have selective ionophores. Two solid contact ion-selective electrodes (SCISEs) are utilized, which are prepared similarly, except for adding ionophore to one of the membranes. We show experimentally and theoretically that a significant signal is observed only when the analyte ion is present in the sample solution. The dynamic response of the sensor is investigated theoretically by Nernst-Planck-Poisson finite element simulations. Symbolic regression is used to generate human-readable expressions. Differential SCISEs are tested under potentiometric and amperometric conditions. While a large potential response is seen in the conventional SCISE vs reference electrode setup at high concentrations of interfering ions, the signal of interfering species is eliminated in the differential SCISE setup. Consequently, it is possible to measure a few μM levels of ammonium in droplets without the interference of potassium using an ionophore that is not especially selective for ammonium over potassium.

Deep Eutectic Solvents Enhance Stability of Ag/AgCl Solid State Miniaturised Reference Electrode

A new class of solid-state miniaturised reference electrodes with a deep eutectic solvent as an alternate enhancement electrode system is described. A simple and accurate stable electrochemical sensor was prepared by developing a conventional reference electrode using an Ag/AgCl planar micro-reference electrode covered with a PVC polymer. A conductive deep eutectic solvent (DES), ethaline, was added in small quantities and mixed with an internal electrolyte to maintain the Cl− ion concentration in the constructed electrode. The fabricated microelectrode showed good stability, reproducibility, and long-term stability against varying concentrations of different ions. The potential response of the fabricated microelectrode was studied under varying concentrations of Cl− ions in the presence of 0.1 to 1.0% DES in a concentrated electrolyte system (20 mM Na2SO4). The stability of the fabricated microelectrode was addressed against Br− and Cl− ions using different inorganic salts, and the potential measurements were found to be insensitive toward all responsive ions. The stability response of the fabricated microelectrode against Cl− ions was optimised in the presence of 1.0% DES. The experimental data showed good agreement with the potential change of the fabricated electrode in the presence of the supporting DES electrolyte. The liquid junction-free PVC solid-state miniaturised reference electrode demonstrated a constant potentiometric measurement over a long period of time. The concentrated supporting DES electrolyte solution (20 mM) exhibited better stability values and was a more suitable fabricated microelectrode than other additive concentrations. The long-term stability of the developed microelectrode displayed a good lifetime and high stability of around 60 days.

Combining an Integrated Sensor Array with Machine Learning for the Simultaneous Quantification of Multiple Cations in Aqueous Mixtures.

The direct quantification of multiple ions in aqueous mixtures is achieved by combining an automated machine learning pipeline with transient potentiometric data obtained from a single miniaturized array of polymeric sensors electrodeposited on a conventional printed circuit board (PCB) substrate. A proof-of-concept system was demonstrated by employing 16 polymeric sensors in combination with features extracted from the transient differential voltages produced by these sensors when transitioning from a reference solution to a test solution, thereby obviating the need for a conventional reference electrode. A tree-based regression model enabled concentrations of various metal cations in pure solutions to be determined in less than 2 min. In a model mixture comprising Al3+, Cu2+, Na+, and Fe3+, the mean relative error was found to depend on the type of ion and varied between 1% for Fe3+ and 44% for Na+ in the concentration range 1-10 mg/L. Overall, a mean relative error of 16% was obtained for quantification of these four ions across a total of 124 tests in different solutions spanning concentrations between 2 and 360 mg/L. These results demonstrate how the analytical capability of a multiselective sensor array can leverage data-driven approaches through training by examples for accelerated testing and can be proposed to complement traditional analytical tools to meet industrial demands, including traceability of chemicals.

Potentiometric Free Chlorine Detection without Using Conventional Reference Electrodes

Chlorine disinfection of water is one treatment method to supply safe tap water. The quantitative monitoring of free chlorine concentration as an important water quality index is effective to maintain tap water hygienic safety. In this study, a simple potentiometric sensor which is composed of two dissimilar metal electrodes (a pair of platinum and austenitic stainless steel: SUS316) was evaluated in synthetic and actual tap water. It was demonstrated that the open circuit potential of each electrode had a different sensitivity to free chlorine and that the difference could be extracted as the sensing signal without using conventional reference electrodes. In a flowing system using tap water, more than 300 mV of large sensor signal and good reproducibility were observed at a free chlorine concentration of 0.6 mg l−1. The long-term baseline drift was within the range of ±10 mV and the sensor was almost immune to various environmental factors such as temperature, pressure, flow rate, and conductivity, but not for pH. These results would pave the way to develop various sensor applications that could be directly applied to tap water pipelines for continuous in-line monitoring of residual chlorine with low cost and maintenance.

Potentiometric Free Chlorine Detection without Using Conventional Reference Electrodes

Introduction Chlorine disinfection of water is one of the treatment methods to supply safe drinking water. The concentration of free chlorine has to be monitored as an important index to make the process efficient and is generally measured at several points in the pipeline system between water treatment plant and the water taps. For realizing smart water supply system based on various IoT technologies, low cost and maintenance-free type sensor which can be easily applied to pipeline network system would be effective.Various kinds of analytical techniques for detection of free chlorine concentration have been proposed and practically utilized. Comparing with regent-type colorimetric methods, electrochemical methods are suitable for in-line monitoring with simplicity and low cost. So far, many amperometric sensors have been proposed [1, 2], Recently, the authors reported a simple sensor device which is composed of two dissimilar electrodes [3]. The open circuit potential of each electrode has a different sensitivity to free chlorine and then the differential signal is extracted as sensor output. In this study, sensing characteristics of this sensor device in flowing-tap-water system were evaluated. Principle The schematic diagram of simple two-electrode system to enable in-line monitoring of free chlorine concentration is represented in Fig.1. Ideally, the sensor device consists of detecting and compensating metal electrodes that are active and inactive to free chlorine as target compound, respectively. Furthermore, sensitivities to interferences, such as temperature, pressure, pH, conductivity, and so on, have to be almost same in order to self-compensate the fluctuation of various environmental factors. In our previous study [3], it was found that platinum and SUS316 electrode are suitable for detecting and compensating electrode, respectively. The difference in open circuit potential could be explained by mixed potential theory. This passive-type sensor which utilize its electromotive force between dissimilar electrodes would have many advantages of low cost, low power consumption and these features enable long-term use of sensor device without periodical maintenance. Method Pt and SUS316 were used as test electrodes. These metal rods were embedded in center of a Teflon mold. Prior to use, each electrode surface was polished with SiC paper and ultrasonically rinsed with ethanol. In order to validate the sensor performances of Pt-SUS316 pair of electrodes in flowing-tap-water system, these electrodes were directly inserted in pipeline, as shown in Fig. 1. Practical tap water with or without free chlorine was fed into this test pipeline at various flow rate by using activated carbon filter which can selectively remove free chlorine. The differential open circuit potentials of Pt-SUS316 pair were measured using a high-input impedance electrometer. The concentration of residual chlorine was checked by free chlorine portable photometer based on DPD method. Results and Conclusions As a first step, the baseline drift behavior of Pt-SUS316 electrode pair was checked, as shown in Fig. 2. Baseline drift was defined as the variation in sensor output from that at the start time of each experiment. Although a slight baseline drift was observed, the value of the drifts were within the range of ±10 mV. However, trend of the drift could not be clarified. It would be caused by tiny fluctuation of environmental conditions such as temperature, pH, etc.Typical sensor performance in flowing-tap-water system was described in Fig. 3. Potential difference (sensor output) between Pt and SUS316 was around 150 mV in practical tap water without free chlorine. It indicates that open circuit potential of Pt was higher than that of SUS316 under this condition. When the flow experiment started, the baseline level was slightly fluctuated. After the level was stabilized, tap water containing free chlorine (0.6 mg/L) flow thorough the test pipeline. The sensor output sharply increased and reached to steady state within 10 min. This large response was mainly attributed to high sensitivity of Pt to free chlorine. Therefore, concentration of free chlorine could be monitored under in-line condition without using conventional reference electrodes. On the other hand, recovery rate was very slow and seem to become slower. However, reproducibility of the sensor response with repeated exposure to free chlorine was good since the steady state values almost unchanged.

Quantification of Multi-Ion Mixtures Using a Machine Learning Assisted Integrated Electronic Tongue Leveraging Mobile and Cloud Platforms

Quantification of Multi-Ion Mixtures Using a Machine Learning Assisted Integrated Electronic Tongue Leveraging Mobile and Cloud Platforms

CSIRO SENSEI™ in Situ System for Groundwater Monitoring

Currently, standard electroanalytical multi-sensor systems used in-situ to monitor the chemistry of aqueous systems are based on conventional glass ion-selective electrodes. Issues with these electrodes are common and range from their fragile construction, to fouling of the junction and often reference electrode poisoning. Remote operations, such as mining sites, require new technologies to overcome these challenges, encouraging the development of low-maintenance options for monitoring mineral processes and environmental pollution in-situ.CSIRO is developing a robust and cost-effective solid-state sensor and analytics platform, termed SENSEI™, which includes solid-state electrodes and system electronics embedded directly into the measurement unit. The monitoring system includes CSIRO’s patented pH and reference electrodes together with ORP and conductivity sensors. Third party sensors can be included as part of the unit via MODBUS connection. The all-solid construction of the unit enables operation at elevated pressures and in the presence of external forces, and direct contact of the electrodes with the electronics removes the need for analogue cables, reducing electronic interference.A key feature of the SENSEI™ system is the patented solid-state reference electrode. Due to the issues mentioned earlier, conventional reference electrodes were not suitable in an all-solid system and this led to CSIRO developing a new solid salt-polymer composite reference electrode. The SENSEI™ reference electrode includes an Ag/AgCl reference element embedded in a composite material of crosslinked polyvinyl acetate and KCl. After the initial stabilisation time the potential of the reference electrodes stabilises at -45±5 mV vs. SCE. According to laboratory and pilot-scale experiments, the electrode functions maintenance-free during continuous online monitoring for 9-12 months in aqueous systems, including groundwater and acidic mineral leaching systems.The first large-scale application for the system is in environmental groundwater monitoring of an in-situ recovery operation at Heathgate Resources Pty Ltd. In in-situ recovery mining systems the leaching solution is pumped underground, where it dissolves the metals of the ore deposit, and afterwards pumped back to the surface for post-processing, so proper process control is crucial for a safe and environmentally friendly operation to ensure mining fluids are contained within the mining region. Continuous monitoring of the lateral, overlying and underlying aquifers which ring the mining operation enables quick corrective actions to be taken in the event of possible contamination from a leaching solution. The field trial began in 2019 and will continue until the end of 2020.Figure. A schematic drawing of the SENSEI™ sensor unit. The sensor pack includes solid-state (1) ORP electrode, (2) reference electrode, (3) pH electrode and (4) conductivity/temperature sensor. Figure 1

Potentiometric Free Chlorine Detection without Using Conventional Reference Electrodes

Introduction Water chlorination is one of key process for supplying safe drinking water. The concentration of fee chlorine has to be monitored as an important index to make the process efficient and is mainly measured at water treatment plant. For realizing smart water supply system based on various IoT technologies, low cost and maintenance-free type sensor which can be easily applied to whole pipeline network system including water outlet on every home would be required. Various kinds of analytical techniques for detection of free chlorine concentration have been proposed and practically utilized. Comparing with regent-type colorimetric methods, electrochemical methods are suitable for in-line monitoring with simplicity and low cost. So far, many amperometric sensors have been proposed [1, 2], Recently, the authors reported a simple sensor device which is composed of two dissimilar electrodes [3]. The open circuit potential of each electrode has a different sensitivity to free chlorine and then the differential signal is extracted as sensor output. In this study, sensing characteristics of this sensor device in flowing-tap-water system were evaluated. Principle The schematic diagram of simple two-electrode system to enable in-line monitoring of free chlorine concentration is represented in Fig.1. Ideally, the sensor device consists of detecting and compensating metal electrodes that are active and inactive to free chlorine as target compound, respectively. Furthermore, sensitivities to interferences, such as temperature, pressure, pH, conductivity, and so on, have to be almost same in order to self-compensate the fluctuation of various environmental factors. In our previous study [3], it was found that platinum and SUS316 electrode are suitable for detecting and compensating electrode, respectively. The difference in open circuit potential could be explained by mixed potential theory. This passive-type sensor which utilize its electromotive force between dissimilar electrodes would have many advantages of low cost, low power consumption and these features enable long-term use of sensor device without periodical maintenance. Method Pt and SUS316 were used as test electrodes. These metal rods were embedded in center of a Teflon mold. Prior to use, each electrode surface was polished with SiC paper and ultrasonically rinsed with ethanol. In order to validate the sensor performances of Pt-SUS316 pair of electrodes in flowing-tap-water system, these electrodes were directly inserted in pipeline, as shown in Fig. 1. Practical tap water with or without free chlorine was fed into this test pipeline at various flow rate by using activated carbon filter which can selectively remove free chlorine. The differential open circuit potentials of Pt-SUS316 pair were measured using a high-input impedance electrometer. The concentration of residual chlorine was checked by free chlorine portable photometer based on DPD method. Results and Conclusions As a first step, the baseline drift behavior of Pt-SUS316 electrode pair was checked, as shown in Fig. 2. Baseline drift was defined as the variation in sensor output from that at the start time of each experiment. Although a slight baseline drift was observed, the value of the drifts were within the range of ±20 mV. However, trend of the drift could not be clarified. It would be caused by tiny fluctuation of environmental conditions such as temperature, pH, etc. Typical sensor performance in flowing-tap-water system was described in Fig. 3. Potential difference (sensor output) between Pt and SUS316 was around 200 mV in practical tap water without free chlorine. It indicates that open circuit potential of Pt was higher than that of SUS316 under this condition. When the flow experiment started, the baseline level was slightly fluctuated. After the level was stabilized, tap water containing free chlorine (0.6 mg/L) flow thorough the test pipeline. The senor output sharply increased and reached to steady state within 10 min. This large response was mainly attributed to high sensitivity of pt to free chlorine. Therefore, concentration of free chlorine could be monitored under in-line condition without using conventional reference electrodes. On the other hand, recovery rate was very slow and seem to become slower. However, reproducibility of the sensor response with repeated exposure to free chlorine was good since the steady state values almost unchanged.

Solid-State pH Sensors for Mine Water Monitoring

Introduction The monitoring of water quality parameters such as pH, redox potential, and conductivity is essential in order to investigate the variety of hydrochemical processes occurring in aqueous environments. For a better understanding of these processes, measurements with high temporal resolution are needed, which cannot be achieved with manual sampling procedures. Hence, alternative technical analysis methods, such as sensors, are used to monitor relevant parameters in-situ. Unfortunately conventional probes often experience harsh or detrimental conditions during on-site deployment. All-solid-state potentiometric sensors have been proposed as robust alternatives for demanding environments that deliver results with sufficient accuracy, at relatively low-cost, with experimental and instrumental simplicity [1].This work focuses on the development of a solid-state pH sensor for the monitoring of mine water and acid mine drainage (AMD). AMD is the consequence of uncontrolled sulfidic mineral oxidation, typically as a result of ore or coal mining practices. The resulting outflow of acidic water, which can contain high concentrations of metal ions, is potentially disastrous to aquatic life and also poses a great threat to water supplies [2]. Our aim is to develop a robust and cost-effective sensor that enables in-situ AMD monitoring in mines and surrounding waterways, as well as pit lakes formed as the result of flooded open-pit mines. With increased spatial and temporal resolution in comparison to manual sampling, these sensors will help to predict hazardous conditions and increase the understanding of the complex underlying geochemical mechanisms. Methods The proposed sensor consists of a pH sensitive iridium oxide (IrOx) layer in combination with a solid-state reference electrode. During sensor fabrication structured titanium and gold electrodes were deposited on oxidised silicon substrates using standard cleanroom techniques. IrOx was subsequently electrochemically coated on these electrodes via cyclic voltammetry. The deposition solution was prepared according to the protocol published by Marzouk [3]. In a three electrode configuration (reference: 3 M KCl Ag/AgCl, counter: platinum gauze) the prepared metal electrodes functioned as the working electrodes. Homogenous IrOx layers with a thickness around 80 nm were obtained after 100 cycles at 0.1 V/s between -0.5 V and 0.85 V or -0.7 V and 0.9 V for the gold and titanium electrodes respectively (see Figures 1 and 2).Several approaches for the construction of solid state reference electrodes (SSREs) have been presented in literature [4]. In this work, salt-saturated polymers were deposited on Ag/AgCl layers, similar to [5]. The selected polymers were either unsaturated polyester resins or UV-curing epoxy-based resins. These resins were mixed with up to 70 ma% of finely ground KCl. The resulting slurry was dropped on Ag/AgCl electrodes and cured to form the SSREs.Data collection was performed with EZO-circuits from Atlas Scientific in connection with a RaspberryPi or an ESP32-based microcontroller using I2C or serial protocols.The fabricated IrOx electrodes were characterised regarding their pH sensing performance. Their sensitivity was evaluated by recording the open circuit potential (OCP) vs. a commercial reference electrode (3 M KCl, Ag/AgCl) during a titration of a Briton-Robinson buffer with 0.5 M KOH at 25°C. Drift rates were measured in standard buffer solutions. In order to determine the SSRE’s electrochemical potential stability, OCP was recorded versus a conventional reference electrode in KCl solutions of varying concentration at 25°C. Results and Conclusions As shown in Figure 3, the IrOx electrodes exhibit a super-Nernstian pH sensitivity of around -73 mV/pH between pH 2 to 11.5. These values are comparable to published results [3]. Electrodes from several batches fabricated on different days show high reproducibility with respect to sensitivity and intercept, as indicated by the closely overlaying data points in Figure 3. These results suggest a high robustness of the coating process. The drift rate of the IrOx electrodes is less than 1 mV/h which is sufficient for the intended application. The functionality of the SSRE can be deducted from the data given in Figure 4: An uncoated Ag/AgCl electrode exhibits Nernstian behavior to changes in chloride ion concentration whereas the fabricated SSRE with a polymer coating shows a stable potential. The combination of SSRE and IrOx electrode results in a potentiometric pH sensor whose output changes with pH as shown in Figure 5. Outlook Future work will focus on improving the sensing characteristics as well as measurements in AMD samples. Eventually on-site deployment of the sensors is planned. Additionally, first experiments to transfer the electrodes to flexible and chemically inert substrates for ultimate robustness and potential applications in smart robotic skins have been conducted (see Figure 6). Acknowledgments This research has been funded by the European Social Fund (ESF) and the Free State of Saxony. (ARIDuA , project number 100310491).

Valve-Actuator-Integrated Reference Electrode for an Ultra-Long-Life Rumen pH Sensor.

We demonstrated a newly developed Ag/AgCl reference electrode- with a valve-actuator for two years or longer rumen pH monitoring. Previous studies on pH sensors reported that the short lifetime of Ag/AgCl reference electrodes is caused by an outflow of internal electrolyte. We introduced a valve-actuator into a liquid junction to reduce the outflow by intermittent measurement. The results indicated that the potential change when switching the liquid junction was less than 0.5 mV and its response time was less than 0.083 s. In the 24-h potential measurement with the valve-actuator-integrated reference electrode (VAIRE), the valve was actuated once every hour, and the standard deviation of the potential was 0.29 mV. The lifetime of the VAIRE was estimated at 2.0 years calculating from an electrolyte outflow, which is significantly longer than that of conventional reference electrodes. A pH sensor using the VAIRE was estimated to operate for 2.0 years with the pH error ≤0.1, which meets the requirement of cows’ rumen pH monitoring.

Far-field potentials in the compound muscle action potential.

It has long been believed that the compound muscle action potential (CMAP) in motor-nerve conduction studies (MCSs) records the action potential beneath the active electrode over the muscle belly. However, recent studies have revealed the contribution of the reference electrode to the CMAP, most prominent in the tibial nerve, followed by the ulnar nerve. This "reference electrode potential" is recorded when the conventional reference electrode distal to the muscle belly is connected to a proximal reference. It must be a far-field potential (FFP) considering its distribution, although the precise mechanism of its generation has not been clarified. The conventional theory of termination of the action potential at the muscle-tendon junction is insufficient. Regarding the ulnar CMAP, interosseous muscles mostly contribute to the FFPs. New understanding of CMAP based on the FFP theory may provide new insights into the interpretation of MCSs and related techniques, including motor unit number estimation.

Two-electrode-pair electrocardiogram with no common ground between two pairs.

An electrocardiogram (ECG) records the electrical activity of the heart using two electrodes to detect electrophysiological signals from the organ and one reference electrode (typically attached to the right leg) as the reference potential. An inconvenience of the three electrodes is that the grounds of the amplifiers are interconnected all over the body. To address this inconvenience, this paper proposes a two-electrode ECG measurement method with common electrodes instead of the reference electrode of the right leg. The power supply and the ground of the amplifier supplying the two electrode pairs are not connected and independent. Pasted on the skin with the body as the reference potential, both electrodes detect electrophysiological signals, transmitting the signals through two isolation amplifiers to an instrumentation amplifier filter and generating ECG waveforms. Both previous-stage electrode amplifier circuits of the isolation amplifiers used their respective power supplies; their grounds were unconnected to those of the power supplies. Similarly, the next-stage electrode amplifiers used their respective power supplies, with their grounds unconnected to those of the power supplies. Experiments yielded ECG signal waveforms in Leads I to III, with that of Lead I most resembling the waveforms of conventional reference electrodes. This method can be used to develop wireless ECG devices and portable ECG devices that eliminate the need for wiring to facilitate ECG measurement.

Hydrogen-bromate flow battery: can one reach both high bromate utilization and specific power?

Hydrogen-bromate flow battery is a promising hybrid current source for air-deficient environment that functions by electrocatalyzed reactions of hydrogen oxidation and aqueous LiBrO3 reduction. The flow cell consists of porous carbonaceous cathode, platinum catalyzed hydrogen oxidation gas diffusion anode, and separating proton exchange membrane. Performance of the hydrogen-bromate flow battery single cell has been optimized by varying the catholyte feed rate, LiBrO3 concentration in catholyte, hydrogen pressure, membrane thickness, amount of porous carbon at cathode, and Pt loading at anode. Shape of the I-V curve is characterized by a sharp maximum of current, which indicates passivation of one of the electrodes. Combination of conventional reference electrode and home-made thin-film Luggin capillary has been used to monitor separately the polarizations of both flow cell electrodes. Poisoning of platinum hydrogen oxidation electrocatalyst by bromine species, which permeated the membrane, is shown as a major source of performance losses of hydrogen-bromate flow battery at high power density. Hypothesis supported by experiments claims that the degree of the platinum electrocatalyst poisoning is determined by the balance between the rates of the bromine species supply to anode and their removal by liquid water that permeates the membrane. Use of thinner proton exchange membrane and thinner carbonaceous cathode is a prerequisite to achieving high power density of the cell at high current efficiency of the cathode process. At 40 °C, area-specific power reaches 0.74 W cm−2 at the level of catholyte utilization equal to 0.93.