Simultaneous Detection of Ammonium and Nitrate in Environmental Samples Using on Ion-Selective Electrode and Comparison with Portable Colorimetric Assays

Printed Potentiometric Ammonium Sensors for Agriculture Applications

Ammonium (NH4 +) concentration is critical to both nutrient availability and nitrogen (N) loss in soil ecosystems but can be highly variable across spatial and temporal scales. For this reason, effectively informing agricultural practices such as fertilizer management and understanding of mechanisms of soil N loss require sensor technologies to monitor ammonium concentrations in real time. Our work investigates the performance of fully printed ammonium ion-selective sensors used in diverse soil environments. Ammonium sensors consisting of a printed ammonium ion-selective electrode and a printed Ag/AgCl reference were fabricated and characterized in aqueous solutions and three different soil types (sand, peat, and clay) under the range of ion concentrations likely to be present in soil (0.01-100 mM). The response of ammonium sensors was further evaluated under variable gravimetric moisture content in the soil to reflect their reliability under field conditions. Ammonium sensors demonstrated a sensitivity of 53.6 ± 5.1 mV/decade when tested in aqueous solution, and a sensitivity of 55.7 ± 11 mV/dec, 57.5 ± 4.1 mV/dec, and 43.7 ± 4 mV/dec was measured in sand, clay, and peat soils, respectively.

Green synthesis of silver nanoparticles by Smyrnium cordifolium plant and its application for colorimetric detection of ammonia

The need to identify ammonia is necessary because of its harmful effects on the environment and humans. In this study, a colorimetric method was also developed for the detection of ammonia using silver nanoparticles (AgNPs) synthesized with the green approach. Biosynthesis of AgNPs was performed by silver nitrate as a silver precursor and Smyrnium cordifolium extract as a reducing and stabilizing agent. Plant extract was studied by FTIR and LC/Mass techniques. The optimization of the effective parameters was carried out with central composite design according to silver nitrate concentration, plant extract volume, pH, and temperature. Biosynthetic nano-silver was characterized with XRD, EDS/EDX, FE-SEM, FTIR, TGA, and DLS methods. The AgNPs was validated for ammonia colorimetric detection. Biosynthesis of AgNPs were increased in 20 mM AgNO3, 5 ml Smyrnium cordifolium extract, pH 10, and the temperature of 70 °C. Crystal form of AgNPs characterized with XRD at 2Ѳ value of 38.34°, 44.19°, 64.74°, and 77.59° and spherical shape highlighted in the range between 77.8 and 93 nm. Plant extract consisted of polyphenol (phenolic acid, flavonoid, and terpenoid), fatty acid, amino acid, sugar, purine, and organic acid. AgNPs were used for colorimetric detection of ammonia by shifting the λmax from 580 to 490 nm. A method for ammonia detection was set up, with linear range of 0.5-200 ppm, detection limit of 0.028 ppm and recovery level of 96.3 ± 6.5%. In conclusion, a new biosynthetic method by specified local plant was developed to propose a simple and sensitive colorimetric method for soluble ammonia detection.

Low-cost precision agriculture for sustainable farming using paper-based analytical devices

The United Nations estimates that by 2030, agricultural production must increase by 70% to meet food demand. Precision agriculture (PA) optimizes production through efficient resource use, with soil fertility being crucial for nutrient supply. Traditional nutrient quantification methods are costly and time-consuming. This study introduces a rapid (15 min), user-friendly, paper-based platform for determining four essential macronutrients-nitrate, magnesium, calcium, and ammonium-using colorimetric methods and a smartphone for data reading and storage. The sensor effectively detects typical soil nutrient concentrations, showing strong linearity and adequate detection limits. For nitrate, the RGB method resulted in an R 2 of 0.992, a detection range of 0.5 to 10.0 mmol L-1, and an LOD of 0.299 mmol L-1. Calcium quantification using grayscale displayed an R 2 of 0.993, a detection range of 2.0 to 6.0 mmol L-1, and an LOD of 0.595 mmol L-1. Magnesium was best quantified using the hue color space, with an R 2 of 0.999, a detection range of 1.0 to 6.0 mmol L-1, and an LOD of 0.144 mmol L-1. Similarly, ammonium detection using the hue color space had an R 2 of 0.988, a range of 0.5 to 2.5 mmol L-1, and an LOD of 0.170 mmol L-1. This device enhances soil fertility assessment accessibility, supporting PA implementation and higher food production.

Application of a portable ion chromatograph for real-time field analysis of nitrite and nitrate in soils and soil pore waters

Real-time monitoring of nitrite and nitrate is crucial for maintaining soil health and promoting plant growth. In this study, a portable ion-chromatograph (IC, Aquamonitrix) analyser, coupled with a field-applicable ultrasonic-assisted extraction method, was utilised for in-field determination of nitrate and nitrite in soils. This is the first application of this type of analyser to soil nutrients. On-site analysis of soil from a local sports field showed 94.8 ± 4.3 μg g-1 nitrate, with LODs of 32.0 μg g-1 for nitrate and 5.4 μg g-1 for nitrite. The results were in close agreement with those obtained using a conventional lab-based IC. Relative standard deviations (%RSDs) for soil analysis using Aquamonitrix were consistently below 10%. The obtained average recoveries of samples spiked with nitrite were 100% and 104% for the portable IC and conventional IC, respectively. Furthermore, to assess the suitability of portable IC for samples with high organic matter content, various natural organic fertilisers were extracted and analysed. The results showed 16.2 ± 0.7 μg g-1 nitrite and 28.5 ± 5.6 μg g-1 nitrate in sheep manure samples with LODs of 2.0 μg g-1 for nitrite and 12.0 μg g-1 for nitrate. The portable IC system was further demonstrated via real-time on-site analysis of soil pore-water acquired using a portable battery-based ceramic pore-water sampler. A continuous increase in nitrate concentration over time was observed (from 80 to 148 μg mL-1) in the soil pore-water in a vegetable garden four days after heavy rain. Unlike conventionally sampled natural waters, 7-day storage of the studied pore water samples revealed no changes in nitrate concentrations. An average of 558 ± 51 μg mL-1 nitrate was detected in the soil pore-water samples analysed on a spinach farm, immediately after irrigation.

Portable IC system enabled with dual LED-based absorbance detectors and 3D-printed post-column heated micro-reactor for the simultaneous determination of ammonium, nitrite and nitrate

BACKGROUND

The on-site and simultaneous determination of anionic nitrite (NO2-) and nitrate (NO3-), and cationic ammonium (NH4+), in industrial and natural waters, presents a significant analytical challenge. Toward this end, herein a 3D-printed micro-reactor with an integrated heater chip was designed and optimised for the post-column colorimetric detection of NH4+ using a modified Berthelot reaction. The system was integrated within a portable and field deployable ion chromatograph (Aquamonitrix) designed to separate and detect NO2- and NO3-, but here enabled with dual LED-based absorbance detectors, with the aim to provide the first system capable of simultaneous determination of both anions and NH4+ in industrial and natural waters.

RESULTS

Incorporating a 0.750 mm I.D. 3D-printed serpentine-based microchannel for sample-reagent mixing and heating, the resultant micro-reactor had a total reactor channel length of 1.26 m, which provided for a reaction time of 1.42 min based upon a total flow rate of 0.27 mL min-1, within a 40 mm2 printed area. The colorimetric reaction was performed within the micro-reactor, which was then coupled to a dedicated 660 nm LED-based absorbance detector. By rapidly delivering a reactor temperature of 70 °C in just 40 s, the optimal conditions to improve reaction kinetics were achieved to provide for limits of detection of 0.1 mg L-1 for NH4+, based upon an injection volume of just 10 μL. Linearity for NH4+ was observed over the range 0-50 mg L-1, n = 3, R2 = 0.9987. The reactor was found to deliver excellent reproducibility when included as a post-column reactor within the Aquamonitrix analyser, with an overall relative standard deviation below 1.2 % for peak height and 0.3 % for peak residence time, based upon 6 repeat injections.

SIGNIFICANCE

The printed post-column reactor assembly was integrated into a commercial portable ion chromatograph developed for the separation and detection of NO2- and NO3-, thus providing a fully automated system for the remote and simultaneous analysis of NO2-, NO3-, and NH4+ in natural and industrial waters. The fully automated system was deployed externally within a greenhouse facility to demonstrate this capability.

Highly sensitive absorbance measurement using droplet microfluidics integrated with an oil extraction and long pathlength detection flow cell

In droplet microfluidics, UV-Vis absorption spectroscopy along with colorimetric assays have been widely used for chemical and biochemical analysis. However, the sensitivity of the measurement can be limited by the short optical pathlength. Here we report a novel design to enhance the sensitivity by removing oil and converting the droplets into a single-phase aqueous flow, which can be measured within a U-shape channel with long optical pathlength. The flow cells were fabricated via 3D printing. The calibration results have demonstrated complete oil removal and effective optical pathlengths similar to the designed channel lengths (from 5 to 20 mm). The flow cell was further employed in a droplet microfluidic-based phosphate sensing system. The measured phosphate levels displayed excellent consistency with data obtained from traditional UV spectroscopy analysis. This flow cell design overcomes the limitations of short optical pathlengths in droplet microfluidics and has the potential to be used for in situ and continuous monitoring.

Structure Optimization and Data Processing Method of Electronic Nose Bionic Chamber for Detecting Ammonia Emissions from Livestock Excrement Fermentation

In areas where livestock are bred, there is a demand for accurate, real-time, and stable monitoring of ammonia concentration in the breeding environment. However, existing electronic nose systems have slow response times and limited detection accuracy. In this study, we introduce a novel solution: the bionic chamber construction of the electronic nose is optimized, and the sensor response data in the chamber are analyzed using an intelligent algorithm. We analyze the structure of the biomimetic chamber and the surface airflow of the sensor array to determine the sensing units of the system. The system employs an electronic nose to detect ammonia and ethanol gases in a circulating airflow within a closed box. The captured signals are processed, followed by the application of classification and regression models for data prediction. Our results suggest that the system, leveraging the biomimetic chamber, offers rapid gas detection response times. A high classification prediction accuracy, with a determination coefficient R2 value of 0.99 for single-output regression and over 0.98 for multi-output regression predictions, is achieved by incorporating a backpropagation (BP) neural network algorithm. These outcomes demonstrate the effectiveness of the electronic nose, based on an optimized bionic chamber combined with a BP neural network algorithm, in accurately detecting ammonia emitted during livestock excreta fermentation, satisfying the ammonia detection requirements of breeding farms.

Ammonium concentration in stream sediments resulting from decades of discharge from a wastewater treatment plant

A study of ammonium pollution in the sediments of a stream that receives wastewater treatment plant (WWTP) discharge has been carried out. It is urgently necessary to find environmental indicators that can help prevent and detect potential contamination of water, as water is an increasingly scarce resource. To understand the behaviour of ammonium ions introduced by a historical (50-year) contamination process, vertical boreholes were drilled in the stream banks to depths between 30 and 120 cm. Moisture, pH, ammonium (soluble and exchangeable), and clay fraction content were analysed. The variation profile of these parameters was evaluated as a function of depth to determine factors related to the distribution of ammonium in several locations along the stream banks. The ammonium concentration was asymmetrically distributed among samples collected in near-surface locations, with ammonium concentrations between 0.3048 mmol/kg soil and 0.0007 mmol/kg soil. Ammonium was typically concentrated at sediment depths of 30-40 cm, which also exhibited the highest clay fraction content. High positive correlations were detected (r > 0.8; p < 0.0001) among the different ammonium variables (exchanged and dissolved species). No contamination effect was observed below 60-70 cm depth, which was due to ammonium retention in a natural barrier layer of clayey sediment. The clays in our study area (previously identified as smectite, a 2:1 sheet silicate) were able to control the contamination by retaining ammonium in the interlayers, which retarded nitrification. It is suggested that clay could serve as a geo-indicator of ammonium pollution evolution.

A submersible probe with in-line calibration and a symmetrical reference element for continuous direct nitrate concentration measurements

Current methods to monitor nitrate levels in freshwater systems are outdated because they require expensive equipment and manpower. Punctual sampling on the field or at a fixed measuring station is still the accepted monitoring procedure and fails to provide real-time estimation of nitrate levels. Continuous information is of crucial importance to evaluate the health of natural aquatic systems, which can strongly suffer from a nitrogen imbalance. We present here a nitrate-selective potentiometric probe to measure the analyte continuously without requiring maintenance or high-power consumption. Owing to a simple design where the sensors are located directly in contact with the sample, the need for constant pump usage is eliminated, requiring just 0.7 mW power per day instead of 184 mW per day and per pump. It is estimated that with this power consumption, the setup can easily run for more than 97 h on four simple Li-ion batteries. A simple in-line one-point calibration step was implemented to allow for drift correction. At the same time, a symmetrical design was used involving a second nitrate probe as a reference electrode placed in the calibrant compartment. This, combined with an in situ calibration step, allows one to quantify nitrate ion concentrations directly, instead of yielding activities. The dependence on ion activity was removed by using the analysed sample spiked with nitrate as the calibrant. This results in essentially the same activity coefficients and additionally reduces junction potentials to a fraction of a millivolt. In addition, a symmetrical reference element served to compensate for fluctuations caused by environmental factors (temperature, convection, etc.) to achieve improved stability and signal reproducibility compared to a traditional Ag/AgCl based reference electrode. The final prototype was deployed in the Arve River in Geneva for 75 h without requiring any intervention. The nitrate levels measured using the symmetrical reference element over this period were estimated at 44.0 ± 3.5 M and agreed well with the values obtained with ion chromatography (38.2 ± 2.1 μM) used as the reference method. Thanks to a modular sensing head the potentiometric sensors can be easily exchanged, making it possible to quantify other types of analytes and leading the way to a new monitoring strategy.

A Multi-Pumping Gradient Calibration Module for Potentiometric Determination of Nitrate in Surface Water

The novel, automated, multi-pumping flow system (MPFS) for online calibration and determination of nitrate in surface water is presented for the first time. The system was equipped with micropumps of three different nominal volumes (10, 20, and 50 µL). As a result, it was possible to prepare from one standard, directly in a flow system, up to seven standard solutions. Determination of nitrate was conducted in stop-flow conditions and is based on a commercially available ion selective electrode (ISE) application. It was found that the linearity and slope of the calibration graphs depend mainly on the characteristics of the ISE. The obtained results were very repeatable, owing to the high precision of the micro-pumps used. The R.S.D. for the stroke volume of each micro-pump was below 1%. The accuracy of the method was checked through determination of nitrate in surface water samples. The obtained results were compared with those of the reference method (photometric Hach cuvette tests). It was found that, at a 96% confidence level, the difference between the results obtained by the proposed method and the reference method was statistically insignificant. The accuracy of the method was confirmed through the determination of nitrate in Certified Reference Material. The relative deviation (R.D.) of the measured and the certified concentrations was 5%.

Electrospraying Zwitterionic Copolymers as an Effective Biofouling Control for Accurate and Continuous Monitoring of Wastewater Dynamics in a Real-Time and Long-Term Manner

Long-term continuous monitoring (LTCM) of water quality can provide high-fidelity datasets essential for executing swift control and enhancing system efficiency. One roadblock for LTCM using solid-state ion-selective electrode (S-ISE) sensors is biofouling on the sensor surface, which perturbs analyte mass transfer and deteriorates the sensor reading accuracy. This study advanced the anti-biofouling property of S-ISE sensors through precisely coating a self-assembled channel-type zwitterionic copolymer poly(trifluoroethyl methacrylate-random-sulfobetaine methacrylate) (PTFEMA-r-SBMA) on the sensor surface using electrospray. The PTFEMA-r-SBMA membrane exhibits exceptional permeability and selectivity to primary ions in water solutions. NH₄⁺ S-ISE sensors with this anti-fouling zwitterionic layer were examined in real wastewater for 55 days consecutively, exhibiting sensitivity close to the theoretical value (59.18 mV/dec) and long-term stability (error <4 mg/L). Furthermore, a denoising data processing algorithm (DDPA) was developed to further improve the sensor accuracy, reducing the S-ISE sensor error to only 1.2 mg/L after 50 days of real wastewater analysis. Based on the dynamic energy cost function and carbon footprint models, LTCM is expected to save 44.9% NH₄⁺ discharge, 12.8% energy consumption, and 26.7% greenhouse emission under normal operational conditions. This study unveils an innovative LTCM methodology by integrating advanced materials (anti-fouling layer coating) with sensor data processing (DDPA).

Printed Potentiometric Nitrate Sensors for Use in Soil

Plant-available nitrogen, often in the form of nitrate, is an essential nutrient for plant growth. However, excessive nitrate in the environment and watershed has harmful impacts on natural ecosystems and consequently human health. A distributed network of nitrate sensors could help to quantify and monitor nitrogen in agriculture and the environment. Here, we have developed fully printed potentiometric nitrate sensors and characterized their sensitivity and selectivity to nitrate. Each sensor comprises an ion-selective electrode and a reference electrode that are functionalized with polymeric membranes. The sensitivity of the printed ion-selective electrodes was characterized by measuring their potential with respect to a commercial silver/silver chloride reference electrode in varying concentrations of nitrate solutions. The sensitivity of the printed reference electrodes to nitrate was minimized with a membrane containing polyvinyl butyral (PVB), sodium chloride, and sodium nitrate. Selectivity studies with sulphate, chloride, phosphate, nitrite, ammonium, calcium, potassium, and magnesium showed that high concentrations of calcium can influence sensor behavior. The printed ion-selective and reference electrodes were combined to form a fully printed sensor with sensitivity of −48.0 ± 3.3 mV/dec between 0.62 and 6200 ppm nitrate in solution and −47 ± 4.1 mV/dec in peat soil.

Monitoring Microalgal Growth of Chlorella minutissima with a New All Solid-state Contact Nitrate Selective Sensor

As third generation feedstock, microalgae are microorganisms that can grow only in the optimum conditions. There are parameters including the concentration of macro and microelements in nutrient solution, pH, temperature, and light intensity that have significant impact on microalgal growth. In recent years, various sensing devices has been developed for sensitive measurement of these parameters during microalgal growth. In this study, a new potentiometric nitrate selective sensor was developed to indicate the nitrate uptake of microalgae and the effect of nitrate nutrient on microalgal growth, specifically, and this sensor was successfully applied to determine nitrate concentration in medium during microalgal growth. Moreover, the effects of nitrate, carbonate and phosphate concentration in the growth medium on biomass production of Chlorella minutissima were investigated by using Box-Behnken design method, and optimum conditions were determined for the highest biomass production of microalgae. As a result of the experiments, it was seen that the highest C. minutissima production was achieved using the medium consist of 2.63 g/L NaNO₃ , 0.35 g/L Na₂ CO₃ and 0.4 g/L KH₂ PO_4. Statistically, it was observed that there was a proportional relationship between the microalgae production and investigated parameters such as carbon, nitrogen and phosphate amounts of culture mediums. The electrode showed a wide linear range between 1.0×10^-1 and 5.0×10^-5 M with a detection limit of the 5×10^-6 M and the response time was found as 10 s. The results showed that developed nitrate selective sensor could be successfully applied for continuous measurement of nitrate in microalgal productions at reduced cost. This article is protected by copyright. All rights reserved.

Recent Advances in Chemical Sensors for Soil Analysis: A Review

The continuously rising interest in chemical sensors’ applications in environmental monitoring, for soil analysis in particular, is owed to the sufficient sensitivity and selectivity of these analytical devices, their low costs, their simple measurement setups, and the possibility to perform online and in-field analyses with them. In this review the recent advances in chemical sensors for soil analysis are summarized. The working principles of chemical sensors involved in soil analysis; their benefits and drawbacks; and select applications of both the single selective sensors and multisensor systems for assessments of main plant nutrition components, pollutants, and other important soil parameters (pH, moisture content, salinity, exhaled gases, etc.) of the past two decades with a focus on the last 5 years (from 2017 to 2021) are overviewed.

Point-of-use sensors and machine learning enable low-cost determination of soil nitrogen

Overfertilization with nitrogen fertilizers has damaged the environment and health of soil, but standard laboratory testing of soil to determine the levels of nitrogen (mainly NH₄⁺ and NO₃^-) is not performed regularly. Here we demonstrate that point-of-use measurements of NH₄⁺, combined with soil conductivity, pH, easily accessible weather and timing data, allow instantaneous prediction of levels of NO₃^- in soil (R² = 0.70) using a machine learning model. A long short-term memory recurrent neural network model can also be used to predict levels of NH₄⁺ and NO₃^- up to 12 days into the future from a single measurement at day one, with [Formula: see text] and [Formula: see text], for unseen weather conditions. Our machine-learning-based approach eliminates the need for dedicated instruments to determine the levels of NO₃^- in soil. Nitrogenous soil nutrients can be determined and predicted with enough accuracy to forecast the impact of climate on fertilization planning and to tune timing for crop requirements, reducing overfertilization while improving crop yields.

An Electrochemical Enzyme Biosensor for Ammonium Detection in Aquaculture Using Screen-Printed Electrode Modified by Gold Nanoparticle/Polymethylene Blue

A SPEC/AuNPs/PMB modified electrode was prepared by electrodeposition and electro-polymerization. The electrochemical behavior of reduced nicotinamide adenine dinucleotide (NADH) on the surface of the modified electrode was studied by cyclic voltammetry. A certain amount of substrate and glutamate dehydrogenase (GLDH) were coated on the modified electrode to form a functional enzyme membrane. The ammonia nitrogen in the water sample could be calculated indirectly by measuring the consumption of NADH in the reaction. The results showed that the strength of electro-catalytic current signal was increased by two times; the catalytic oxidation potential was shifted to the left by 0.5 V, and the anti-interference ability of the sensor was enhanced. The optimum substrate concentration and enzyme loading were determined as 1.3 mM NADH, 28 mM α-Ketoglutarate and 2.0 U GLDH, respectively. The homemade ceramic heating plate controlled the working electrode to work at 37 °C. A pH compensation algorithm based on piecewise linear interpolation could reduce the measurement error to less than 3.29 μM. The biosensor exhibited good linearity in the range of 0~300 μM with a detection limit of 0.65 μM NH₄⁺. Compared with standard Nessler's method, the recoveries were 93.71~105.92%. The biosensor was found to be stable for at least 14 days when refrigerated and sealed at 4 °C.

Internet of Things Implementation of Nitrate and Ammonium Sensors for Online Water Monitoring

In this work, we proposed a new wireless sensor to contribute to research aimed at continuous monitoring of nitrate and ammonium in water, which as leading agents of water pollution have become the source of a serious problem today. In this research, a well-implemented application of an electroanalytical sensor was achieved by combining it with the internet of things (IoT) concept, which is the most modern technique for wireless data collection. We developed a portable IoT system and ion-selective nitrate and ammonium electrodes and monitored the nitrate and ammonium levels of the water online. The system was produced in a low-cost manner (under $25) and it enabled data acquisition without energy-related problems, thanks to the support of solar energy and mobile power bank. The recovery rates of the sensors were tested with the standard addition method and response was obtained between 101.74 and 147.01%.

Recent Advancement of the Sensors for Monitoring the Water Quality Parameters in Smart Fisheries Farming

Water quality is the most critical factor affecting fish health and performance in aquaculture production systems. Fish life is mostly dependent on the water fishes live in for all their needs. Therefore, it is essential to have a clear understanding of the water quality requirements of the fish. This research discusses the critical water parameters (temperature, pH, nitrate, phosphate, calcium, magnesium, and dissolved oxygen (DO)) for fisheries and reviews the existing sensors to detect those parameters. Moreover, this paper proposes a prospective solution for smart fisheries that will help to monitor water quality factors, make decisions based on the collected data, and adapt more quickly to changing conditions.

An All-Solid-State Nitrate Ion-Selective Electrode with Nanohybrids Composite Films for In-Situ Soil Nutrient Monitoring

In this paper, an all-solid-state nitrate doped polypyrrole (PPy(NO₃⁻) ion-selective electrode (ISE) was prepared with a nanohybrid composite film of gold nanoparticles (AuNPs) and electrochemically reduced graphene oxide (ERGO). Preliminary tests on the ISE based in-situ soil nitrate–nitrogen (NO₃⁻-N) monitoring was conducted in a laboratory 3-stage column. Comparisons were made between the NO₃⁻-N content of in-situ soil percolate solution and laboratory-prepared extract solution. Possible influential factors of sample depth, NO₃⁻-N content, soil texture, and moisture were varied. Field-emission scanning electron microscopy (FESEM) and X-ray powder diffraction (XRD) characterized morphology and content information of the composite film of ERGO/AuNPs. Due to the performance excellence for conductivity, stability, and hydrophobicity, the ISE with ERGO/AuNPs illustrates an acceptable detection range from 10⁻¹ to 10⁻⁵ M. The response time was determined to be about 10 s. The lifetime was 65 days, which revealed great potential for the implementation of the ERGO/AuNPs mediated ISE for in-situ NO₃⁻-N monitoring. In-situ NO₃⁻-N testing results conducted by the all-solid-state ISE followed a similar trend with the standard UV-VIS method.

Why ammonium detection is particularly challenging but insightful with ionophore-based potentiometric sensors – an overview of the progress in the last 20 years

An overview of ionophore-based electrodes for ammonium sensing critically analyzing contributions in the last 20 years and with focus in analytical applications.

Disposable Multi-Walled Carbon Nanotubes-Based Plasticizer-Free Solid-Contact Pb2+-Selective Electrodes with a Sub-PPB Detection Limit †

Potentiometric plasticizer-free solid-contact Pb²⁺-selective electrodes based on copolymer methyl methacrylate-n-butyl acrylate (MMA-BA) as membrane matrix and multi-walled carbon nanotubes (MWCNTs) as intermediate ion-to-electron transducing layer have been developed. The disposable electrodes were prepared by drop-casting the copolymer membrane onto a layer of MWCNTs, which deposited on golden disk electrodes. The obtained electrodes exhibited a sub-ppb level detection limit of 10⁻¹⁰ mol·L⁻¹. The proposed electrodes demonstrated a Nernstian slope of 29.1 ± 0.5 mV/decade in the linear range from 2.0 × 10⁻¹⁰ to 1.5 × 10⁻³ mol·L⁻¹. No interference from gases (O₂ and CO₂) or water films was observed. The electrochemical impedance spectroscopy of the fabricated electrodes was compared to that of plasticizer-free Pb²⁺-selective electrodes without MWCNTs as intermediated layers. The plasticizer-free MWCNTs-based Pb²⁺-selective electrodes can provide a promising platform for Pb(II) detection in environmental and clinical application.

Additively Manufactured Digital Microfluidic Platforms for Ion-Selective Sensing

Digital microfluidic (DMF) sensors integrated with circuit systems have been applied to a broad range of applications including biology, medicine, and chemistry. Compared with the conventional microfluidic devices that require extra liquid as a carrier and a complex pumping system to operate, DMF is an ideal platform for ion-selective sensing as it enables the droplet operation in a discrete, accurate, and automatic way. However, it is quite rare that DMF platform is utilized for the ion-selective detection. In this paper, we report an integrated DMF system which combines DMF and ion-selective sensing for facile blending of multiple ions, and detection of targeted primary ion. The platform is fabricated through an additive manufacturing method, together with the real-time droplet's motion monitoring feedback system. Thus, the fabricated system demonstrates controlled droplet manipulation ability including droplet actuation, mixing, and speed control. Targeted primary ion is selectively detected under concentration range from 10^-6 to 1 M. The interference study with blended ions has been investigated through on-chip ion selective membranes.