A Hybrid Genetic Expression Programming and Genetic Algorithm (GEP-GA) of Auto-Modeling Electrical Equivalent Circuit for Particle Structure Measurement With Electrochemical Impedance Spectroscopy (EIS)

A hybrid Genetic Expression Program and Genetic Algorithm (GEP-GA) is proposed for auto-modeling the Electrical Equivalent Circuit (EEC) of particle structure measurement with Electrochemical Impedance Spectroscopy (EIS). It combines the GEP with the ability of searching mathematical models and the GA with the ability of electrical parameters global searching. The GEP is used to modeling EEC of EIS, the GA is used to calculate the electrical parameters and fitness of the EEC. The hybrid method has the advantage of no need manually set. Firstly, the method is used to reconstruct EEC of simulation model and simultaneously calculate its electrical parameters. The results show that the auto-modeling EEC is same as the simulation's, and the accuracy of calculating electrical parameters over 99.5%. Secondly, a portable and detachable sensor is proposed to measure the EIS of particle solution. Finally, the GEP-GA is verified by auto-modeling the EEC of $10 ~\mu \text{m}$ Poly Methyl Methacrylate (10 PMMA), the linear correlation coefficient of EIS between experiment and auto-modeling EEC ${R}^{{2}}={0.99874}$ . Meanwhile, the EIS of $10 ~\mu \text{m}$ Polystyrene Magnetic particles (10 PSM), and $10 ~\mu \text{m}$ , $20 ~\mu \text{m}$ , $30 ~\mu \text{m}$ Polystyrene particles (10 PS, 20 PS, 30 PS) are also fitted with the EEC model of 10 PMMA. The results show that their linear correlation coefficient ${R}^{{2}}>{0.998}$ . It indicates that the hybrid of GEP-GA can auto-modeling the EEC and simultaneously calculate the electrical parameters. Furthermore, the electrical characters of the particle suspension and the particle structure can be measured with these electrical parameters.