Understanding the Impedance of CNOs-Graphene hybrid electrode through both experimental and simulated electrochemical impedance spectrum

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Using a combination of experimental measurements and molecular dynamic (MD) simulations, we study the impedance of hybrid electrode composed of graphene and carbon nanometer onions (CNOs). On the experiment’s side, electrochemical measurements are conducted on the electrodde sample prepared from growing CNOs onto the graphitic plane. The general trend of impedance’s variations with frequencies is identified at different temperatures and ion concentration. Parameter fitting of equivalent circuit is accomplished with the assistance from machine learning technique using neural network. On the simulation’s side, electrode geometries including concave slit-pore and convex CNO-pore surfaces are modeled to investigate ion movements. Based on trajectories of ion dynamics, the physical origin of corresponding equivalent circuit component such as constant phase element is revealed. Regarding the geometry of electrode surface, the divide between planar and nonplanar part is observed in terms of charging level and charging time constant. Between the slit-pore and CNO-pore geometries, the differences in impedance spectrum is quantitatively characterized by solving the topology of and parameter of transmission line model of the equivalent circuit. In the branch of transmission line model, the resistance and capacitance are both larger for the space closer to the pore bottom or further from pore mouth.