Development of an optical fibre reflectance sensor for copper (II) detection based on immobilised salicylic acid

Immobilized salicylic acid onto XAD-2 (styrene–divinylbenzene cross-linked copolymer) has been attempted in this study as a reagent phase for the development of an optical fibre copper (II) sensor. The measurements were carried out at a given wavelength of 690.27 nm since it yielded the largest divergence different in reflectance spectra before and after reaction with the analyte element. The optimum response was obtained at pH 5.0. The linear dynamic range of Cu(II) was found within the concentration range of 1.0–2.0 mmol L⁻¹ with its LOD of 0.5 mmol L⁻¹. The sensor response from different probes (n = 9) gave an R.S.D. of 8.4% at 0.55 mmol L⁻¹ Cu(II). The effect of interfered ions at 1:1 molar ratio of Cu(II):foreign ion was also studied in this work.     

Simultaneous determination of epinephrine and ascorbic acid at the electrochemical sensor of triazole SAM modified gold electrode

The electrochemical sensor of triazole (TA) self-assembled monolayer (SAM) modified gold electrode (TA SAM/Au) was fabricated. The electrochemical behaviors of epinephrine (EP) at TA SAM/Au have been studied. The TA SAM/Au shows an excellent electrocatalytic activity for the oxidation of EP and accelerates electron transfer rate. The diffusion coefficient is 1.135 × 10⁻⁶ cm² s⁻¹. Under the optimum experiment conditions (i.e. 0.1 mol L⁻¹, pH 4.4, sodium borate buffer, accumulation time: 180 s, accumulation potential: 0.6 V, scan rate: 0.1 Vs⁻¹), the cathodic peak current of EP versus its concentration has a good linear relation in the ranges of 1.0 × 10⁻⁷ to 1.0 × 10⁻⁵ mol L⁻¹ and 1.0 × 10⁻⁵ to 6.0 × 10⁻⁴ mol L⁻¹ by square wave adsorptive stripping voltammetry (SWASV), with the correlation coefficient of 0.9985 and 0.9996, respectively. Detection limit is down to 1.0 × 10⁻⁸ mol L⁻¹. The TA SAM/Au can be used for the determination of EP in practical injection. Meantime, the oxidative peak potentials of EP and ascorbic acid (AA) are well separated about 200 ± 10 mV at TA SAM/Au, the oxidation peak current increases approximately linearly with increasing concentration of both EP and AA in the concentration range of 2.0 × 10⁻⁵ to 1.6 × 10⁻⁴ mol L⁻¹. It can be used for simultaneous determination of EP and AA.     

Packaging effect investigation of WL-CSP with a central opening: A case study on pressure sensors

This study reports the packaging effects of wafer-level chip scale packaging (WL-CSP) with a central opening on piezoresistive pressure sensors. A regular pressure sensor with calculated sensitivity of 3.1 × 10^?2 mVV^?1 kPa^?1 and a sensitive pressure sensor with calculated sensitivity of 32.0 × 10^?2 mVV^?1 kPa^?1 are investigated. A finite element (FE) model validated by experimental measurements is used to explore the sensing characteristics of the pressure sensors. The results show that the output variation of the packaged pressure sensor is dominated by the CTE mismatch not the piezoresistive coefficient change as temperature varies. WL-CSP with small polyimide (PI) thickness and large PI opening produces small packaging induced stress, making it ideal for precision sensing for both regular and sensitive pressure sensors.     

Development of wireless compressive/relaxation-stress measurement system integrated with pressure-sensitive carbon black-filled silicone rubber-based sensors

In order to detect the installation compressive stress and monitor the stress relaxation between two bending surfaces on a defensive furnishment, a wireless compressive-stress/relaxation-stress measurement system based on pressure-sensitive sensors is developed. The flexible pressure-sensitive stress sensor array is fabricated by using carbon black-filled silicone rubber-based composite. The wireless stress measurement system integrated with this sensor array is tested with compressive stress in the range from 0 MPa to 3 MPa for performance evaluation. Experimental results indicate that the fractional change in electrical resistance of the pressure-sensitive stress sensor changes linearly and reversibly with the compressive stress, and its fractional change goes up to 355% under uniaxial compression; the change rate of the electrical resistance can track the relaxation stress and give out a credible measurement in the process of stress relaxation. The relationship between input (compressive stress) and output (the fractional change in electrical resistance) of the pressure-sensitive sensor is ΔR/R₀ = σ × 1.2 MPa^?1. The wireless compressive stress measurement system can be used to achieve sensitivity of 1.33 V/MPa to the stress at stress resolution of 920.3 Pa. The newly developed wireless stress measurement system integrated with pressure-sensitive carbon black-filled silicone rubber-based sensors has advantages such as high sensitivity to stress, high stress resolution, simple circuit and low energy consumption.     

Humidity-insensitive and low oxygen dependence tungsten oxide gas sensors

Gas sensing characteristics of WO₃ powder and its physical properties under different heat treatment conditions have been investigated. The WO₃ powder was synthesized by wet process from ammonium tungstate parapentahydrate and nitric solution. The precipitated product was then calcined at 300–800 °C for 2–12 h. The physical properties of the products were characterized by using X-ray diffractometer (XRD), scanning electron microscope (SEM), and BET method. It was found that the crystallite size, particle size and surface area of the WO₃ powders were in the range of 30–45 nm, 0.1–3.0 μm and 1.2–3.7 m²/g, respectively. Calcination at higher temperature and longer time led to the increase of particle size by more than 300%, and reduction in specific surface area by more than 60%. However, the crystallite size was found to increase only by ∼30% under identical heat treatment. These results inferred that such heat treatment had more profound effect on crystallite aggregation than on crystallite growth. Gas sensing measurement showed that the largest change of output voltage to both ethyl alcohol and ammonia was obtained from the sensor calcined at 600 °C for 2 h, which had the highest surface area. However, the highest sensitivity which is defined as the ratio of sensor's resistance in air to that in the sample gas, R_air/R_gas, was obtained from the sensor calcined at 600 °C for 6 h due to its highest background resistance in air. Moreover, it was also found that the sensors were less sensitive to the oxygen content in the carrier gas and did not sensitive at all to water vapor.     

Evaluation of response characteristics of resistive oxygen sensors based on porous cerium oxide thick film using pressure modulation method

In order to reduce the response time of resistive oxygen sensors using porous cerium oxide thick film, it is important to ascertain the factors controlling response. Pressure modulation method (PMM) was used to find the rate-limiting step of sensor response. This useful method measures the amplitude of sensor output (H(f)) for the sine wave modulation of oxygen partial pressure at constant frequency (f). In PMM, “break” response time, which is minimum period in which the sensor responds precisely, can be measured. Three points were examined: (1) simulated calculations of PMM were carried out using a model of porous thick film in which spherical particles are connected in a three-dimensional network; (2) sensor response speed was experimentally measured using PMM; and (3) the diffusion coefficient and surface reaction coefficient were estimated by comparison between experiment and calculation. The plot of log f versus log H(f) in the high f region was found to have a slope of approximately −0.5 for both porous thick film and non-porous thin film, when the rate-limiting step was diffusion. Calculations showed the response time of porous thick film was 1/20 that of non-porous thin film when the grain diameter of the porous thick film was the same as the thickness of non-porous thin film. At 973 K, “break” response time (t_b) of the resistive oxygen sensor was found by experiment to be 109 ms. It was concluded that the response of the resistive oxygen sensor prepared in this study was strongly controlled by diffusion at 923–1023 K, since the experiment revealed that the slope of plot of log f versus log H(f) in the high f region was approximately −0.5. At 923–1023 K, the diffusion coefficient of oxygen vacancy in porous ceria (D_V) was expressed as follows: D_V (m²s⁻¹) = 5.78 × 10⁻⁴ exp(−1.94 eV/kT). At 1023 K, the surface reaction coefficient (K) was found to exceed 10⁻⁴ m/s.     

Development of a mercury optical sensor based on immobilization of 4-(2-pyridylazo)-resorcinol on a triacetylcellulose membrane

A new optical sensor for mercury(II) ions is developed based on immobilization of 4-(2-pyridylazo)-resorcinol (PAR) on a triacetylcellulose membrane. Chemical binding of Hg²⁺ ions in solution with a PAR immobilized on the triacetylcellulose surface could be monitored spectrophotometrically at 525 nm. The optode shows excellent response over a wide concentration range of 5–3360 μM Hg(II) with a limit of detection of 1.5 μM Hg(II). The influence of factors responsible for the improved sensitivity of the sensor were studied and identified. The response time of the optode was 20 min for a stable solution, and was 15 min for a stirrer solution. The influence of potential interfering ions on the determination of 5 × 10⁻⁵ M Hg(II) was studied. The sensor was applied for determination of Hg(II) in water samples.     

Electrochemical determination of ascorbic acid in fruits on a vanadium oxide polypropylene carbonate modified electrode

A novel vanadium oxide polypropylene carbonate modified glassy carbon electrode was developed and used for the measurement of ascorbic acid (AA). The electrode was prepared by casting a mixture of vanadium tri(isopropoxide) oxide (VO(OC₃H₇)₃) and poly(propylene carbonate) (PPC) onto the surface of a glassy carbon electrode. The electrochemical behavior of the VO(OC₃H₇)₃–PPC film modified glassy carbon electrode was investigated by cyclic voltammetry and amperometry. This modified electrode exhibited electrocatalytic response to the oxidation of ascorbic acid. Compared with a bare glassy carbon electrode, the modified electrode exhibits a 220 mV shift of the oxidation potential of ascorbic acid in the cathodic direction and a marked enhancement of the current response. The response current revealed a good linear relationship with the concentration of ascorbic acid in the range of 4 × 10⁻⁸ and 1 × 10⁻⁴ mol L⁻¹ and the detection limit of 1.5 × 10⁻⁸ mol L⁻¹ (S/N = 3) in the pH 8.06 Britton–Robinson solution. Quantitative recovery of the ascorbic acid in synthetic samples has been obtained and the interferences from different species have been studied. The method has been successfully applied to the determination of ascorbic acid in fruits. The concentrations of ascorbic acid measured by this method are in good agreement with the literature value. It is much promising for the modified films to be used as an electrochemical sensor for the detection of ascorbic acid.     

Chromium(III)-selective sensor based on tri-o-thymotide in PVC matrix

Tri-o-thymotide (I) has been used as an electroactive material in PVC (poly(vinyl chloride)) matrix for fabrication of chromium(III)-selective sensor. The membrane containing tri-o-thymotide, sodium tetraphenyl borate (NaTPB), dibutyl phthalate (DBP) and PVC in the optimum ratio 5:1:75:100 (w/w) exhibits a working concentration range of 4.0 × 10⁻⁶ to 1.0 × 10⁻¹ M with a Nernstian slope of 20.0 ± 0.1 mV/decade of activity in the pH range of 2.8–5.1. The detection limit of this sensor is 2.0 × 10⁻⁷ M. The electrode exhibits a fast response time of 15 s, shows good selectivity towards Cr³⁺ over a number of mono-, bi- and trivalent cations and can also be used in partially non-aqueous medium (up to 15%, v/v) also. The assembly has been successfully used as an indicator electrode in the potentiometric titration of chromium(III) against EDTA and also to determine Cr(III) quantitatively in electroplating industry waste samples.     

Red emitting MTiO3 (M = Ca or Sr) phosphors doped with Eu3+ or Pr3+ with some cations as co-dopants

Ca (or Sr)TiO₃:Eu³⁺, M (Li⁺ or Na⁺ or K⁺) and CaTiO₃:Pr³⁺, M (Li⁺ or Na⁺ or Ag⁺ or K⁺ or Gd³⁺ or La³⁺) powders were prepared by combustion synthesis method and the samples were further heated to ～1000 °C to improve the crystallinity. The structure and morphology of materials were examined by X-ray diffraction (XRD) and a scanning electron microscopy (SEM). The morphologies of SrTiO₃:Eu³⁺, CaTiO₃:Eu³⁺ or CaTiO₃:Pr³⁺ powders co-doped with other metal ions were very similar. Small and coagulated particles of nearly cubical shapes with small size distribution having smooth and regular surface were formed. Photo-luminescence spectra of CaTiO₃:Pr³⁺ and co-doped either with Li⁺, Na⁺, K⁺, Ag⁺, La³⁺ or Gd³⁺ ions showed red emissions at 613 nm due to the ¹D₂ → ³H₄ transition of Pr³⁺. The variation of intensity of emission peak with different co-doping follows the order: K⁺ > Ag⁺ > Na⁺ > Li⁺ > La³⁺ > Gd³⁺. The characteristic emissions of CaTiO₃:Eu³⁺ lattices had strong emission at 614 and 620 nm for ⁵D₀ → ⁷F₂ with other weak transitions observed at 580, 592, 654, 705 nm for ⁵D₀ → ⁷F_n transitions where n = 0, 1, 3, 4 respectively in all host lattices. Photoluminescence intensity in SrTiO₃:Eu³⁺ is more than CaTiO₃:Eu³⁺ lattices. A remarkable increase of photoluminescence intensity (in ⁵D₀ → ⁷F₂ transition) was observed if co-doped with Li⁺ ions in CaTiO₃:Eu³⁺ and SrTiO3:Eu³⁺.     

Bayesian modelling of algal mass occurrences—using adaptive MCMC methods with a lake water quality model

Our study aims to estimate confounded effects of nutrients and grazing zooplankton (Crustacea) on phytoplankton groups—specifically on nitrogen-fixing Cyanobacteria—in the shallow, mesotrophic Lake Pyhäjärvi in the northern hemisphere (Finland, northern Europe, lat. 60°54′–61°06′, long. 22°09′–22°22′). Phytoplankton is modelled with a non-linear dynamic model which describes the succession of three dominant algae groups (Diatomophyceae, Chrysophyceae, nitrogen-fixing Cyanobacteria) and minor groups summed together as a function of total phosphorus, total nitrogen, temperature, global irradiance and crustacean zooplankton grazing. The model is fitted using 8 years of in situ observations and adaptive Markov chain Monte Carlo (MCMC) methods for estimation of model parameters. The approach offers a way to deal with noisy data and a large number of weakly identifiable parameters in a model. From our posterior simulations we calculate the lower limit for zooplankton carbon mass concentration (45 μgC L⁻¹) and the upper limit for total phosphorus concentration (16 μg L⁻¹) that satisfy with 0.95 probability our predefined water quality criteria (Cyanobacteria concentration during late summer period does not exceed the value 0.86 mg L⁻¹). Within the observational range total phosphorus has marginal effect on Cyanobacteria compared to the zooplankton grazing effect, which is temperature-dependent. Extensive fishing efforts are needed to attain the criteria.     

Human activity recognition with smartphone sensors using deep learning neural networks

Human activities are inherently translation invariant and hierarchical. Human activity recognition (HAR), a field that has garnered a lot of attention in recent years due to its high demand in various application domains, makes use of time-series sensor data to infer activities. In this paper, a deep convolutional neural network (convnet) is proposed to perform efficient and effective HAR using smartphone sensors by exploiting the inherent characteristics of activities and 1D time-series signals, at the same time providing a way to automatically and data-adaptively extract robust features from raw data. Experiments show that convnets indeed derive relevant and more complex features with every additional layer, although difference of feature complexity level decreases with every additional layer. A wider time span of temporal local correlation can be exploited (1 × 9–1 × 14) and a low pooling size (1 × 2–1 × 3) is shown to be beneficial. Convnets also achieved an almost perfect classification on moving activities, especially very similar ones which were previously perceived to be very difficult to classify. Lastly, convnets outperform other state-of-the-art data mining techniques in HAR for the benchmark dataset collected from 30 volunteer subjects, achieving an overall performance of 94.79% on the test set with raw sensor data, and 95.75% with additional information of temporal fast Fourier transform of the HAR data set.     

Spin-valve planar Hall sensor for single bead detection

The planar Hall effect (PHE) sensor with a junction size of 3 μm × 3 μm for a single micro-bead detection has been fabricated successfully using a typical spin-valve thin film Ta(5)/NiFe(16)/Cu(1.2)/NiFe(2)/IrMn(15)/Ta(5) nm. The PHE sensor exhibits a sensitivity of about 7.2 μV Oe^?1 in the magnetic field range of ±7 Oe approximately. We have performed an experiment to illustrated the possibility of single micro-bead detection by using a PHE sensor. A single micro-bead of 2.8 μm diameter size is secluded from 0.1% dilute solution of the Dynabeads^® M-280 dropped on the sensor surface and is located on the sensor junction by using a micro magnetic needle. The comparison of the PHE voltage profiles in the field range from 0 to 20 Oe in the absence and presence of a single micro-bead identifies a single Dynabeads^® M-280, the maximal signal change as large as ΔV ～ 1.1 μV can be obtained at the field ～6.6 Oe. The results are well described in terms of the reversal of a basic single domain structure.     

A survey on wireless sensor network infrastructure for agriculture

The hybrid wireless sensor network is a promising application of wireless sensor networking techniques. The main difference between a hybrid WSN and a terrestrial wireless sensor network is the wireless underground sensor network, which communicates in the soil. In this paper, a hybrid wireless sensor network architecture is introduced. The framework to deploy and operate a hybrid WSN is developed. Experiments were conducted using a soil that was 50% sand, 35% silt, and 15% clay; it had a bulk density of 1.5 g/cm³ and a specific density of 2.6 cm^? 3. The experiment was conducted for several soil moistures (5, 10, 15, 20 and 25%) and three signal frequencies (433, 868 and 915 MHz). The results show that the radio signal path loss is smallest for low frequency signals and low moisture soils. Furthermore, the node deployment depth affected signal attenuation for the 433 MHz signal. The best node deployment depth for effective transmission in a wireless underground sensor network was determined.     

Thin film temperature sensor for real-time measurement of electrolyte temperature in a polymer electrolyte fuel cell

This paper describes a technique for the measurement of the electrolyte temperature in an operating polymer electrolyte fuel cell (PEFC). A patterned thin film gold thermistor embedded in a 16 μm thick parylene film was laminated in the Nafion^® electrolyte layer for in situ temperature measurements. Experimental results show that the sensor has a linear response of (3.03 ± 0.09) × 10⁻³ °C⁻¹ in the 20–100 °C temperature range and is robust enough to withstand the electrolyte expansion forces that occur during water uptake. An electrolyte temperature increase of 1.5 °C was observed in real-time when operating the fuel cell at 0.2 V and a current density of 0.19 A/cm². The temperature sensitivity of the present sensor is in an order of magnitude better than the conventional micro-thermocouples that have been reported. Additionally, use of micro-fabrication techniques allows for an accurate placement of the temperature sensor within the fuel cell. Simulation results show that the sensor has no significant effect on the local temperature distribution.     

Design and performance of a microcantilever-based hydrogen sensor

This paper describes the design of, and the effects of basic environmental parameters on, a microelectromechanical (MEMS) hydrogen sensor. The sensor contains an array of 10 micromachined cantilever beams. Each cantilever is 500 μm wide×267 μm long×2 μm thick and has a capacitance readout capable of measuring cantilever deflection to within 1 nm. A 20-nm-thick coating of 90% palladium–10% nickel bends some of the cantilevers in the presence of hydrogen. The palladium–nickel coatings are deposited in ultra-high-vacuum (UHV) to ensure freedom from a “relaxation” artifact apparently caused by oxidation of the coatings. The sensor consumes 84 mW of power in continuous operation, and can detect hydrogen concentrations between 0.1 and 100% with a roughly linear response between 10 and 90% hydrogen. The response magnitude decreases with increasing temperature, humidity, and oxygen concentration, and the response time decreases with increasing temperature and hydrogen concentration. The 0–90% response time of an unheated cantilever to 1% hydrogen in air is about 90 s at 25 °C and 0% humidity.     

Flexible vapour sensors using single walled carbon nanotubes

Thin, strongly adhering films of single-walled carbon nanotube bundles (SWNT) on flexible substrates such as poly(ethyleneterephthalate) (PET) were used for vapour sensing (hexane, toluene, acetone, chloroform, acetonitrile, methanol, water, etc.). These sensors are extremely easy to fabricate using the line patterning method. For example, ‘4-probe’ sensor patterns are drawn on a computer and then printed on overhead transparency (PET) sheets. These PET patterns were coated with films of electronically conductive SWNT bundles (1–2 μm thick) by dip-coating in aqueous surfactant-supported dispersions and mounted in glass chambers equipped for vapour sensing. Experiments conducted under saturated vapour conditions in air showed sensor responses that correlated well with solvent polarity [E_T(30) scale]. Similar results were obtained under controlled vapour conditions (no air) at 10,000 ppm. Control experiments using films of carbon black on PET (Aquadag-E^®), also prepared by the line patterning method, showed very little response to vapours under identical experimental conditions. The sensors are very flexible, e.g., they can be bent to diameters as small as 10 mm without significantly compromising sensor function.     

A 24-h forecast of ozone peaks and exceedance levels using neural classifiers and weather predictions

A neural network combined to a neural classifier is used in a real time forecasting of hourly maximum ozone in the centre of France, in an urban atmosphere. This neural model is based on the MultiLayer Perceptron (MLP) structure. The inputs of the statistical network are model output statistics of the weather predictions from the French National Weather Service. These predicted meteorological parameters are very easily available through an air quality network. The lead time used in this forecasting is (t + 24) h. Efforts are related to a regularisation method which is based on a Bayesian Information Criterion-like and to the determination of a confidence interval of forecasting. We offer a statistical validation between various statistical models and a deterministic chemistry-transport model. In this experiment, with the final neural network, the ozone peaks are fairly well predicted (in terms of global fit), with an Agreement Index = 92%, the Mean Absolute Error = the Root Mean Square Error = 15 μg m⁻³ and the Mean Bias Error = 5 μg m⁻³, where the European threshold of the hourly ozone is 180 μg m⁻³.To improve the performance of this exceedance forecasting, instead of the previous model, we use a neural classifier with a sigmoid function in the output layer. The output of the network ranges from [0,1] and can be interpreted as the probability of exceedance of the threshold. This model is compared to a classical logistic regression. With this neural classifier, the Success Index of forecasting is 78% whereas it is from 65% to 72% with the classical MLPs. During the validation phase, in the Summer of 2003, six ozone peaks above the threshold were detected. They actually were seven.Finally, the model called NEUROZONE is now used in real time. New data will be introduced in the training data each year, at the end of September. The network will be re-trained and new regression parameters estimated. So, one of the main difficulties in the training phase – namely the low frequency of ozone peaks above the threshold in this region – will be solved.     

A micro shear stress sensor based on laterally aligned carbon nanotubes

This paper reports the development of a micro thermal shear stress sensor that utilizes multiwalled carbon nanotubes as the sensing element. The sensor was fabricated by laterally aligning randomly distributed nanotubes into a 360 μm long and 90 μm wide conductive trace between two triangular shaped micro electrodes through the use of a high frequency AC electric field. During operation, the aligned nanotubes are electrically heated to an elevated temperature and surface shear stress is measured indirectly by the amount of convective heat transfer from the heated nanotubes to the surrounding fluid flow.The nanotube alignment process was primarily controlled by three different phenomena: dielectrophoresis, joule heating, and Brownian motion. Numerical simulations, together with experimental verifications, indicated that a successful alignment could only be realized if: (1) the dielectrophoretic force was positive, (2) the electro-thermal force was also positive, and (3) the dielectrophoretic force was high enough to overcome Brownian motion. The aligned nanotube trace has a room-temperature resistance of 580 Ω, which corresponds to a conductivity of 2.7 × 10⁴ S/m. The absolute temperature coefficient of resistivity ranges from 0.01 to 0.04% °C⁻¹. This is about one order of magnitude smaller than the highly doped polysilicon sensing material used in the MEMS micro shear stress sensor. The shear stress sensitivity of the nanotube trace operated at a 3% overheat ratio is found to follow the theoretical sensor power ∝ (shear stress)^1/3 relationship, provided the shear stress level is higher than 0.34 mPa. This result confirms the feasibility of using aligned multi-walled carbon nanotubes as a thermal shear stress sensing material.     

Thick film sensors based on laccases from different sources immobilized in polyaniline matrix

Thick film electrode based biosensors containing Trametes versicolor (TvL) and Aspergillus niger (AnL) laccases and Agaricus bisporus tissues (AbT) were developed for the determination of phenolic compounds and the measurement was based on oxygen consumption in relation to analyte oxidation. The electrodeposited organic polymer; polyaniline was used as a matrix for the immobilization in the preparation of thick film sensors. The systems were calibrated for different phenolic substances. A linearity was obtained in concentration range between 0.4 and 6.0 μM phenol, 0.2 and 1.0 μM catechol, 2.0 and 20.0 μM l-DOPA for TvL based biosensor; for AnL based enzyme electrode 0.4 and 4.0 μM phenol, 0.4 and 15 μM catechol, 0.4 and 6.0 μM l-DOPA; for AbT electrode 1.0 and 10 μM phenol, 0.4 and 1.6 μM catechol, 1.0 and 10 μM l-DOPA, respectively, in the response time of 300 s. Furthermore, as well as sample application and accuracy, optimum pH, temperature and thermal stabilities of the proposed systems were also detected.