空白： Automated intelligent analyzer of electrochemical impedance spectroscopy (AIA-EIS) currently has three main automated function modules: EIS automated validation and improvement (EIS-AVI), equivalent circuit model (ECM) prediction, and ECM parameter fitting, which can basically cover the EIS preprocess before any mechanism analysis.

EIS automated validation and improvement (EIS-AVI) module [1] Fig. 1 (a) Nyquist and (b) Bode plots of a typical experimental EIS with obvious outliers. The inset in (a) is the enlargement of the area where the outliers detected by EIS-AVI locates. The parameter setting in one outlier detection workflow is outlier search threshold = Q2 and residual combination = ‘|ε_S-G,Im|, |ε_Im|’. In EIS-AVI, χ²_Threshold = 2.5×10^-2 , and n_Threshold = 10% of the EIS data number (30) = 3. The detected outliers are marked as big red stars, and their detected sequences are labeled by (1), (2), (3).