Use of an Electronic Tongue Based on All‐Solid‐State Potentiometric Sensors for the Quantitation of Alkaline Ions

An array of eight nonspecific potentiometric sensors was used in combination with multivariate calibration for the simultaneous determination of NH , K⁺ and Na⁺ ions. The sensors were of the all‐solid‐state type and employed a PVC polymer membrane. Signals were processed by using a multilayer artificial neural network (ANN). The ANN configuration used was optimized by using 8 neurons in the input layer, 5 in the hidden layer and 3 in the output layer. Use of the Bayesian Regularization algorithm allowed a quick building of an accurate model, as confirmed by random multi‐starting of network weights. The system was used to analyze synthetic and river water, waste water and fertilizer samples. Correct results were obtained for the three ions in synthetic and real water samples; in fertilizers, ammonium ion can be determined, while sodium and potassium show biased results.     

Use of sequential injection analysis to construct an electronic-tongue: application to multidetermination employing the transient response of a potentiometric sensor array

An electronic tongue based on the transient response of an array of non-specific-response potentiometric sensors was developed. A sequential injection analysis (SIA) system was used in order to automate its training and operation. The use of the transient recording entails the dynamic nature of the sensor's response, which can be of high information content, of primary ions and also of interfering ions; these may better discriminated if the kinetic resolution is added. This work presents the extraction of significant information contained in the transient response of a sensor array formed by five all-solid-state potentiometric sensors. The tool employed was the Fourier transform, from which a number of coefficients were fed into an artificial neural network (ANN) model, used to perform a quantitative multidetermination. The studied case was the analysis of mixtures of calcium, sodium and potassium. Obtained performance is compared with the more traditional automated electronic tongue using final steady-state potentials.     

An electronic tongue using potentiometric all-solid-state PVC-membrane sensors for the simultaneous quantification of ammonium and potassium ions in water

The simultaneous determination of NH₄⁺ and K⁺ in solution has been attempted using a potentiometric sensor array and multivariate calibration. The sensors used are rather non-specific and of all-solid-state type, employing polymeric (PVC) membranes. The subsequent data processing is based on the use of a multilayer artificial neural network (ANN). This approach is given the name "electronic tongue" because it mimics the sense of taste in animals. The sensors incorporate, as recognition elements, neutral carriers belonging to the family of the ionophoric antibiotics. In this work the ANN type is optimized by studying its topology, the training algorithm, and the transfer functions. Also, different pretreatments of the starting data are evaluated. The chosen ANN is formed by 8 input neurons, 20 neurons in the hidden layer and 2 neurons in the output layer. The transfer function selected for the hidden layer was sigmoidal and linear for the output layer. It is also recommended to scale the starting data before training. A correct fit for the test data set is obtained when it is trained with the Bayesian regularization algorithm. The viability for the determination of ammonium and potassium ions in synthetic samples was evaluated; cumulative prediction errors of approximately 1% (relative values) were obtained. These results were comparable with those obtained with a generalized regression ANN as a reference algorithm. In a final application, results close to the expected values were obtained for the two considered ions, with concentrations between 0 and 40 mmol L^–1.     

Novel Dicyanoargentate Polymeric Membrane Sensors for Selective Determination of Cyanide Ions

The construction and general performance characteristics of three novel potentiometric PVC membrane sensors responsive to dicyanoargentate anion are described. The sensors are based on the use of magnesium(II)‐ and iron(II)‐phthalocyanines as neutral ionophores and iron(II)‐bathophenanthroline dicyanoargentate ion‐pair complex as an ion exchanger in plasticized PVC matrices. These sensors exhibit fast, stable and near‐Nernstian response (54–59 mV/decade) for the singly charged dicyanoargentate anion over the concentration range 1×10^?2–5.8×10^?6 M. Potentiometric responses of sensors based on metal phthalocyanines and iron(II)‐bathophenanthroline are stable over the pH ranges 5–7 and 5–12, respectively. The selectivity of the sensors are fairly good over most common anions. Use of the sensors for potentiometric determination of microgram quantities of cyanide ion after conversion into dicyanoargentate anions shows an average recovery of 99.5% and a mean standard deviation of ±0.5%. Determination of cyanide ions in some exhausted electroplating bath samples gives results that compare favourably well with data obtained using the solid‐state cyanide electrode.     

Sequential injection system with higher dimensional electrochemical sensor signals Part 2. Potentiometric e-tongue for the determination of alkaline ions

An intelligent, automatic system based on an array of non-specific-response chemical sensors was developed. As a great amount of information is required for its correct modelling, we propose a system generating it itself. The sequential injection analysis (SIA) technique was chosen as it enables the processes of training, calibration, validation and operation to be automated simply. Detection was carried out using an array of potentiometric sensors based on PVC membranes of different selectivity. The diluted standard solutions needed for system learning and response modelling are automatically prepared from more concentrated standards. The electrodes used were characterised with respect to one and two analytes, by means of high-dimensionality calibrations, and the response surface of each was represented; this characterisation enabled an interference study of great practical utility. The combined response was modelled by means of artificial neural networks (ANNs), and thus it was possible to obtain an automated electronic tongue based on SIA. In order to identify the ANN which provided the best model of the electrode responses, some of the network's parameters were optimised and its usefulness in determining NH₄⁺, K⁺ and Na⁺ ions in synthetic samples was then tested. Finally, it was used to determine these ions in commercial fertilisers, the obtained results being compared with reference methods.     

Potentiometric carbon paste sensors for lead(II) based on dithiodibenzoic and mercaptobenzoic acids.

Dithiodibenzoic (DTB) acid and mercaptobenzoic (MB) acid were studied to characterize their abilities as modifier agents for lead(II) sensors. For both sensors, the best results were obtained with modified carbon paste electrodes with 24.1% of ligand. The pH influence on the potentiometric response was studied. The selectivity coefficients for both modified electrodes were tabulated. A potentiometric sensor based on DTB acid exhibited a more sensitive and selective response to lead ions than an MB electrode. The limits of detection for the DTB and MB electrodes were very similar, 5.01 x 10(-8) M and 3.98 x 10(-8) M, respectively, for lead(II) activity. The DTB sensor was applied to lead(II) ion determination in real samples and as an indicator electrode in potentiometric titrations. Natural and commercial humic acids were titrated using the DTB electrode to estimate the stability constant between these organic compounds and the lead(II) ions with successful results.     

Electrochemically Generated Recognition Sites in Self‐doped Polyaniline Modified Electrodes for Voltammetric and Potentiometric Determination of Copper(II) Ion

Chemical recognition elements for copper(II) ion have been generated in electrodes modified with poly(aniline‐co‐metanilic acid), P(An‐co‐MA), membrane and the resulting electrodes were used as selective sensors for voltammetric and potentiometric determination of this ion in an extended pH range. The P(An‐co‐MA) membrane was electrodeposited from aqueous mixed monomer solutions of An and MA, without the presence of a supporting electrolyte. For generating the recognition elements, P(An‐co‐MA) modified electrodes were subjected to several consecutive reduction/oxidation potential steps in copper(II) ion solution. It seems that during these potential steps, the receptor sites of the membrane are adjusted to the size, complexing property and hard/soft nature of copper(II) ion. This electrochemically mediated templating process, provided a selective sensor for determination of copper(II) ion. The results of preconcentration/differential pulse anodic stripping voltammetry, indicated analytical relation between the peak current and concentration of copper(II) from 1.0×10⁻⁹ to 1.0×10⁻⁴ M. The interference effect of various metal ions was explored and it was found that only mercury and silver ions show a considerable interference. The sensor exhibited selective potentiometric response for copper(II) over a wide concentration range (1.0×10⁻⁸ to 1.0×10⁻³ M) with a Nernstian slope of 27.9±0.3 mV per decade of copper(II) ion activity.     

Ionic Liquids Modify the Performance of Carbon Based Potentiometric Sensors

A new type of potentiometric sensor based on a recently constructed carbon ionic liquid electrode (CILE) is described. Two kinds of ionic liquids, i.e., N‐octylpyridinium hexafluorophosphate (OPFP) and 1‐butyl‐3‐methylimidazoluim hexafluorophosphate (BMFP) were tested as binder for construction of the carbon composite electrode. The characteristics of these electrodes as potentiometric sensors were evaluated and compared with those of the traditional carbon paste electrode (CPE). The results indicate that potentiometric sensors constructed with ionic liquid show an increase in performance in terms of Nernstian slope, selectivity, response time, and response stability compared to CPE.     

Multisensor system on the basis of an array of non-specific chemical sensors and artificial neural networks for determination of inorganic pollutants in a model groundwater

The application of a multisensor system to groundwater monitoring is investigated. The sensor system is based on an array of non-specific potentiometric chemical sensors with data processing by artificial neural networks and includes 13 sensors with PVC membranes and 12 solid-state ones. Results of measurements in model solutions containing heavy metals, alkali- and alkali-earth cations and inorganic anions at concentrations typical for groundwater near the city of Braunschweig, Germany, are presented. Both the response of the whole sensor array and the responses of subsystems consisting only of PVC and only of solid-state sensors, respectively, are investigated. It is shown that both subsystems can be used for determination of described ions and that the best results are obtained if the whole array of sensors is used.     

New lead (II) selective membrane potentiometric sensors based on chiral 2,6-bis-pyridinecarboximide derivatives

New membrane sensors with cylindrical configuration for lead (II) ions are described based on the use of three newly synthesized pyridine carboximide derivatives as neutral ionophores in plasticized PVC membranes. The sensors exhibit significantly enhanced response towards lead (II) ions over the concentration range 4×10⁻⁶-1×10⁻² mol l⁻¹ at pH 4.5-7 with a lower detection limit of 0.4-3.7 μg ml⁻¹. The sensors display near-Nernstian slope of 26.0-33.1 mV per decade for Pb(II) ions. Effects of plasticizers, lipophilic salts and various foreign common ions are tested. The sensors show long life span, good selectivity for Pb(II) over a wide variety of other metal ions, long term stability, high reproducibility, and fast response. Validation of the method by measuring the lower detection limit, range, accuracy, precision, repeatability and between-day-variability reveals good performance characteristics of the proposed sensors. The sensors are used for direct determination of lead in stack emissions of lead smelters, assay of lead in rocks and monitoring of potentiometric titration of Pb(II) with EDTA. The results obtained agree fairly well with data obtained by atomic absorption spectrometry.     

Determination of thallium(I) in solutions containing cations interfering in potentiometric ion-pair formation-based titrations

The possibility of the use of simple potentiometric coated-wire sensors in the analysis of mixtures of ions, the determination of which is based on the ion-pairing principle, was studied. Attention was especially paid on the determination of thallium(I) in the presence of alkali metal ions, mercury(II), copper(II) and silver(I). It was found that thallium(I) can selectively be titrated with sodium tetraphenylborate in diluted solutions. Interferences of ions of the alkali metals are practically negligible if their concentrations are lower than 10(-3) mol dm(-3). Interference of Cu(II) is minimized using EDTA as a masking agent, Hg(II) and Ag(I) ions are sufficiently screened by additions of sodium cyanide. In mixtures containing higher concentrations of alkali metals, thallium(I) can be oxidized to thallium(III) and selectively titrated as TlCl(-)(4) with a cationic titrant.     

A sequential injection electronic tongue employing the transient response from potentiometric sensors for anion multidetermination

Intelligent and automatic systems based on arrays of non-specific-response chemical sensors were recently developed in our laboratory. For multidetermination applications, the normal choice is an array of potentiometric sensors to generate the signal, and an artificial neural network (ANN) correctly trained to obtain the calibration model. As a great amount of information is required for the proper modelling, we proposed its automated generation by using the sequential injection analysis (SIA) technique. First signals used were steady-state: the equilibrium signal after a step-change in concentration. We have now adapted our procedures to record the transient response corresponding to a sample step. The novelty in this approach is therefore the use of the dynamic components of the signal in order to better discriminate or differentiate a sample. In the developed electronic tongue systems, detection is carried out by using a sensor array formed by five potentiometric sensors based on PVC membranes. For the developed application we employed two different chloride-selective sensors, two nitrate-selective sensors and one generic response sensor. As the amount of raw data (fivefold recordings corresponding to the five sensors) is excessive for an ANN, some feature extraction step prior to the modelling was needed. In order to attain substantial data reduction and noise filtering, the data obtained were fitted with orthonormal Legendre polynomials. In this case, a third-degree Legendre polynomial was shown to be sufficient to fit the data. The coefficients of these polynomials were the input information fed into the ANN used to model the concentrations of the determined species (Cl⁻, and ). Best results were obtained by using a backpropagation neural network trained with the Bayesian regularisation algorithm; the net had a single hidden layer containing three neurons with the tansig transfer function. The results obtained from the time-dependent response were compared with those obtained from steady-state conditions, showing the former superior performance. Finally, the method was applied for determining anions in synthetic samples and real water samples, where a satisfactory comparison was also achieved.      

Novel Sensors for Batch and Flow Injection Analysis of Histamine Based on Crown Ethers

Six types of histamine potentiometric sensors are developed. They are based on using dibenzo‐30‐crown‐10 (DB30C10) with potassium tetrakis(p‐chlorophenyl)borate lipophilic additive (Type I), dibenzo‐30‐crown‐10 without additive (Type II), dibenzo‐24‐crown‐8 (DB24C8) with the same additive (Type III), dibenzo‐24‐crown‐8 without additive (Type IV), dibenzo‐18‐crown‐6 with the additive (Type V) and dibenzo‐18‐crown‐6 without additive (Type VI) as neutral carriers for histamine. Sensors based on dibenzo‐30‐crown‐10 with (PTp‐C1PB) lipophilic additive (Type I) and dibenzo‐30‐crown‐10 without additive (Type II) show good response. The other sensors Types III–VI show poor response in terms of calibration range and slope.     

Room Temperature Ionic Liquids (RTILs) and Multiwalled Carbon Nanotubes (MWCNTs) as Modifiers for Improvement of Carbon Paste Ion Selective Electrode Response; A Comparison Study with PVC Membrane

Room temperature ionic liquids (RTILs), 1‐n‐butyl‐3‐methylimidazolium tetrafluoroborate, [bmim]BF₄, and multiwalled carbon nanotubes (MWCNTs) were used for improvement of a praseodymium carbon paste ion selective sensor response. [bmim]BF₄ can be a better binder than mineral oils. MWCNTs have a good conductivity which helps the transduction of the signal in carbon paste electrode. The characteristics of these electrodes as potentiometric sensors were evaluated and compared with PVC membrane sensor. The results indicate that potentiometric sensor constructed with ionic liquid shows an increase in performance in terms of Nernstian slope, selectivity, response time, and response stability compared to Pr(III) PVC membrane sensor.     

Lead(II) Potentiometric Sensor Based on 1,4,8,11‐Tetrathiacyclotetradecane Neutral Carrier and Lipophilic Additives

A potentiometric sensor for lead(II) ions based on the use of 1,4,8,11‐tetrathiacyclotetradecane (TTCTD) as a neutral ionophore and potassium tetrakis‐(p‐chlorophenyl)borate as a lipophilic additive in plasticized PVC membranes is developed. The sensor exhibits linear potentiometric response towards lead(II) ions over the concentration range of 1.0×10^?5–1.0×10^?2 mol L^?1 with a Nernstian slope of 29.9 mV decade^?1 and a lower limit of detection of 2.2×10^?6 mol L^?1 Pb(II) ions over the pH range of 3–6.5. Sensor membrane without a lipophilic additive displays poor response. The sensor shows high selectivity for Pb(II) over a wide variety of alkali, alkaline earth and transition metal ions. The sensor shows long life span, high reproducibility, fast response and long term stability. Validation of the method by measuring the lower limit of detection, lower limit of linear range, accuracy, precision and sensitivity reveals good performance characteristics of the proposed sensor. The developed sensor is successfully applied to direct determination of lead(II) in real samples. The sensor is also used as an indicator electrode for the potentiometric titration of Pb(II) with EDTA and potassium chromate. The results obtained agree fairly well with data obtained by AAS.     

Potentiometric determination of potassium cations using a nickel(II) hexacyanoferrate-modified electrode

Electroactive nickel(II) hexacyanoferrate (NiHCF) thin film modified electrodes are effective potentiometric sensors for the determination of potassium ions. The NiHCF films are deposited onto glassy carbon electrodes by repetitive potential cycling in K(3)Fe(CN)(6)/NaNO(3)/Ni(NO(3))(2) solution. The modified electrodes exhibit a linear response to potassium ions in the concentration range 1x10(-3) to 2.0 mol dm(-3), with a near-Nernstian slope (45-49 mV per decade) at 25 degrees C. In the determination of potassium ion in syrups used for treatment of potassium deficiency, the NiHCF-modified electrode gave comparable results to those obtained using flame emission spectrophotometry.     

Principal Component‐Wavelet Neural Network as a Multivariate Calibration Method for Simultaneous Determination of Iron,Nickel, and Cobalt

Abstract

Principal component‐artificial neural network (PC‐ANN) and principal component‐wavelet neural network (PC‐WNN) are applied for simultaneous determination of iron(II), nickel(II), and cobalt(II). A simple and selective spectrophotometric method for simultaneous determination of iron(II), nickel(II), and cobalt(II) based on formation of their complexes with 1‐(2‐pyridylazo)‐2‐naphtol (PAN) in micellar media is described. Although the complexes of Fe(II), Ni(II), and Co(II) with reagent show a spectral overlap, they have been simultaneously determined by PC‐ANN and PC‐WNN. The results obtained by the two methods were compared and it was shown that in PC‐WNN, the convergence speed was faster and the root mean square error of prediction set was also smaller than PC‐ANN. Interference effects of common anions and cations were studied and the proposed method was also applied satisfactorily to the determination of Fe(II), Ni(II) and Co(II) in synthetic samples.     

Voltammetric Electronic Tongue Based on Carbon Paste Electrodes Modified with Biochar for Phenolic Compounds Stripping Detection

Biochar is a charcoal produced from the biomass pyrolysis process that presents a highly porous and functionalized surface. In the present work an array of carbon paste electrodes (CPE) made of different forms of carbon (graphite, carbon nanotubes and activated biochar) was evaluated in the development of an electronic tongue for discrimination and stripping voltammetric determination of catechol (CAT), 4‐ethylcatechol (4‐EC) and 4‐ethylguaiacol (4‐EG) phenolic compounds. Morphological characterization of carbon materials and electrodes surfaces was performed by scanning electron microscopy (SEM) and semi‐quantitative elemental composition by energy dispersive spectroscopy (EDS). Electrochemical Impedance Spectroscopy (EIS) measurements were used for electrochemical characterization of electrodes. Cyclic voltammetry measurements were performed for the phenolic compounds evaluated using different concentrations. Principal component analysis (PCA) was performed to evaluate the qualitative analysis. Quantitative data modeling was done using artificial neural networks (ANN). The proposed sensor array presented analytical potentiality allowing the distinction and determination of CAT, 4‐EC and 4‐EG by using chemometric processing. The method showed sensibility, reproducibility and a good linearity (R²>0.9940) for three compounds evaluated. Spontaneous preconcentration of three compounds was possible using all three sensors, which can allow the application of these as passive samplers for remote determinations of phenolic compounds in wine and food samples.     

Mercury(II) ion-selective electrodes based on heterocyclic systems

Mercury ion-selective electrodes (ISEs) were prepared with a polymeric membrane based on heterocyclic systems: 2-methylsulfanyl-4-(4-nitro-phenyl)-l-p-tolyl-1H-imidazole (I) and 2,4-diphenyl-l-p-tolyl-1H-imidazole (II) as the ionophores. Several ISEs were conditioned and tested for the selection of common ions. The electrodes based on these ionophores showed a good potentiometric response for Hg2+ ions over a wide concentration range of 5.0 x 10(5-) - 1.0 x 10(-1)M with near-Nernstian slopes. Stable potentiometric signals were obtained within a short time period of 20 s. The detection limits, the working pH range of the electrodes were 1.0 x 10(-5) M and 1.6-4.4 respectively. The electrodes showed better selectivity for Hg2+ ions over many of the alkali, alkaline-earth and heavy metal ions. Also sharp end points were obtained when these sensors were used as indicator electrodes for the potentiometric titration of Hg2+ ions with iodide ions.     

Silver and lead all-plastic sensors—polyaniline vs. poly(3,4-ethyledioxythiophene) solid contact

Silver and lead selective all-plastic ion-selective electrodes were obtained using poly(vinyl chloride)-based membranes and either poly(3,4-ethylenedioxythiophene) or polyaniline dispersion cast on an insulating plastic support as transducer and electrical lead. The effect of interactions of applied conducting polymer with analyte ions on potentiometric responses was evaluated and correlated with changes in elemental composition and element distribution within the ion-selective membrane and the conducting polymer transducer revealed in course of laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) experiments. In the case of silver selective electrodes, potentiometric responses obtained are much dependent on the oxidation state of the polymer placed beneath the ion-selective membrane. For semi-oxidized polymer (poly(3,4-ethylenedioxythiophene)-based electrodes, linear responses with detection limit equal to 10^−5.4 M were obtained. For a more oxidized polyaniline (of higher conductivity), although the electrodes were pretreated exactly in the same way and tested in parallel, super Nernstian potential slope was recorded within the AgNO₃ activities range form 10⁻⁶ to 10⁻⁷ M. These responses were consistent with results of LA-ICP-MS, revealing profoundly higher silver signals intensities for poly(3,4-ethylenedioxythiophene) underlying silver selective membrane. It seems highly probable that silver is accumulated in this polymer layer as Ag⁰ due to spontaneous redox reaction leading to oxidation of the polymer; however, this process requires also the presence of silver ions at the interface. In fact, when reduced (deprotonated) polyaniline was used as transducer, the potentiometric responses of the sensor were, within the range of experimental error, the same as obtained for poly(3,4-ethylenedioxythiophene)-based sensor. On the other hand, for lead(II) selective sensors, the difference in responses of electrodes prepared using poly(3,4-ethylenedioxythiophene) or polyaniline was less pronounced, which is in accordance with the elemental composition of these sensors.