Effect of lead accumulation in maize leaves on their chemical images created by a flow-through electronic tongue.

A flow-through electronic tongue based on miniaturized ion-selective electrode array was used for the classification of the maize leaf samples (Zea mays) exposed to media containing Pb(II) ions. The system provided a good recognition of the extracts from the plant leaves treated with solutions of varying concentrations of Pb(NO(3))(2). Additionally, samples derived from specific segments of the maize leaf, representing different developmental stages of cells, were also discriminated. The presented results showed that the developed sensor array combined with Partial Least Squares-Discriminant Analysis (PLS-DA) technique allowed to recognize the plant samples on the basis of the changes in the ionic composition of the leaf homogenates.

SIA system employing the transient response from a potentiometric sensor array--Correction of a saline matrix effect.

A Sequential Injection Analysis (SIA) system and an 8-potentiometric all-solid-state sensor array were coupled in a simple and automated electronic tongue device. The potentiometric sensors used were planar microfabricated structures with standard PVC membranes deposited onto a gold contact. The SIA system permitted the automated operation and generation of the calibration data, needed to build an Artificial Neural Network model, thanks to the precise dosing and mixing of volumes of stock solutions. The resolution of a four-ion mixture, i.e. ammonium, sodium, nitrate and chloride was the study case used for characterization of the system. Two different variants for signal acquisition, steady-state and transient recording, were arranged and compared. The dynamic treatment is shown to offer improved performance thanks to the benefits of the kinetic resolution. For this, it first extracts meaningful data from a FFT transform of each sensor's transient, which is then fed to an ANN model for estimation of each concentration in the four-ion mixture. While in a standard laboratory situation there was no difference between the two approaches, the dynamic treatment allowed the correction of a matrix effect in the case study, where an uncontrolled saline effect could be counterbalanced.

Monitoring of cell cultures with LTCC microelectrode array.

Monitoring of cell cultures in microbioreactors is a crucial task in cell bioassays and toxicological tests. In this work a novel tool based on a miniaturized sensor array fabricated using low-temperature cofired ceramics (LTCC) technology is presented. The developed device is applied to the monitoring of cell-culture media change, detection of the growth of various species, and in toxicological studies performed with the use of cells. Noninvasive monitoring performed with the LTCC microelectrode array can be applied for future cell-engineering purposes.

Direct and two-stage data analysis procedures based on PCA, PLS-DA and ANN for ISE-based electronic tongue-Effect of supervised feature extraction.

A novel strategy of data analysis for artificial taste and odour systems is presented in this work. It is demonstrated that using a supervised method also in feature extraction phase enhances fruit juice classification capability of sensor array developed at Warsaw University of Technology. Comparison of direct processing (raw data processed by Artificial Neural Network (ANN), raw data processed by Partial Least Squares-Discriminant Analysis (PLS-DA)) and two-stage processing (Principal Components Analysis (PCA) outputs processed by ANN, PLS-DA outputs processed by ANN) is presented. It is shown that considerable increase of classification capability occurred in the case of the new method proposed by the authors.

Ion selective transistor modelling for behavioural simulations.

Computer aided design and simulation of complex silicon microsystems oriented for environment monitoring requires efficient and accurate models of ion selective sensors, compatible with the existing behavioural simulators. This paper concerns sensors based on the back-side contact Ion Sensitive Field Effect Transistors (ISFETs). The ISFETs with silicon nitride gate are sensitive to hydrogen ion concentration. When the transistor gate is additionally covered with a special ion selective membrane, selectivity to other than hydrogen ions can be achieved. Such sensors are especially suitable for flow analysis of solutions containing various ions. The problem of ion selective sensor modelling is illustrated here on a practical example of an ammonium sensitive membrane. The membrane is investigated in the presence of some interfering ions and appropriate selectivity coefficients are determined. Then, the model of the whole sensor is created and used in subsequent electrical simulations. Providing that appropriate selectivity coefficients are known, the proposed model is applicable for any membrane, and can be straightforwardly implemented for behavioural simulation of water monitoring microsystems. The model has been already applied in a real on-line water pollution monitoring system for detection of various contaminants.

Towards advanced chemical microsensors-an overview.

The paper presents design and performance of miniaturized chemical sensors based on silicon transducers: ion-sensitive field effect transistor (ISFET) and solid-state electrode (SSE). The sensors were fabricated as back-side contact structures, which facilitate their mounting in a flow-cell. The role of an intermediate layer between the transducer and the ion-selective membrane is discussed. Various polymeric matrices were used to manufacture microsensors: polysiloxanes, polyacrylates (polymethacrylates), polyurethanes.