Sequential injection system with higher dimensional electrochemical sensor signals Part 1. Voltammetric e-tongue for the determination of oxidizable compounds

A sequential injection analysis (SIA) system was developed with the aim of obtaining an automatic and versatile way to prepare standards needed in the study of systems with higher dimensional sensor signals. To illustrate this, different analytical techniques were used in determinations of several analytes. Automated potentiometric calibrations of different potentiometric sensors, with and without interference, were carried out. Useful determinations of selectivity coefficients with two degrees of freedom were obtained. Simultaneous voltammetric determinations have also been done. Firstly, simultaneous determinations of lead and cadmium, using epoxy-graphite composite as the working electrode, have enabled a separate calibration for each metal to be obtained. Next, a voltammetric electronic tongue was designed and applied to the determination of oxidizable species. The use of artificial neural networks has solved the overlapped signal of ascorbic acid, 4-aminophenol and 4-acetamidophenol (paracetamol). A set of 63 data points was prepared automatically and has facilitated the training of an electronic tongue for these three analytes. Accurate predictions of test solutions, in the range of 12–410 μM for ascorbic acid, 17–530 μM for 4-aminophenol and 10–420 μM for paracetamol, have been achieved with RMSEs lower than 0.10 μM.     

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.      

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.     

Simultaneous Titration of Ternary Mixtures of Pb(II), Cd(II) and Cu(II) with Potentiometric Electronic Tongue Detection

An automatic titration method is reported to resolve ternary mixtures of transition metals (Pb²⁺, Cd²⁺ and Cu²⁺) employing electronic tongue detection and a reduced number of pre‐defined additions of EDTA titrant. Sensors used were PVC membrane selective electrodes with generic response to heavy‐metals, plus an artificial neural network response model. Detection limits obtained were ca. 1 mg L^?1 for the three target ions and reproducibilities 3.0 % for Pb²⁺, 4.1 % for Cd²⁺ and 5.2 % for Cu²⁺. The system was applied to contaminated soil samples and high accuracy was obtained for the determination of Pb²⁺. In the determination Cd²⁺ and Cu²⁺, sample matrix showed a significant effect.     

Automated SIA System Using an Array of Potentiometric Sensors for Determining Alkaline‐Earth Ions in Water

This work deals with the simultaneous determination of Mg²⁺, Ca²⁺, and Ba²⁺ in water using a PVC‐membrane potentiometric sensor array and multivariate calibration, in what is known as electronic tongue. The subsequent processing of the data was based on the use of a multilayer artificial neural network (ANN). The information needed for training or generation of the model was obtained with the aid of an automated analytical system based on the Sequential Injection Analysis (SIA) technique. The modeling ability was verified with an external set of standards, and next the determinations were performed in real samples of mineral waters, where close results for Mg²⁺ and Ca²⁺ were obtained to those obtained with reference methods. The determination of Ba²⁺ can be considered as semi‐quantitative for synthetic samples – due to the absence of Ba²⁺ in mineral waters, its concentration in real samples was not measured.     

Sequential injection/electrochemical immunoassay for quantifying the pesticide metabolite 3,5,6-trichloro-2-pyridinol

An automated and sensitive sequential injection electrochemical immunoassay was developed to monitor a potential insecticide biomarker, 3,5,6-trichloro-2-pyridinol. The current method involved a sequential injection analysis (SIA) system equipped with a thin-layer electrochemical flow cell and permanent magnet, which was used to fix 3,5,6-trichloro-2-pyridinol (TCP) antibody coated magnetic beads (TCP-Ab-MBs) in the reaction zone. After competitive immunoreactions among TCP-Ab-MBs, TCP analyte, and horseradish peroxidase (HRP) labeled TCP, a 3,3′,5,5′-tetramethylbenzidine dihydrochloride and hydrogen peroxide (TMB-H₂O₂) substrate solution was injected to produce an electroactive enzymatic product. The activity of HRP tracers was monitored by a square wave voltammetric scanning electroactive enzymatic product in the thin-layer flow cell. The voltammetric characteristics of the substrate and the enzymatic product were investigated under batch conditions, and the parameters of the immunoassay were optimized in the SIA system. Under the optimal conditions, the system was used to measure as low as 6 ng L⁻¹(ppt) TCP, which is around 50-fold lower than the value indicated by the manufacturer of the TCP RaPID Assay^® kit (0.25 μg/L, colorimetric detection). The performance of the developed immunoassay system was successfully evaluated on tap water and river water samples spiked with TCP. This technique could be readily used for detecting other environmental contaminants by developing specific antibodies against contaminants and is expected to open new opportunities for environmental and biological monitoring.     

Sequential injection system for on-line analysis of total nitrogen with UV-mineralization

An automatic method for the determination of total nitrogen in wastewater by sequential injection analysis and mineralization with UV radiation has been developed. The method is based on the mineralization of the samples with sodium persulphate in basic medium under UV radiation. Small volumes of sample and reagents are firstly aspirated into a single channel and then propelled by flow reversal to the UV reactor and then to the detector. The organic and inorganic nitrogen compounds are oxidized to nitrate that is then measured at 226 nm. The sequential injection procedure has been optimized and the factors affecting the efficiency of the oxidation have been studied with a number of test substances with different chemical structures and properties. Solutions in the concentration range 1-56 g l⁻¹ of nitrogen can be analyzed with the described procedure. The sample rate is of 30-40 samples h⁻¹. The LOD is 0.6 mg l⁻¹ N and the reproducibility is 1.8% (28 mg l⁻¹ N). Organic carbon in the form of glucose was added to a number of test solutions to study the potential interference of organic matter.The method was compared with the Kjeldahl digestion method by analyzing 15 wastewater samples with both methods. The nitrate and nitrite content of the non-oxidized samples were subtracted from the corresponding nitrogen content determined after photo-oxidation and the value compared with the Kjeldahl nitrogen content.     

EIS multianalyte sensing with an automated SIA system—An electronic tongue employing the impedimetric signal

In this work, the simultaneous quantification of three alkaline ions (potassium, sodium and ammonium) from a single impedance spectrum is presented. For this purpose, a generic ionophore - dibenzo-18-crown-6 - was used as a recognition element, entrapped into a polymeric matrix of polypyrrole generated by electropolymerization. Electrochemical impedance spectroscopy (EIS) and artificial neural networks (ANNs) were employed to obtain and process the data, respectively. In fact, EIS detected the ions exchanged between the medium and the sensing layer whereas ANNs, after an appropriated training process, could turn the impedance spectrum into concentrations values. A sequential injection analysis (SIA) system was employed for operation and to automatically generate the information required for the training of the ANN. Best results were obtained by using a backpropagation neural network made up by two hidden layers: the first one contained three neurons with the radbas transfer function and the second one ten neurons with the tansig transfer function. Three commercial fertilizers were tested employing the proposed methodology on account of the high complexity of their matrix. The experimental results were compared with reference methods.     

Sequential injection-ELISA based system for online determination of hyaluronan

Sequential injection-bead-based immunoassay system has been developed. The main purpose is to make immunoassay process more automated by manipulating the precise delivery of micro-volumes of reagents and the precise timing of incubation and washing steps with a computer program that controls the bi-directional syringe pump. The manifold was designed with the aims of reducing back pressure from beads that act as solid surfaces for immobilization of the target substance, reducing dispersion and dilution of the reagent during incubation, and maximizing signal while minimizing incubation time. This was done by introducing air segment to separate the reagent zone from the carrier stream and by using a suitable sensitive detector which, in this case, was an amperometer. In this study, hyaluronan (HA) was used as a target analyte because of its clinical significance as a potential biomarker for liver, bone and cancer diseases. Amount of hyaluronan was determined using competitive enzyme linked immuno sorbent assay (ELISA) based technique where immobilized HA and HA in solution compete to bind with a fixed amount of biotinylated HA-binding proteins (b-HABPs). Upon separation of the two phases, anti-biotin conjugated with enzyme and a suitable substrate were introduced to follow the binding reaction of the immobilized HA and b-HABPs whose degree of binding is indirectly proportional to the amount of HA in solution. A calibration curve was constructed from a series of concentrations of HA standards. Lowest detectable concentration was found to be 1 ng/mL with the dynamic working range of 1-5000 ng/mL and R.S.D. of intra-assay (n = 7) and inter-assay (n = 3) of various HA concentrations were 4-10% and 9-12%, respectively. Used beads could be reused by washing with 2 M guanidine. Total analysis time for this automatic assay was about 30 min as compared to the 5-8 h used in conventional batch well ELISA. The system could be applied to assay HA in human serum.     

The recognition of beer with flow-through sensor array based on miniaturized solid-state electrodes

Flow-through electronic tongue based on miniaturized solid-state potentiometric sensors has been developed. A simple technique, i.e. membrane solution casting on the surface of the planar Au transducers was applied for the preparation of classical ion-selective and partially selective microelectrodes, introduced in the flow-through sensor array. The performance of the designed electronic tongue was tested in the qualitative analysis of various brands of beer. Samples of the same brand of beer but with different manufacture dates, originating from different manufacture lots, have been applied in the studies. The combination of PLS and ANN techniques allowed the discrimination between different brands of beer with 83% of correct classifications.     

Sequential injection with lab-at-valve (LAV) approach for potentiometric determination of chloride

Sequential injection with “Lab-at-Valve (LAV)” approach is demonstrated for potentiometric determination of chloride. The LAV flow-through electrode system consists of two Ag/AgCl electrodes: one as a reference electrode, silver chloride activated surface-silver wire soaked in a constant-concentration chloride ion solution in a small tube covered with a polymer-membrane, another as a working electrode (a similar silver chloride activated surface-silver wire) placed in a flow channel. The electrode system is attached at one port of a 10 port multiposition valve. A modified autoburette was used as a propelling device. Using SI operation via a program written in-house, based on LabVIEW^®, a standard/sample is inserted, via the selection valve, in potassium nitrate as an electrolyte and water is used as a carrier. The zones are transported from the holding coil to the flow cell to monitor the difference in potential due to concentration cell behavior. The potential difference is then recorded as a peak. Peak height is proportional to logarithm of chloride concentration. The SI-LAV for chloride determination is very simple, fast, precise, accurate, automatic and economical. Applications to mineral drinking water and surface water have been made. The results agree with those of IC and titrimetric methods.     

Sequential injection analysis with second-order treatment for the determination of dyes in the exhaustion process of tanning effluents

A sequential injection (SI)-DAD spectrophotometric method to control the exhaustion of dyes in a mixture of three dyes from a tanning industry process has been developed. It is based on an interdiffusion process of the sample and reagents which leads to a gradual fall in pH through the channel to the detector recording a data matrix. The aim of this paper is to develop a second-order calibration model that is unaffected by interferents by applying multivariate curve resolution with alternating least squares (MCR-ALS). We obtained a linear calibration in the 5-30 mg l⁻¹ range with a correlation coefficient of 0.999 for each dye with detection limits of 2.6, 3.9 and 2.1 mg l⁻¹ for Acid Red, Acid Brown and Acid Orange, respectively. The simultaneous determination of the three dyes from tanning samples showed a satisfactory precision for the three analytes. The method has been validated comparing the concentration of some spiked samples with the expected concentration using a t-paired test. When we used this method to study the exhaustion of dyes, we found that there were several stages in this process. These data may be the key to optimising the exhaustion process.     

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.     

Hybrid E‐Tongue for the Evaluation of Sweetness and Bitterness of Soft Drinks Fortified with Epigallocatechin Gallate

A home‐made hybrid electronic tongue was set up, validated and applied to discriminate soft drinks fortified with plant extracts of green tea. The e‐tongue consists of a flow injection system equipped with two electrochemical and one optical sensors. Different formulations of soft drinks composed of glucose and epigallocatechin gallate were then discriminated by principal component analysis. Furthermore, two partial least squares regression models were developed to estimate the “sweetness” (r² of 0.992) and “bitterness” (r² of 0.993) of the model solutions and commercial soft drinks, before and after their fortification with epigallocatechin gallate.     

Reversed flow injection and sandwich sequential injection methods for the spectrophotometric determination of copper(II) with cuprizone

Two new flow methods, flow injection analysis (FIA) and sequential injection analysis (SIA), for the spectrophotometric determination of Cu(II) in water at trace levels have been developed and optimised. Both methods are based on the reaction with oxalic acid bis(cyclohexylidene hydrazide) (cuprizone) in alkaline media. The two procedures have been developed for the final aim to compare their performances and to offer new rapid heavy metals analysis tools, avoiding the use of extraction steps. A detailed study of the physico-chemical parameters affecting the systems performances has been carried out. The reversed FIA and sandwich SIA approaches offered the best sensitivity. In both cases, an extremely good linearity has been obtained within the range 0.06-4 μg ml⁻¹ (correlation coefficient r=0.9999), whereas the observed detection limits were 0.013 and 0.004 μg ml⁻¹, for FIA and SIA, respectively. Furthermore, due to the great similarity of the diffusion zones in the reaction slugs, our approach offers the opportunity to compare the two methods in analogous conditions. This SIA method, besides keeping its typical reagent saving features, offered analytical performances equivalent to those of FIA. To obtain these results, an original “stop-flow like” method was successfully employed in the SIA approach. Both methods were validated by analysis of real water samples, after copper addition, and certified reference samples of fortified and waste waters.     

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.     

Sequential injection method for the direct spectrophotometric determination of bismuth in pharmaceutical products

A spectrophotometric method is reported for the determination of bismuth in pharmaceutical products using sequential injection analysis. Methylthymol blue (MTB) was used as a color forming reagent and the absorbance of the Bi(III)-MTB complex was monitored at 548 nm. The various chemical and physical variables that affected the reaction were studied. A linear calibration graph was obtained in the range 0.0-75.0 mg l⁻¹ Bi(III) at a sampling frequency of 72 h⁻¹. The reagent consumption was considerably reduced compared to conventional flow injection systems, as only 150 μl of MTB were consumed per run. The precision was very satisfactory (s_r=0.5%, at 50.0 mg l⁻¹ Bi(III), n=12) and the limit of detection, c_L, was 0.250 mg l⁻¹. The developed method was applied successfully to the analysis of various pharmaceutical products containing Bi(III). The relative errors e_r, were <1.5% in all cases and were evaluated by comparison of the obtained results with those found using atomic absorption spectrometry as the reference method.     

Automatic sequential injection analysis electronic tongue with integrated reference electrode for the determination of ascorbic acid, uric acid and paracetamol

A new approach towards a voltammetric electronic tongue has been developed. Automation of the system was achieved by the use of a sequential injection analysis (SIA) system. Design and construction of a small detection device containing 3 working electrodes was carried out. Platinum, gold and epoxy-graphite discs were used for this purpose. An Ag/AgCl reference electrode was integrated into the measuring cell in order to minimise electrical noise. Three oxidisable compounds of clinical interest i.e., ascorbic acid, uric acid and paracetamol, could be quantified by the system. Employing the voltammograms as departure information, artificial neural networks (ANN) have been used as chemometric tool for the modelling of the system.     

Simple sequential injection analysis system for rapid determination of microalbuminuria

A simple, specific and sensitive sequential injection analysis (SIA) system based on non-immunoassay fluorescent detection has been developed for the determination of urinary albumin. The specific binding of the dye Albumin Blue 580 (AB 580) to albumin in urine generated high emission fluorescent signals. The excitation and emission wavelengths were set at 590 and 610 nm, respectively. The analytical range was obtained from 1 to 100 mg L⁻¹, with a detection limit of 0.3 mg L⁻¹ (S/N = 3). The SIA system gave high precision with relative standard deviations (R.S.D.s) of 0.9% and 1.4% when evaluated with 15 and 100 mg L⁻¹ albumin (n = 15), respectively. The method exhibited good reproducibility, as assessed by performing four analytical curves on different days, and intra-run CVs (2.3-3.3%) and inter-run CVs (3.8%) were obtained. Rapid operation was achieved with a sample throughput of 37 h⁻¹. This method was successfully applied to the determination of urinary albumin, and the method was highly correlated with the immunoturbidimetric method (r² = 0.965; n = 72).     

Sequential injection system for simultaneous determination of chloride and iodide by a Gran’s plot method

This paper describes an automated set-up based on the sequential injection analysis (SIA) concept with potentiometric detection for the determination of chloride and iodide at low concentrations. The assessment of both ion concentrations is accomplished by titration with silver ions using the Gran’s plot approach. The proposed procedure enables chloride and iodide to be determined simultaneously in the range 6.0×10⁻⁶ to 1.0×10⁻⁴ mol l⁻¹ if a minimum silver concentration in the volumetric solution is chosen (5×10⁻⁵ mol l⁻¹). Conventional titrations based on the first derivative evaluation of the equivalence points applied to the same solutions fail, especially for chloride determinations. Although, a comparison of results obtained for higher analyte concentrations shows that they have similar accuracy and precision.