Pattern Recognition Applications in Conducting Polymer Based Sensors

Copyright (C IFAC Advanced Cuntrol of Chemical Proce sses. Banff. Canada. 1997

PATTERN RECOGNITION APPLICATIONS IN CONDUCTING POLYMER BASED SENSORS

Afshad Talaie and Jose A. Romagnoli

2.0saka National Research Institute 1-8-31 . Midorigaoka. Ikeda 563. Japan

1.ICI Laboratory o/Process Systems Engineering Chemical Engineering Department Universi/.v of Sydney NSW. 2006. Australia

Abstract A new approach towards the development of a novel pH sensor using electrically conducting polymers and a pattern recognition technique is addressed. The approach is based on computer analysis of different experimental works in which different polymer-based pH electrodes are examined. In this wotk, we present a novel conducting polymer pH sensor that can be used to detect the pH of even very acidic and basic solutions. Since reusibility and reproducibility of conducting polymer sensors have been controversial issues we also examine the ability of Artificial Intelligence (AI) in overcoming these problems. The introduced integrated ANN/polypyrrole based pH sensor has shown much better reproducibility in detecting pH of different acidic and basic media over conventional polymeric pH detectors. The AI ba'ied data acquisition is a new approach towards pattern recognition in conducting polymer based sensors and detector~. Our system can detect the pH in a reliable online/real time manner and also enables us to have access to the history of a desirable chemical process with respect to the extent of the acidity of the process. Keyword: Conducting Polymer, pH Sensor, Pattern Recognition

conductivity of the polymer. Polyaniline as an electroactive material also undergoes transitions between different conductivity states if different potentials are applied . Application of the potential and acidlbase treatment of the polymer both vary the chemical structure of the polymer which result in changing the conductivity and also the colour of the polymer. These chromatic changes in polyaniline by acidlbase treatment have led to an interest in pH indicators applications. An example of such chromatic changes while the pH or the applied potential are varied is illustrated in Figure I .

I. INTRODUCTION One group of polymer materials that has been at the forefront of recent developments in chemical activity and conducting characteristics areas is electroactive, conducting polymers. Interests in these novel materials has been demonstrated by scientists in many diverse areas such as electrochemistry , solidstate physics , information technology (Skotheim , 1990: Talaie, 1996). In recent times scientists have been giving particular attention to two novel polymer materials with unique physical and chemical properties. These two polymeric materials are polypyrrole and polyaniline ( Talaie and Esmaili, 1996). The usage of these novel materials in pH sensing technology has been of our interest in our studies (Talaie, 1997). It has been found that the conductivity of poly aniline is significantly dependent on the proton doping level. In other words the proton at ion process, which may occur by insertion of the polymer in acidic media, increases the

It has been suggested that the conduction mechanism in conducting polymers is significantly dependent upon the movement of charge along the polymer change. The conductivity of the polyaniline can be easily influenced by the protonation process because of the chemical structure of the polymer in which the charge can move easily along the polymer structure . This is more unlikely happen to polypyrrole

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materials since charges are more localised. Hence changes in the conductivity of polypyrrole by the acidlbase treatment is much less than what is observed in polyaniline materials. However, there have been few studies in which small changes in the conductivity of polypynole materials have been reponed while the pH of operational environment varied (Talaie, 1995). Although these two polymeric materials show a great potential for replacement of the popular glass electrode, they did not satisfy the market with respect to their reproducibility issue. In fact reproducibility of the conducting polymer based sensors have been the center of our recent activities at the ICI group within the Chemical Engineering Depanment at Sydney University. Different artificial intelligence methods have been employed to enhance the performance of the sensors with regards to the reusibility and reproducibility issues. The results are promising and have proven that combining an AI trained computer with the conducting polymer based detection technology improves the performance of the polymer based ion detectors (Talaie and Romagnoli, 1996). In this paper we shall repon on the improvement in reproducibility of results obtained for conducting polymer based pH sensors when an AI method is used. Since there have been only few studies on the utilisation of polypyrrole materials in pH detection technology, this repon demonstrates the ability of an integrated ANN/polypyrrole based pH sensor in detection of acidity of different media.

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from Aldrich. All acids were supplied by BDH. Polypyrrole films were galvanostatically produced on gold and platinum electrodes. Cyclic voltamrnetry was performed on a BAS CV-27 Voltammograph (Bio Analytical System. Lafayette, PA, USA). A BAS LC-4C amperometric detector was used for amperometric measurements. Pulse resistometry measurements were facilitated by the use of a resistometer developed at CSIRO Division of Mineral Products, Melbourne, Australia. A 10 m V DC power supply was employed for applying voltage, and a multimeter model HP 3645B was used for recording currents. The experimental work and data collection were carried out at the Chemistry Depanment, W ollongong University, Australia. The data processing and pattern recognition studies were carried out at Chemical Engineering Department , Sydney University, Australia. Polymerisations were carried out potentiostatically (at constant applied potential) in a three electrode chemical cell. All polymers were grown at constant charge and constant potential (E= 0.75 V and Q= 100 mC). The working electrode was the sandwich electrode, the reference and auxiliary electrodes were Ag/AgCI and Platinum plate respectively. Solutions of different pHs were made from HCI, H2 SO. for acidic media and from NaOH for basic media. These solutions were diluted with I M NaCI to keep the ionic strength relatively constant. The time response of each polymer during its conductive/non conductive transition to the pH treatment was measured by immersing the polymer in a high pH solution and then in a low pH solution. When the output current had stabilised (between I to 3 minutes) it was recorded and then using the Ohm's law the polymer resistance was calculated. The data was saved in a digital file for the data processing step. Data analysis was carried out in the MATLAB environment. Different matrices were made from the data and transferred to Microsoft Excel for final preparation of the data before being submitted to a neural network package software entitled Turbo Neuron for training and pattern recognition application,

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3. RESULTS AND DISCUSSIONS The introduced integrated ANN/conducting polymer based pH sensor uses the same apparatus and design previously described (Talaie et al. , 1996),. MATLABTh4 was used to filter out random noises in the experimental.electrochemical data. The filtered data was then transferred to the ANN trained computer. In the next step the input and output data were defmed for the system. Since the acidlbase and base/acid treatment were carried out immediately after each other and also considering the dynamic nature of the polymer, for each resistance value two different pHs were associated. Since our interest is in

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the acidic conductivity. The hydroxy influence is such that the polymer chain conformation and configuration looses its flexibility which results in localisation of charges along the polymer chain. As soon as the polymer was immersed in an acidic environment the movement of charges easily began along the polymer structure resulting in a more conductive material at lower pHs. This is the main reason that the output error for acidlbase treatment is 0.002 and the output error for base/acid treatment is lI.! almost 0.017. Although the error for the output 2 is ... [ 110 I .............. _ _ SIlo, ......... tic" much bigger than the output 1, it is in an acceptable range of error and suggests the high accuracy of the ANN modelling of pH sensor experiments involving • am conducting polymers. This can be demonstrated in detail by comparing of the predicted and target • ~a m output data. Such a comparison is presented in .., Figures 4 and 5 for each value of pHs detected by the integrated ANN/conducting polymer based pH • am .- - ..:. ...;:-~ ~ -:- . . sensor. As can be observed from the Figures the errors related to the output 1 are mainly in the pHs a .. between 6-8 for a range of detected pH between 0 to - - - - - - - - - ~-~14. In comparison the most of errors are in pH •• • "" between 3 to 4 for the output 2 where the hydroxy Epoch No. attack on the polymer needs to be compensated by Figure 2: The profile of training and test during protonation.

detecting pH the resistance data was introduced as input and the pH values were introduced as outputs. To create an accurate computer model and pattern, the training of the system should be carried out under preselected conditions. Different conditions were tried until an optimised conditions was found for the most effective and accurate detectinon of the pH of the operational . •

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It took only 12 seconds to train the data obtained in H2S04 and NaOH environments. In this learning process 96% improvement in initial error was achieved after 300 training cycles (epoch) with an error of 0.0104 and 0.0311 for training and test respectively in the final epoch (Figure 3). It was found that the acidlbase treatment (output I) results was more accurate than base/acid treatment results (output 2). ~J

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Figure 3: The percentage of error for detection of pH in H1 S04 and NaOH environment for both' acidlbase and base/acid treatment This is expected since the hydroxy attacks (at pH between 12 to 14) the polymer chain and therefore a large number of the protons are required to regain 343

This suggests that if the proton at ion process varies, the performance of the sensor also changes. To study such an effect in detail, the same polymer was studied in another acidic media (HCI) while the same training conditions were carried out. As expected more training cycles were needed (epoch 320) to achieve the best possible training. The final errors of outputs are summarised in Figure 6. According to the figure errors of 0.031 and 0.045 were experienced for the outputs I and 2 respectively. This was much higher than what

reponed in H2SO. (Figure 3) where the number of hydrogen was twice as much. This proves that the protonation process and the number of hydrogen in the acidic media was of crucial imponance in the performance of the conducting polymer based pH electrodes.

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An ANN computer trained network with a pattern recognition method has been used to enhance the performance of a polypyrrole based pH sensor. The sensor was used for detection of pH in different acidic and basic environments. It was found that the application of anificial intelligence methods in data processing and modelling of the pH sensor system leads to an integrated ANN/pH sensor system in which the detection of pH can be performed in a more reproducible manner. It has also been found that the type of acid and consequently the protonation process plays a crucial role in the performance of the introduced integrated system. This model prediction process is strongly recommended in the pH sensing technology involving conducting polymers if careful attention is paid in the polymerisation step and correct assumptions during modelling and pattern recognition are carried out.

Figure 5: The percentage of error for detection of pH in H1 SO. and NaOH environment for base/acid treatment

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References

Figure 6: The percentage of error for detection of pH in HCI and NaOH environment for both acidlbase and base/acid treatment

Talaie A. and Esmaili M. (l996a), An Enhancement to Polypyrrole/Chloride Ion Sensor Performance, Smart Mater. Struct., Vol. 5, p. 1 Talaie A. (1996b)., Conducting polypyrrole and polyaniline-based chemical sensors", Chemistry in Australia, p. 570. Talaie A. (1997a) , Conducting Polymer Based PH detector: A New Outlook to PH Sensing Technology, Polymer, In press. Talaie A. (1994), Electronic Propenies of Novel Conducting Polypyrrole and Polyaniline Materials, Ph.D Thesis, Wollongong University

If a comparison study of the predicted and target values is carried out for the values of individual pHs for the output 1 in HCl media (Figure 7), it can be pointed out that the accuracy of all individual detected pHs in the acidic range (PH between 0 to 6) is less than what experienced in H2SO. (Figure 4). This supports the effect of the protonation and type of acid involved in the operational environment in the performance of the integrated system. Taking all results into account, it can be said that the integrated ANN/polymer based pH sensor demonstrates a great potential for producing a reliable pH sensor with reasonable accuracy if the sensor preparation and acidlbase treatment are carefully performed. 344

Talaie A., and Romagnoli, I.A. (1996c), Application of Artificial Neural Networks to the Re al- Time Operation of Conducting Polymer Sensors: A Pattern Recognition Approach", Synth. Met., Vot. 82, p.27. Talaie A, Romagnoli I .A, and Mirhosseini A. (1997b), Towards an Online Conducting

Polymer Composite Based Electrode Using a Fuzzy Clustering Technique, Smart Materials& Structures, submitted. Skotheim T.A. (1986), Handbook of Conducting Polymers, Marcel Dekker, New York

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