Electrochemical impedance spectroscopy (EIS) has been
emerging
as a promising tool to study the core mechanisms occurring within
metal halide perovskites (MHPs). Generally, MHPs show one or two semicircles
in the Nyquist spectra in the probed frequency range. However, in
the presence of external stimuli, often a Warburg diffusion or an
inductive loop is observed at low frequencies. In such cases, a comparison
of low-frequency parameters in both cases cannot be drawn because
of the lack of a unique electrical circuit (EC). To overcome the issue
of lack of EC, transformation of the frequency-domain technique to
the time domain is carried out. In this work, we investigated three
different cases of MAPbI3, MAPbBr3, and surface-passivated
MAPbBr3 single crystals (SCs), which showed one suppressed
semicircle, two semicircles, and a Warburg-like diffusion, respectively,
in the Nyquist response of EIS. Next, we transformed these spectra
into the time domain using the distribution of relaxation times (DRT)
technique, a machine-learning-assisted tool. The obtained results
suggest that in the case of Nyquist spectra with one semicircle (the
case of MAPbI3 SCs), the observed time constants using
EC and DRT are close enough. However, in the case of MAPbBr3 SC, three different time constants are obtained, associated with
high, medium, and low frequencies, although the Nyquist response showed
two semicircles. At last, in the presence of surface-passivated SCs,
the Warburg-like feature changes significantly for different passivation
times. Interestingly, the DRT spectra showed almost similar time constants,
through which reliable information on the low-frequency RC can be
extracted. Thus, DRT can pave the way for the easy and reliable interpretation
of EIS spectra, which is not possible using EC.