Modelling Dynamics of Amperometric Biosensors in Batch and Flow Injection Analysis

A mathematical model of amperometric biosensors has been developed. The model is based on non-stationary diffusion equations containing a non-linear term related to Michaelis–Menten kinetic of the enzymatic reaction. Using digital simulation, the influence of the substrate concentration as well as maximal enzymatic rate on the biosensor response was investigated. The digital simulation was carried out using the finite difference technique. The model describes the biosensor action in batch and flow injection regimes.     

Multivariate data analysis of dynamic amperometric biosensor responses from binary analyte mixtures-application of sensitivity correction algorithms

In this paper, it is demonstrated that a single-receptor biosensor can be used to quantitatively determine each analyte in binary mixtures using multivariate data analysis tools based on the dynamic responses received from flow injection peaks. Mixtures with different concentrations of two phenolic compounds, catechol and 4-chlorophenol, were measured with a graphite electrode modified with tyrosinase enzyme at an applied potential of −50 mV versus Ag/AgCl. A correction algorithm based on measurements of references in-between samples was applied to compensate for biosensor ageing as well as differences caused by deviations between biosensor preparations. After correction, the relative prediction errors with partial least squares regression (PLS-R) for catechol and 4-chlorophenol were 7.4 and 5.5%, respectively, using an analysis sequence measured on one biosensor. Additional validation mixtures of the two phenols were measured with a new biosensor, prepared with the same procedure but with a different batch of tyrosinase enzyme. Using the mixture responses for the first sensor as a calibration set in PLS-R, the relative prediction errors of the validation mixtures, after applying correction procedures, were 7.0% for catechol and 16.0% for 4-chlorophenol. These preliminary results indicate that by applying correction algorithms it could be possible to use less stable biosensors in continuous on-line measurements together with multivariate data analysis without time-consuming calibration procedures.     

Mechanisms controlling the sensitivity of amperometric biosensors in flow injection analysis systems

This paper numerically investigates the sensitivity of an amperometric biosensor acting in the flow injection mode when the biosensor contacts an analyte for a short time. The analytical system is modelled by non-stationary reaction-diffusion equations containing a non-linear term related to the Michaelis-Menten kinetics of an enzymatic reaction. The mathematical model involves three regions: the enzyme layer where enzymatic reaction as well as the mass transport by diffusion takes place, a diffusion limiting region where only the diffusion takes place, and a convective region. The biosensor operation is analysed with a special emphasis to the conditions at which the biosensor sensitivity can be increased and the calibration curve can be prolonged by changing the injection duration, the permeability of the external diffusion layer, the thickness of the enzyme layer and the catalytic activity of the enzyme. The apparent Michaelis constant is used as a main characteristic of the sensitivity and the calibration curve of the biosensor. The numerical simulation was carried out using the finite difference technique.     

An integrated bienzyme glucose oxidase-fructose dehydrogenase-tetrathiafulvalene-3-mercaptopropionic acid-gold electrode for the simultaneous determination of glucose and fructose

A bienzyme biosensor for the simultaneous determination of glucose and fructose was developed by coimmobilising glucose oxidase (GOD), fructose dehydrogenase (FDH), and the mediator, tetrathiafulvalene (TTF), by cross-linking with glutaraldehyde atop a 3-mercaptopropionic acid (MPA) self-assembled monolayer (SAM) on a gold disk electrode (AuE). The performance of this bienzyme electrode under batch and flow injection (FI) conditions, as well as an amperometric detection in high-performance liquid chromatography (HPLC), are reported. The order of enzyme immobilisation atop the MPA-SAM affected the biosensor amperometric response in terms of sensitivity, with the immobilisation order GOD, FDH, TTF being selected. Similar analytical characteristics to those obtained with single GOD or FDH SAM-based biosensors for glucose and fructose were achieved with the bienzyme electrode, indicating that no noticeable changes in the biosensor responses to the analytes occurred as a consequence of the coimmobilisation of both enzymes on the same MPA-AuE. The suitability of the bienzyme biosensor for the analysis of real samples under flow injection conditions was tested by determining glucose in two certified serum samples. The simultaneous determination of glucose and fructose in the same sample cannot be performed without a separation step because at the detection potential used (+0.10 V), both sugars show amperometric response. Consequently, HPLC with amperometric detection at the TTF-FDH-GOD-MPA-AuE was accomplished. Glucose and fructose were simultaneously determined in honey, cola softdrink, and commercial apple juice, and the results were compared with those obtained by using other reference methods.     

Modified microelectrodes and multivariate calibration for flow injection amperometric simultaneous determination of ascorbic acid, dopamine, epinephrine and dipyrone

Flow injection amperometric quantification of ascorbic acid (AA), dopamine (DA), epinephrine (EP) and dipyrone (DI) in mixtures (in the microgram g-1 range) was successfully performed by using an array of microelectrodes with units modified by the electrodeposition of different noble metals, together with multivariate calibration analysis. The four groups of microelectrodes utilized included a pure gold electrode and electrodes modified by electrodeposition of platinum, palladium or a mixture of platinum + palladium. The array of microelectrodes was inserted in a flow cell and the amperometric data acquisition was performed with a four-channel potentiostat. The analysis of the resulting signals was carried out by a multivariate calibration method, using a group of 16 standard mixtures selected by a two-level factorial design. The analysis of synthetic samples and pharmaceutical compounds containing AA and DI led to very similar values to those obtained by the classical iodimetric analysis. The average absolute errors (in microgram g-1) calculated for each analyte were 0.3, 0.2, 0.4 and 0.4 for AA, DA, EP and DI, respectively.     

Computational modelling of amperometric biosensors in the case of substrate and product inhibition

In this paper the response of an amperometric biosensor at mixed enzyme kinetics and diffusion limitations is modelled in the case of the substrate and the product inhibition. The model is based on non-stationary reaction–diffusion equations containing a non-linear term related to non-Michaelis–Menten kinetics of an enzymatic reaction. A numerical simulation was carried out using a finite difference technique. The complex enzyme kinetics produced different calibration curves for the response at the transition and the steady-state. The biosensor operation is analysed with a special emphasis to the conditions at which the biosensor response change shows a maximal value. The dependence of the biosensor sensitivity on the biosensor configuration is also investigated. Results of the simulation are compared with known analytical results and with previously conducted researches on the biosensors.     

Minimization of Interferences in Flow Injection Amperometric Glucose Biosensor Based on Oxidation of Enzymatically‐produced H2O2

One of the major problems in amperometric biosensors based on detection of H₂O₂ produced by enzymatic reaction between oxidase enzymes and substrate is the interference of redox active compounds such as ascorbic acid (AA), dopamine (DA) and uric acid (UA). To minimize these interferences, sodium bismuthate was used for the first time as an insoluble pre‐oxidant in the flow injection (FI) amperometric glucose biosensor at a Glucose oxidase (GOx) immobilized Pt/Pd bimetallic modified pre‐anodized pencil graphite electrode (p.PGE). In this context, these interfering compounds were injected into a flow injection analysis (FIA) system using an injector which was filled with NaBiO₃. Thus, these interferents were converted into their redox inactive oxidized forms before reaching the electrode in the flow cell. While glucose was not influenced by the pre‐oxidant in the injector, the huge oxidation peak currents of the interferents decreased significantly in the biosensor. FI amperometric current time curves showed that the AA, DA and UA were minimized by 96 %, 86 %, and 98 % respectively, in the presence of an equivalent concentration of interferences in a 1.0 mM glucose solution. The proposed FI amperometric glucose biosensor exhibits a wide linear range (0.01–10 mM, R²=0.9994) with a detection limit of 2.4×10^?3 mM. Glucose levels in the artificial serum and two real samples were successfully determined using the fabricated FI amperometric biosensor.     

A neural network approach based on gold‐nanoparticle enzyme biosensor

Gold nanoparticles have demonstrated to be a very useful material for the construction of stable and sensitive glucose oxidase (GOx) amperometric biosensors. However, as for other enzyme electrodes, the lack of specificity for glucose limits their practical applications. Coupling biosensor responses with chemometric tools can be used to solve complex analytical signals from mixtures of species with similar properties. In this work, an amperometric biosensor based on a colloidal gold—cysteamine—gold disk electrode with the enzyme GOx and a redox mediator, tetrathiafulvalene (TTF), co‐immobilised atop the modified electrode, was used for the simultaneous determination of glucose and its common interferences, ascorbic acid and uric acid, in mixtures. Analytical data obtained from cyclic voltammograms generated with the biosensor were processed using an artificial neural network (ANN), and the separate quantification of the analytes over a range of 0.1–1 mM each was performed without any pretreatment. In all cases, the correlation coefficients obtained were higher than 0.99 and the mean prediction error was less than 1.7%. Copyright © 2007 John Wiley & Sons, Ltd.     

Simultaneous determination of three fluoroquinolones by linear sweep stripping voltammetry with the aid of chemometrics

A linear sweep stripping voltammetric (LSSV) method has been researched and developed for simultaneous quantitative determination of mixtures of three antibiotic drugs, ofloxacin, norfloxacin and ciprofloxacin. It relies on reductive reaction of the antibiotics at a mercury electrode in a Britton-Robinson buffer (pH 3.78). The voltammograms of these three compounds overlap strongly, and show non-linear character. Thus, it is difficult to analyse the compounds individually in their mixtures. In this work, chemometrics methods such as classical least squares (CLS), principal component regression (PCR), partial least squares (PLS) and radial basis function-artificial neural networks (RBF-ANN) were applied for the simultaneous determination of these compounds. The prediction performance of the calibration models constructed on the basis of these methods was compared. It was shown that satisfactory quantitative results were obtained with the use of the RBF-ANN calibration model relative prediction error (RPE_T) of 8.1% and an average recovery of 101%. This method is able to accommodate non-linear data quite well. The proposed analytical method based on LSSV was applied for the analysis of ofloxacin, norfloxacin and ciprofloxacin antibiotics in bird feedstuffs and their spiked samples, as well as in eye drops with satisfactory results.     

Catechol determination in compost bioremediation using a laccase sensor and artificial neural networks

An electrochemical biosensor based on the immobilization of laccase on magnetic core-shell (Fe₃O₄–SiO₂) nanoparticles was combined with artificial neural networks (ANNs) for the determination of catechol concentration in compost bioremediation of municipal solid waste. The immobilization matrix provided a good microenvironment for retaining laccase bioactivity, and the combination with ANNs offered a good chemometric tool for data analysis in respect to the dynamic, nonlinear, and uncertain characteristics of the complex composting system. Catechol concentrations in compost samples were determined by using both the laccase sensor and HPLC for calibration. The detection range varied from 7.5 × 10^–7 to 4.4 × 10^–4 M, and the amperometric response current reached 95% of the steady-state current within about 70 s. The performance of the ANN model was compared with the linear regression model in respect to simulation accuracy, adaptability to uncertainty, etc. All the results showed that the combination of amperometric enzyme sensor and artificial neural networks was a rapid, sensitive, and robust method in the quantitative study of the composting system. Figure Structure of the magnetic carbon paste electrode used in the electrochemical biosensor     

Modelling synergistic action of laccase-based biosensor utilizing simultaneous substrates conversion

The response of a laccase-based amperometric biosensor that acts in a synergistic manner was modelled digitally. A mathematical model of the biosensor is based on a system of non-linear reaction diffusion equations. The modelling biosensor comprises three compartments, an enzyme layer, a dialysis membrane and an outer diffusion layer. By changing input parameters the biosensor action was analysed with a special emphasis to the influence of the species concentrations on the synergy of the simultaneous substrates conversion. The digital simulation was carried out using the finite difference technique.     

Response Behavior of Amperometric Glucose Biosensors Based on Different Carbon Substrate Transducers Coated with Enzyme‐Active Layer: A Comparative Study

Carbon electrodes (glassy carbon, GC, screen‐printed carbon, SPC, and carbon fiber, CF) were used as substrate transducers to prepare glucose biosensors of different sizes and geometries, based on iron‐ruthenium hexacyanoferrate as H₂O₂ reduction mediator and glucose oxidase immobilized in a poly(1,2‐phenylenediamine) membrane. Their response behavior under hydrodynamic amperometric conditions at an operating potential of ?0.02 V vs. Ag/AgCl was studied and compared. While the GC and SPC based conventional size biosensors showed enzymatic catalysis controlled current response with nonlinear concentration dependence, the CF based micro‐biosensor exhibited, due to diffusion‐controlled current response, extended linear range calibration curves with relatively lower sensitivity and longer response times. Several preparation parameters responsible for the improvement of biosensor performance were also investigated.     

Flow electrochemical biosensors based on enzymatic porous reactor and tubular detector of silver solid amalgam

A flow amperometric enzymatic biosensor for the determination of glucose was constructed. The biosensor consists of a flow reactor based on porous silver solid amalgam (AgSA) and a flow tubular detector based on compact AgSA. The preparation of the sensor and the determination of glucose occurred in three steps. First, a self-assembled monolayer of 11-mercaptoundecanoic acid (MUA) was formed at the porous surface of the reactor. Second, enzyme glucose oxidase (GOx) was covalently immobilized at MUA-layer using N-ethyl-N′-(3-dimethylaminopropyl) carboimide and N-hydroxysuccinimide chemistry. Finally, a decrease of oxygen concentration (directly proportional to the concentration of glucose) during enzymatic reaction was amperometrically measured on the tubular detector under flow injection conditions. The following parameters of glucose determination were optimized with respect to amperometric response: composition of the mobile phase, its concentration, the potential of detection and the flow rate. The calibration curve of glucose was linear in the concentration range of 0.02–0.80 mmol L⁻¹ with detection limit of 0.01 mmol L⁻¹. The content of glucose in the sample of honey was determined as 35.5 ± 1.0 mass % (number of the repeated measurements n = 7; standard deviation SD = 1.2%; relative standard deviation RSD = 3.2%) which corresponds well with the declared values. The tested biosensor proved good long-term stability (77% of the current response of glucose was retained after 35 days).     

Simultaneous determination of aniline and cyclohexylamine by principal component artificial neural networks.

A specterophotometric method for simultaneous determination of aniline and cyclohexylamine using principal component artificial neural networks is proposed. This method is based on the reactions involving aniline and/or cyclohexylamine, with bis(acetylacetoneethylendiamine)tributylphosphine cobalt(III) perchlorate as a complexing reagent. A nonionic surfactant, Triton X-100, was used for dissolving the complexes and intensifying the signals. The absorption data were based on the spectra registered in the range of 350 - 550 nm. An artificial neural network consisting of three layers of nodes was trained by applying a back-propagation learning rule. Sigmoid transfer functions were used in the hidden and output layers to facilitate nonlinear calibration. The predictive ability of artificial neural networks was examined for the determination of aniline and cyclohexylamine in synthetic mixtures.     

The Effect of Diffusion Limitations on the Response of Amperometric Biosensors with Substrate Cyclic Conversion

A mathematical model of amperometric biosensors in which chemical amplification by cyclic substrate conversion takes place in a single enzyme membrane has been developed. The model involves three regions: the enzyme layer where enzyme reaction as well as mass transport by diffusion takes place, a diffusion limiting region where only the diffusion takes place, and a convective region where the analyte concentration is maintained constant. Using computer simulation the influence of the thicknesses of the enzyme layer and the diffusion region on the biosensor response was investigated. This paper deals with conditions when the mass transport in the exterior region may be neglected to simulate the biosensor response in a well-stirred solution. The digital simulation was carried out using the finite difference technique.     

Determination of Phenolic Compounds Based on Co‐Immobilization of Methylene Blue and HRP on Multi‐Wall Carbon Nanotubes

This work evaluated an amperometric biosensor based on multi‐wall carbon nanotubes (MWCNT), chemically modified with methylene blue (Met) and horseradish peroxidase (HRP), for detection of phenolic compounds. The dependences of the biosensor response due to the enzyme immobilization procedure, HRP amounts, pH and working potential were investigated. The amperometric response for catechol using the proposed biosensor showed a very wide linear response range (1 to 150 μmol L^?1), good sensitivity (50 nA cm^?2 μmol^?1 L), excellent operational stability (after 300 determinations the response remained at 97%) and very good storage stability (lifetime>3 months). Based on all these characteristics, it is possible to affirm that the material is promising for phenol detection due to its good electrochemical response and enzyme stabilization. The biosensor response for various phenolic compounds was investigated.     

Electroimmobilization of MAO into a Polypyrrole Film and Its Utilization for Amperometric Flow Detection of Antidepressant Drugs

The preparation of a biosensor based on the enzymatic immobilization in polypyrrole polymer for the detection of antidepressant drugs is described. The enzyme monoamine oxidase (MAO) was immobilized by electropolymerization of pyrrole around a platinum electrode, at a constant potential of +0.75 V (vs. Ag/AgCl) in such a way to obtain a membrane thickness, which was constant and equal to 100 mC/cm². The biosensor was obtained from a 0.1 M KCl saline solution containing pyrrole at a concentration equal to 0.4 M and 2.5 mU/mL of MAO. The biosensor was adapted to a continuous flow injection analysis system (FIA) with the amperometric detection of hydrogen peroxide produced by enzymatic reaction carried out at a potential of +0.7 V (vs. Ag/AgCl), pH 7.4 and temperature of 37 °C. In optimized flow conditions, the biosensor presented an analytical response for fluoxetine in the interval between 0.67 and 4.33 mM, with a detection limit of 0.10 mM. The analytical use of the biosensor developed was evaluated through analysis of commercial pharmaceutical products containing fluoxetine, available on the Portuguese market. The amperometric flow results obtained do not differ significantly from the values resulting from analysis of the same products by the method proposed by the US Pharmacopeia, with sampling rates of 20–25 samples/hour.     

Silicone-grease-based immobilisation method for the preparation of enzyme electrodes

An approach to the construction of amperometric biosensors based on the incorporation of an enzyme in silicone grease and using the grease to fill micropores on a graphite surface is described. The enzyme-grease electrode concept, illustrated with the enzyme tyrosinase, offers a very simple, rapid and inexpensive approach to the fabrication of enzyme electrodes. The tyrosinase electrode responds very rapidly to dynamic changes in the concentration of phenolic compounds. A response time (t95%) as low as 5 s has been determined. With flow injection, 120 samples per hour can be processed with a relative standard deviation of 2.4%. The electrode remains active for about 12 d. The detection limit for dopamine is 6 x 10(-6) M. This method of biosensor construction should be applicable to other enzyme-substrate systems.     

A low-cost,fast, disposable and sensitive biosensor study: flow injection analysis of glucose at poly-methylene blue-modified pencil graphite electrode

In this work, firstly methylene blue (MB) was electropolymerized onto pencil graphite electrode (PGE) surface for the electrocatalytic oxidation of NADH. Cyclic voltammograms show that oxidation potential of NADH at Poly-MB/PGE shifted to negative direction about 300 mV compared with bare PGE. These results indicate that Poly-MB/PGE exhibits a good electrocatalytic activity toward NADH oxidation. Then, a glucose biosensor study was performed based on the determination of enzymatically generated NADH by glucose dehydrogenase (GDH) which immobilized onto Poly-MB/PGE using glutaraldehyde cross-linking procedure. The biosensing of glucose in flow injection analysis (FIA) system was performed at GDH/Poly-MB/PGE for the first time. The electrocatalytic oxidation currents of enzymatically produced NADH obtained from FI amperometric current–time curves recorded at + 200 mV and in phosphate buffer solution at pH 7.0 containing 1.0 M KCl were linearly related to the concentration of glucose. Linear calibration plots are obtained in the concentration range from 0.01 to 1.0 mM. The limit of detection (LOD) was found to be 4.0 µM. A fast, sensitive, low-cost and disposable glucose biosensor was constructed in FIA system using GDH/Poly-MB/PGE; therefore, it might provide a new perspective for the fabrication of biosensor of other compounds such as glutamate, lactate and alcohol.     

Voltammetric/amperometric detection for liquid chromatography

A voltammetric/amperometric detector based on a dual-electrode electrochemical detector is described for liquid chromatography. The detector combines the advantages of both voltammetric and amperometric detection. A three-dimensional data array of current response as a function of both time (chromatographic domain) and potential (electrochemical domain) is obtained. From the chromatographic point of view, this allows post-experimental choice of the optimal detection potential. Different detection potentials can even be chosen for each chromatographic peak. Having the voltammetric data as well as the chromatographic data provides ready identification of chromatographically unresolved compounds and the ability to resolve such co-eluting compounds voltammetrically. The voltammetric data also provide a second method of peak identification for greater certainty in peak assignments. Voltammetric detection limits of less than 10 pmol of material injected on the column were achieved with this detection method. From the electrochemical perspective, voltammetric/amperometric detection provides a technique for obtaining hydrodynamic voltammograms with small amounts or small volumes of sample. Voltammograms can also be obtained for the individual components of complex mixtures without the need for isolation steps.