Potentiometric Transduction Research Articles

Optimization and Evaluation of Potentiometric Sensing Membranes for Vildagliptin Determination: A Sustainable Approach Incorporating Whiteness and Greenness Assessment

In the current environmental context, incorporating green analytical chemistry principles into analytical chemistry analysis shows great promise. In drug analysis, the most important objective is to develop techniques that are cost-efficient, eco-friendly, and of high quality. Our study highlights the novelty of utilizing greenness and whiteness approaches in developing a solid-state electrochemical sensor for Vildagliptin (VILD) detection. The sensor employs potentiometric transduction and underwent a dual-phase adjustment process. Initially, various ionophores were evaluated to enhance sensor specificity, followed by the incorporation of a multi-walled carbon nanotube layer as a mediator for ion-to-electron conversion. The selected ionophore was then employed to complete the assessment of VILD. The linearity range obtained was 1.00 × 10−5 M – 1.00 × 10−2 M with a limit of detection of 7.94 × 10−6 M. This sensor demonstrated effectiveness in the selective determination of VILD in bulk powdered material and pharmaceutical formulations. Environmental impact evaluation was performed using the Green Analytical Procedure Index (GAPI) and the Analytical Greenness Calculator (AGREE), comparing it to a previous method. Additionally, The RGB model assessed both method’s whiteness. Our investigation reveals the proposed method as an excellent eco-friendly approach compared to the reported method.

Microfabricated potentiometric sensor based on a carbon nanotube transducer layer for selective Bosentan determination

Abstract In this work, a solid-state electrochemical sensor relying on potentiometric transduction was constructed and optimized to detect Bosentan (BOS) in its pharmaceutical dosage form and human plasma. BOS is useful in pulmonary hypertension management as a nonselective endothelin receptor antagonist. A printed circuit board has been constructed and used as a substrate for microfabricated Cu electrodes. In comparison to a microfabricated control (Cu/ISM) electrode, the sensor potential signal drift was enhanced, and the response time was reduced by using multi-walled carbon nanotubes (MWCNTs) as an ion-to-electron transducer layer. According to IUPAC requirements, the suggested BOS sensors have been electrochemically characterized, and the linear dynamic range is (1.0 × 10−8 to 1.0 × 10−5) M with a limit of detection of 6.28 × 10−9 M and 6.12 × 10−9 M for MWCNT-based sensor (Cu/CNT-NC/ISM) and control sensor (Cu/ISM), respectively. The described sensors have been used successfully to selectively determine BOS in dosage form and human plasma without any pre-treatment steps.

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

Paper-Based Analytical Device Based on Potentiometric Transduction for Sensitive Determination of Phenobarbital.

In medicine, barbiturates are a class of depressive medications used as hypnotics, anticonvulsants, and anxiolytics. For the treatment of specific forms of epilepsy and seizures in young children in underdeveloped countries, the World Health Organization recommends phenobarbital (PBAR), a barbiturate drug. This review describes the fabrication and characterization of a paper-based analytical apparatus for phenobarbital detection that is straightforward, affordable, portable, and disposable. All of the solid-state ion-selective electrodes (ISEs) for PBAR as well as a Ag/AgCl reference electrode were constructed and optimized on a nonconductive paper substrate. Using carbon nanotube ink, the sensors were made to function as an ion-to-electron transducer and to make the paper conductive. A suitable polymeric membrane is drop-cast onto the surface of the carbon ink orifice. The pyrido-tetrapeptide and pyrido-hexapeptide derivatives, which were recently synthesized, functioned as distinct ionophores in the PBAR-membrane sensor, enabling its detection. With a detection limit of 5.0 × 10-7 M, the manufactured analytical device demonstrated a Nernstian response to PBAR anions in 50 mM phosphate buffer, pH 8.5, over a linear range of 1.0 × 10-6 to 1.0 × 10-3 M. The PBAR-based sensors showed quick (less than 5 s) response times for PBAR ion detection. The modified separate solution method was utilized to evaluate the selectivity pattern of these novel ionophores with respect to PBAR ions in comparison to other common anions. The analytical instrument that was exhibited on paper had good precision both within and between days. The suggested technology assisted in the detection of trace amounts of PBAR in real pharmaceutical samples. A comparison was made between the data acquired using the HPLC reference method and the information obtained by the recommended potentiometric approach. The described paper-based analytical device may be a good choice for point-of-care PBAR determination because it is cheap and easy to find and can self-pump (especially when combined with potentiometric detection).

Molecularly Imprinted Polymer Modified with an MWCNT Nanocomposite for the Fabrication of a Barbital Solid-Contact Ion-Selective Electrode.

For potentiometric sensing of barbital (BAR), unique micro-sized imprinted polymer/multiwalled carbon nanotube (MWCNT)-based sensors are introduced. MWCNT is a lipophilic ion-to-electron transducing substance. A synthetic, described, and integrated barbital sodium molecular imprinted polymer (MIP) was used as a recognition receptor for potentiometric transduction in a plasticized polyvinyl chloride membrane. Methacrylic acid and ethylene glycol dimethacrylic acid are used as the functional monomer and crosslinking agent, respectively, in the synthesis of the MIPs. In the operating concentration range of 1.0 × 10–3 to 2.0 × 10–7 M, the sensors’ Nernstian slope was −56.8 ± 0.9 mV/decade, with a detection limit of 1.0 × 10–7 M. The sensor displayed an accurate response time of 10 s and consistent potential response in the pH range of 8.5–11. Using chronopotentiometry tests, the interfacial capacitance of the presented ion-to-electron transducer was assessed. When compared to sensors without MWCNTs, the interfacial double-layer capacitance for sensors based on those layers reached 52.5 μF. After the addition of the MWCNTs nanocomposite layer, the water layer was eliminated between the sensing membrane and the conducting substrate. A wide range of applications for the proposed sensors for BAR detection in real samples can be provided by the sensors’ strong selectivity over the interfering species. The suggested sensors were successfully used to determine BAR in urine samples that had been spiked.

Roles of MXene in Pressure Sensing: Preparation, Composite Structure Design, and Mechanism.

Flexible pressure sensors are one of the most important components in the fields of electronic skin (e-skin), robotics, and health monitoring. However, the application of pressure sensors in practice is still difficult and expensive due to the limited sensing properties and complex manufacturing process. The emergence of MXene, a red-hot member of the 2D nanomaterials, has brought a brand-new breakthrough for pressure sensing. Ti3 C2 Tx is the most popular studied MXene in the field of pressure sensing and shows good mechanical, electrical properties, excellent hydrophilicity, and extensive modifiability. It will ameliorate the properties of the sensitive layer and electrode layer of the pressure sensor, and further apply pressure sensing to many fields, such as e-skin flexibility. Herein, the preparation technologies, antioxidant methods, and properties of MXene are summarized. The design of MXene-based microstructures is introduced, including hydrogels, aerogels, foam, fabrics, and composite nanofibers. The mechanisms of MXene pressure sensors are further broached, including piezoresistive, capacitive, piezoelectric, triboelectric, and potentiometric transduction mechanism. Moreover, the integration of multiple devices is reviewed. Finally, the chance and challenge of pressure sensors improved by MXene smart materials in future e-skin and the Internet of Things are prospected.

New Potentiometric Screen-Printed Platforms Modified with Reduced Graphene Oxide and Based on Man-Made Imprinted Receptors for Caffeine Assessment.

Caffeine is a psychoactive drug that is administered as a class II psychotropic substance. It is also considered a component of analgesics and cold medicines. Excessive intake of caffeine may lead to severe health damage or drug addiction problems. The assessment of normal caffeine consumption from abusive use is not conclusive, and the cut-off value for biological samples has not been established. Herein, new cost-effective and robust all-solid-state platforms based on potentiometric transduction were fabricated and successfully utilized for caffeine assessment. The platforms were modified with reduced graphene oxide (rGO). Tailored caffeine-imprinted polymeric beads (MIPs) based on methacrylic acid (MAA) and ethylene glycol dimethacrylate (EGDMA) were prepared, characterized, and used as recognition receptors in the presented potentiometric sensing devices. In 50 mM MES buffer, the sensors exhibited a slope response of 51.2 ± 0.9 mV/decade (n = 6, R2 = 0.997) over the linear range of 4.5 × 10−6–1.0 × 10−3 M with a detection limit of 3.0 × 10−6 M. They exhibited fast detection of caffeinium ions with less than 5 s response time (<5 s). The behavior of the presented sensors towards caffeinium ions over many common organic and inorganic cations was evaluated using the modified separate solution method (MSSM). Inter-day and intra-day precision for the presented analytical device was also evaluated. Successful applications of the presented caffeine sensors for caffeine determination in commercial tea and coffee and different pharmaceutical formulations were carried out. The data obtained were compared with those obtained by the standard liquid chromatographic approach. The presented analytical device can be considered an attractive tool for caffeine determination because of its affordability and vast availability, particularly when combined with potentiometric detection.

Potentiometric Biosensor Based on Artificial Antibodies for an Alzheimer Biomarker Detection

This paper presents a potentiometric biosensor for the detection of amyloid β-42 (Aβ-42) in point-of-care analysis. This approach is based on the molecular imprint polymer (MIP) technique, which uses covalently immobilised Aβ-42 to create specific detection cavities on the surface of single-walled carbon nanotubes (SWCNTs). The biosensor was prepared by binding Aβ-42 to the SWCNT surface and then imprinting it by adding acrylamide (monomer), N,N′-methylene-bis-acrylamide (crosslinker) and ammonium persulphate (initiator). The target peptide was removed from the polymer matrix by the proteolytic action of an enzyme (proteinase K). The presence of imprinting sites was confirmed by comparing a MIP-modified surface with a negative control (NIP) consisting of a similar material where the target molecule had been removed from the process. The ability of the sensing material to rebind Aβ-42 was demonstrated by incorporating the MIP material as an electroactive compound in a PVC/plasticiser mixture applied to a solid conductive support of graphite. All steps of the synthesis of the imprinted materials were followed by Raman spectroscopy and Fourier transform infrared spectroscopy (FTIR). The analytical performance was evaluated by potentiometric transduction, and the MIP material showed cationic slopes of 75 mV-decade−1 in buffer pH 8.0 and a detection limit of 0.72 μg/mL. Overall, potentiometric transduction confirmed that the sensor can discriminate Aβ-42 in the presence of other biomolecules in the same solution.

Nanoparticle-enhanced in-line potentiometric ion sensor for point-of-care diagnostics for tropicamide abuse in biological fluid

Point of care (POC), also identified as on-site testing, has evolved as a rapid and accurate technique for drug of abuse screening and analysis. The aim of this work is to detect tropicamide (TPC) abuse in biological fluids; we selected rat plasma as example. We developed a disposal miniaturized, portable, green, and budget-friendly POC solid-state electrochemical sensor based on potentiometric transduction. To attain that, an innovative microfabricated electrode modified with conducting polymer poly(3-octylthiophene) (POT) has been placed on sensitized printed circuit board (PCB). A two-stage optimization process was implemented to develop the fabricated electrode. The first stage of the optimization process depends on screening various ionophores in order to enhance the sensor selectivity towards tropicamide. Copper nanoparticles exhibited the highest selectivity towards TPC. The second stage was utilizing a polymer as an ion-to-electron transducer layer between the copper nanoparticles impregnated ion sensing membrane and the microfabricated solid-contact ion-selective electrode. This polymer was added to boost the stability of the potential drift (1.2 mV/h) due to the hydrophobic behavior of the POT, which precludes the formation of an aqueous layer at the Cu electrode/polymeric membrane interface and improve the limit of detection (1.1 × 10−8 M). Nernstian potentiometric response was accomplished for TPC with a slope of 58.46 ± 0.43 mV/decade and E0 ∼ 189.39 ± 2.12 over the concentration range 1.0 × 10−7 to 1.0 × 10−2 M. The suggested sensor's intrinsic figure of merits include a quick response time (13 ± 2 s) and long life time (45 days). The proposed sensor has been successfully employed in the selective determination of TPC in pharmaceutical formulations, and biological fluids. When the results were compared to those of the official approach, there was no statistically significant difference. The Eco-Scale tool assessed and measured the greenness profile of the established method.

An Ion Channel‐Induced Self‐Powered Flexible Pressure Sensor Based on Potentiometric Transduction Mechanism

AbstractGreat efforts have been made to build multifunctional flexible pressure sensing devices to enable future wearable electronics. However, a green‐safe, cost‐effective, self‐powered integrated pressure sensing system remains challenging. Herein, an all‐solid‐state pressure sensing rGM (rGO/GO/PVA nanofibers/MXene) system is designed and developed based on a mechanical potentiometric transduction (MPT) mechanism, which converts mechanical stimulation into the change in the ion transport channel and encodes it into the measured potential difference between two electrodes with hydrated GO, thereby generating potential conduction behavior as well as a programmable stable voltage and current. The self‐powered rGM sensor can yield an output open‐circuit voltage of 0.58 V and a short‐circuit current density of 3.2 µA cm–2 when experiencing a steady mechanical pressure. Unlike typical pressure sensors, rGM sensors have an ultrawide detection range (0.7 Pa–1300 kPa), high stability (maintain 95% performance after 5000 cycles), high adjustability, simple preparation method, implying that the rGM sensor can provide real‐time monitoring for human physiological signals without an external power supply, which has a wide‐range impact on medical care. This work presents a new design based on the MPT mechanism that will significantly simplify manufacturing while improving the performance of future electronic devices and smart systems.

Advanced Wound Dressing for Real-Time pH Monitoring.

The rapid evolution of wearable technologies is giving rise to a strong push for textile chemical sensors design targeting the real-time collection of vital parameters for improved healthcare. Among the most promising applications, monitoring of nonhealing wounds is a scarcely explored medical field that still lacks quantitative tools for the management of the healing process. In this work, a smart bandage is developed for the real-time monitoring of wound pH, which has been reported to correlate with the healing stages, thus potentially giving direct access to the wound status without disturbing the wound bed. The fully textile device is realized by integrating a sensing layer, including the two-terminal pH sensor made of a semiconducting polymer and iridium oxide particles, and an absorbent layer ensuring the delivery of a continuous wound exudate flow across the sensor area. The two-terminal sensor exhibits a reversible response with a sensitivity of (59 ± 4) μA pH–1 in the medically relevant pH range for wound monitoring (pH 6–9), and its performance is not substantially affected either by the presence of the most common chemical interferents or by temperature gradients from 22 to 40 °C. Thanks to the robust sensing mechanism based on potentiometric transduction and the simple device geometry, the fully assembled smart bandage was successfully validated in flow analysis using synthetic wound exudate.

Screen-Printed Sensor Based on Potentiometric Transduction for Free Bilirubin Detection as a Biomarker for Hyperbilirubinemia Diagnosis

Novel reliable and cost-effective potentiometric screen-printed sensors for free bilirubin (BR) detection were presented. The sensors were fabricated using ordered mesoporous carbon (OMC) as an ion-to-electron transducer. The ion-association complex [Ni(bphen)3]2+[BR]2− was utilized as a sensory recognition material in the plasticized Polyvinyl Chloride (PVC) membrane. The membrane was drop-casted on the OMC layer, which is attached on a carbon conductor (2-mm diameter). In a 50 mM phosphate solution of pH 8.5, the electrodes offered a Nernstian slope of −26.8 ± 1.1 (r2 = 0.9997) mV/decade with a range of linearity 1.0 × 10−6–1 × 10−2 M towards free bilirubin with a detection limit 8.8 × 10−7 M (0.52 µg/mL). The presented sensors offered good features in terms of reliability, ease of design, high potential stability, high specificity and good accuracy and precision. Chronopotentiometric and electrochemical impedance spectrometric measurements were used for short-term potential stability and interfacial capacitance calculations. The sensors were used for the determination of free bilirubin in biological fluids. The data obtained are fairly well consistent with those obtained by the reference spectophotometric method. Based on the interaction of free BR with albumin (1:1), the sensors were also utilized for the assessment of albumin in human serum.

Point-of-care diagnostics for drugs of abuse in biological fluids: application of amicrofabricated disposable copper potentiometric sensor.

The major objective of this work was to develop a portable, disposable, cost-effective, and reliable POC solid-state electrochemical sensor based on potentiometric transduction to detect benzodiazepine abuse, mainly diazepam (DZP), in biological fluids. To achieve that, microfabricated Cu electrodes on aprinted circuit board modified with the conducting polymer poly(3-octylthiophene) (POT) have been employed as a substrate. This polymer was introduced to enhance the stability of the potential drift (0.9mV/h) and improve the limit of detection (0.126nmolmL-1). Nernstian potentiometric response was achieved for DZP over the concentration range 1.0 × 10-2 to 5.0 × 10-7molL-1 with a slope of 55.0 ± 0.4mV/decade and E0 ~ 478.9 ± 0.9. Intrinsic merits of the proposed sensor include rapid response time (11± 2s) and long life time (3months). In order to enhance the selectivity of the potentiometric sensor towards the target drug and minimize any false positive results, calix[4]arene (CX4) was impregnated as an ionophore within the PVC plastic ion-sensing membrane. The performance of the POC sensors was assessed using electrochemical methods of analysis and electrochemical impedance spectroscopy as a surface characterization tool. The studied sensors were applied tothe potentiometric determination of DZP in different biological fluids (plasma, urine, saliva, and human milk) in the presence of its metabolite with an average recovery of100.9± 1.3%, 99.4 ± 1.0%, 101.8 ± 1.2%, and 99.0 ± 2.0%, respectively. Graphical abstract.

Rapid and Accurate Validated Potentiometric Method for Bispyribac Herbicide Assessment in Rice and Agricultural Wastewater

A new validated method based on potentiometric transduction for bispyribac herbicide assessment in commercial formulations, rice and wastewater samples is fabricated and characterized. Sensors are based in terms of their fabrication on tridodecyl methyl ammonium chloride (TDMAC) as recognition material. TDMAC was plasticized in a poly (vinyl chloride) (PVC) matrix to prepare the membrane. Under static modes of operation, the sensors revealed a Nernstian anionic slope of −63.6 ± 0.7 mV/decade within a linear range of 9.1 × 10−6–1.0 × 10−2 in 50 mM phosphate buffer solution (PBS), pH7. The detection limit was 6.0 × 10−6 M. The sensor was successfully introduced in a flow-stream system revealing a Nernstian response of −53.8 ± 1.3 mV/decade over a linear range of 2 × 10−4–1.0 × 10−2 M and lower detection limit of 5.6 × 10⁻⁵ M. The sampling rate was calculated to be (~42 sample/h). Validation of the assay method is presented in detail including accuracy, trueness, bias, between-day variability and within-day variability, and good performance characteristics of the method are obtained. The presented method was successfully introduced to bispyribac determination in different complex matrices such as commercial bispyribac sodium known as (Nominee-kz, 3% soluble liquid (SL)), rice samples and agricultural wastewater samples. The samples were analyzed successfully under both static and hydrodynamic modes of operation. The results obtained were in a good agreement with those obtained by the liquid chromatographic method.

Novel Validated Analytical Method Based on Potentiometric Transduction for the Determination of Citicoline Psychostimulant/Nootropic Agent.

Herein, a novel validated potentiometric method is presented for the first time for citicoline determination. The method is based on measuring the potential using new constructed citicoline electrodes. The electrodes are based on the use of citicolinium/phosphomolybdate [Cit]2[PM] (sensor I) and citicolinium/tetraphenylborate [Cit][TPB] (sensor II) ion association complexes. These sensory materials were dispersed in plasticized polyvinyl chloride (PVC) polymeric membranes. The sensors revealed a Nernstian response with the slopes 55.9 ± 1.8(r2 = 0.9994) and 51.8 ± 0.9 (r2 = 0.9991) mV/decade over a linearity range of 6.3 × 10−6–1.0 × 10−3 and 1.0 × 10−5–1.0 × 10−3 M and detection limits of 3.16 × 10−6 and 7.1 × 10−6 M for sensors I and II, respectively. To ensure the existence of monovalent citicoline, all measurements were performed in 50 mM acetate buffer at pH 3.5. All presented electrodes showed good performance characteristics such as rapid response, good selectivity, high potential-stability and long life-span. Method verification and validation in terms of response linearity, quantification limit, accuracy, bias, trueness, robustness, within-day variability and between-days variability were evaluated. The method was introduced for citicoline determination in different pharmaceutical formulations and compared with the standard high performance liquid chromatography (HPLC) method.

Solid-Contact Potentiometric Sensors Based on Stimulus-Responsive Imprinted Polymers for Reversible Detection of Neutral Dopamine.

Herein, we present for the first time a novel potentiometric sensor based on the stimulus-responsive molecularly imprinted polymer (MIP) as a selective receptor for neutral dopamine determination. This smart receptor can change its capabilities to recognize according to external environmental stimuli. Therefore, MIP-binding sites can be regenerated in the polymeric membrane by stimulating with stimulus after each measurement. Based on this effect, reversible detection of the analyte via potentiometric transduction can be achieved. MIPs based on 4-vinylphenylboronic acid as the functional monomer were prepared as the selective receptor. This monomer can successfully bind to dopamine via covalent binding and forming a five- or six-membered cyclic ester in a weakly alkaline aqueous solution. In acidic medium, the produced ester dissociates and regenerates new binding sites in the polymeric membrane. The proposed smart sensor exhibited fast response and good sensitivity towards dopamine with a limit of detection 0.15 µM over the linear range 0.2–10 µM. The selectivity pattern of the proposed ISEs was also evaluated and revealed an enhanced selectivity towards dopamine over several phenolic compounds. Constant-current chronopotentiometry is used for evaluating the short-term potential stability of the proposed ISEs. The obtained results confirm that the stimulus-responsive MIPs provide an attractive way towards reversible MIP-based electrochemical sensors designation.

Validation of a Novel Potentiometric Method Based on a Polymeric PVC Membrane Sensor Integrated with Tailored Receptors for the Antileukemia Drug Cytarabine.

A simple, rapid and easy method is proposed for the detection of a cytostatic therapeutic drug, cytarabine, in real samples. The method is based on potentiometric transduction using prepared and characterized new ion-selective electrodes for cytarabine. The electrodes were integrated with novel man-tailored imprinted polymers and used as a sensory element for recognition. The electrodes revealed a remarkable potentiometric response for cytarabine over the linearity range 1.0 × 10−6–1.0 × 10−3 M at pH 2.8–4 with a detection limit of 5.5 × 10−7 M. The potentiometric response was near-Nernstian, with average slopes of 52.3 ± 1.2 mV/decade. The effect of lipophilic salts and plasticizer types on the potentiometric response was also examined. The electrodes exhibited an enhanced selectivity towards cytarabine over various foreign common ions. Validation and verification of the presented assay method are demonstrated by evaluating the method ruggedness and calculating the detection limit, range of linearity, accuracy (trueness), precision, repeatability (within-day) and reproducibility (between-days). The proposed ion-selective electrodes revealed good performance characteristics and possible application of these electrodes for cytarabine monitoring in different matrices. The electrodes are successfully applied to cytarabine determination in spiked biological fluid samples and in pharmaceutical formulations.

Organic Electrochemical Transistors as Versatile Analytical Potentiometric Sensors.

Potentiometric transduction is an important tool of analytical chemistry to record chemical signals, but some constraints in the miniaturization and low-cost fabrication of the reference electrode are a bottleneck in the realization of more-advanced devices such as wearable and lab-on-a-chip sensors. Here, an organic electrochemical transistor (OECT) has been designed with an alternative architecture that allows to record the potentiometric signals of gate electrodes, which have been chemically modified to obtain Ag/AgnX interfaces (X = Cl−, Br−, I−, and S2−), without the use of a reference electrode. When the OECT is immersed in a sample solution, it reaches an equilibrium state, because PEDOT:PSS exchanges charges with the electrolyte until its Fermi level is aligned to the one of Ag/AgnX. The latter is controlled by Xn− concentration in the solution. As a consequence, in this spontaneous process, the conductivity of PEDOT:PSS changes with the electrochemical potential of the modified gate electrode without any external bias. The sensor works by applying only a fixed drain current or drain voltage and thus the OECT sensor operates with just two terminals. It is also demonstrated that, in this configuration, gate potential values extracted from the drain current are in good agreement with the ones measured with respect to a reference electrode being perfectly correlated (linear slope equal to 1.00 ± 0.03). In the case of the sulfide anion, the OECT performance overcomes the limit represented by the Nernst equation, with a sensitivity of 0.52 V decade−1. The presented results suggest that OECTs could be a viable option to fabricate advanced sensors based on potentiometric transduction.

Use of Cucurbit[6]uril as Ionophore in Ion Selective Electrodes for Etilefrine Determination in Pharmaceuticals

AbstractCucurbiturils are macrocyclic molecules and have been used with promising results in the development of electrochemical sensors and biosensors due to their main properties such as shape, selectivity, binding interactions and solubility. However, its application for the development of ion selective electrodes has been scarce. In this work, cucurbit[6]uril was used as molecular‐recognition compound for etilefrine sensing membrane with potentiometric transduction. The etilefrine selective electrode was evaluated and proposed as an alternative methodology for pharmaceutical quality control. Different membranes composition were evaluated, considering the use of different solvent mediators and the presence of anionic additives. The best membrane comprises 9.24 mmol.Kg−1 of cucurbit[6]uril, 68.90 % (w/w) of dibutylsebacate and 30.18 % (w/w) of carboxylated polyvinyl chloride. The electrode exhibited selective cationic response toward the etilefrine in a concentration interval of more than four decades, with an slope of 57.4±0.5 mV dec−1, a practical detection limit of (8±1)×10−7 mol L−1 and a low limit of linear range of (1.25±0.28)×10−6 mol L−1. The selectivity of the electrode towards different interfering was high. A comparative evaluation of the accuracy and precision of both procedures was done using the t‐student test (t4,12=1.135) and the Fischer test (F12,4=2.42) and compared with the tabulated ones (t4,12=1.135, F11,3=5.91) for the level of confidence of 95 %.

Antibody Biomimetic Material Made of Pyrrole for CA 15-3 and Its Application as Sensing Material in Ion-Selective Electrodes for Potentiometric Detection.

This work reports a very simple approach for creating a synthetic antibody against any protein of interest and its application in potentiometric transduction. The selected protein was Breast Cancer Antigen (CA 15-3), which is implicated in breast cancer disease and used to follow-up breast cancer patients during treatment. The new material with antibody-like properties was obtained by molecular-imprinting technology, prepared by electropolymerizing pyrrol (Py, 5.0 × 10−3 mol/L) around Breast Cancer Antigen (CA 15-3) (100 U/mL) on a fluorine doped tin oxide (FTO) conductive glass support. Cyclic voltammetry was employed for this purpose. All solutions were prepared in 4-(2-Hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) buffer, of pH 6.5. The biomarker was removed from the imprinted sites by chemical action of ethanol. The biomimetic material was then included in poly vinyl chloride (PVC) plasticized membranes to act as potentiometric ionophore, having or not a lipophilic ionic additive added. The corresponding selective electrodes were evaluated by calibration curves (in buffer and in synthetic serum) and by selectivity testing. The best analytical performance was obtained by selective electrodes including the plastic antibody and no lipophilic additive. The average limits of detection were 1.07 U/mL of CA 15-3, with a linear response from 1.44 to 13.2 U/mL and a cationic slope of 44.5 mV/decade. Overall, the lipophilic additives yielded no advantage to the overall potentiometric performance. The application of the MIP-based electrodes to the analysis of spiked synthetic serum showed precise and accurate results.