Explanation based on thermodynamic parameters regarding effect of sensing film thickness and amount of graphene oxide on sensor performance in aniline, N-phenylglycine and graphene oxide based electrochemical heavy metal ion sensor


  • Kusumita Dutta Department of Chemical Engineering, National Centre for Flexible Electronics, Indian Institute of Technology Kanpur, Kanpur, UP, India
  • Siddhartha Panda Department of Chemical Engineering, National Centre for Flexible Electronics, Indian Institute of Technology Kanpur, Kanpur, UP, India




Heavy metal, Partition coefficient, Enthalpy, Reorganization energy, Square wave voltammetry, Barrier width , Solvated ionic radius


Background: To construct a heavy metal ion sensor, selectivity and sensitivity are the key important parameters to be taken care of. In our earlier work, film thickness and amount of graphene oxide (GO) content in a novel composite ANGO, synthesized from aniline, N-phenylglycine and GO was varied and sensing parameters including sensitivity, limit of detection (LOD), thermodynamic parameter which includes -∆Gad and charge transport parameter including barrier width (BW), d, of charge transfer based on Simmon’s model were evaluated and compared and an LOD of 800 ppt for Cd2+ was achieved using square wave voltammetry (SWV) withstanding interference from several ions.

Methods: In this work, thermodynamic factors such as -∆Gad, ∆H, reorganization energy, partition coefficient and solvated ionic radius were used to explain the sensor performance with respect to film thickness and amount of GO. All the parameters were analyzed for different film thicknesses and amount of GO and a correlation was achieved. Finally, effect of electrochemical surface area of different polyaniline-based material on thermodynamic properties of detection process of Cd2+ was studied.    

Results: The variation of the thermodynamic properties for Cd2+ sensing with respect to film thickness and amount of GO were examined. Similarly, variation of thermodynamic properties for polyaniline based different sensing materials were examined. Correlation coefficients were developed from the thermodynamic parameters and the d values to explain the underlying mechanism behind improved sensor performance. 

Conclusions: This study can provide information on the thermodynamic properties which can be predicted from BW technique.  The correlation coefficients would help in designing polyaniline based novel sensing film material with the need of lesser number of experiments.


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