Cortina-Puig Montserrat, Muñoz-Berbel Xavier, Alonso-Lomillo M Asunción, Muñoz-Pascual Francisco J, Del Valle Manuel
Sensors and Biosensors Group, Department of Chemistry, Autonomous University of Barcelona, Edifici Cn, Barcelona E-08193, Spain.
Talanta. 2007 Apr 30;72(2):774-9. doi: 10.1016/j.talanta.2006.12.016. Epub 2007 Jan 16.
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.
在这项工作中，提出了从单个阻抗谱中同时定量三种碱性离子（钾、钠和铵）的方法。为此，使用了一种通用离子载体——二苯并 - 18 - 冠 - 6，将其包裹在通过电聚合生成的聚吡咯聚合物基质中作为识别元件。分别采用电化学阻抗谱（EIS）和人工神经网络（ANN）来获取和处理数据。实际上，EIS检测介质与传感层之间交换的离子，而ANN在经过适当的训练过程后，可以将阻抗谱转换为浓度值。采用顺序注射分析（SIA）系统进行操作，并自动生成训练ANN所需的信息。使用由两个隐藏层组成的反向传播神经网络获得了最佳结果：第一个隐藏层包含三个具有径向基函数的神经元，第二个隐藏层包含十个具有正切Sigmoid函数的神经元。由于三种商业肥料基质的高度复杂性，采用所提出的方法对其进行了测试。将实验结果与参考方法进行了比较。
