Kyungsoon Park1, Byoung-Yong Chang2, Seongpil Hwang1. 1. Department of Advanced Materials Chemistry, Korea University, Sejong 30019, Korea. 2. Department of Chemistry, Pukyong National University, Busan 48513, South Gyeongsang, Korea.
Abstract
Tafel analysis and electrochemical impedance spectroscopy (EIS) have been widely used to characterize many kinds of electrocatalysts. The former provides the kinetic information of an electrochemical reaction with the exchange current while the latter does with the charge transfer resistance closely related to the exchange current. Both techniques, however, suffer from practical troubles which often decrease their reliabilities. In order to circumvent those troubles, an alternative was suggested that Tafel analysis was combined with EIS, even though its theoretical background was not clearly established. Tafel analysis is based on dc measurement, and EIS is on an ac one, respectively. Here, inspired by the second generation of EIS from chronoamperometry, we try to find how those techniques are correlated by investigating an amperometric response from EIS. The first step is Fourier transform of an arbitrary dc potential signal in the time domain to obtain the amplitudes and phases of the Fourier series which are equivalent to ac signals of each frequency. Second, with the Fourier series being applied onto the impedance data, the responding currents of each frequency are calculated by Ohm's law. Third, the current in the frequency domain is transferred back to the time domain by inverse Fourier transform to yield chronoamperometric or Tafel plots depending on the type of the applied dc potential. Finally, we can study Tafel plots based on EIS at different conditions and their correlations which are expected to be a better indicator for characterizing electrocatalysts instead of the slope of the classical Tafel analysis.
Tafel analysis and electrochemical impedance spectroscopy (EIS) have been widely used to characterize many kinds of electrocatalysts. The former provides the kinetic information of an electrochemical reaction with the exchange current while the latter does with the charge transfer resistance closely related to the exchange current. Both techniques, however, suffer from practical troubles which often decrease their reliabilities. In order to circumvent those troubles, an alternative was suggested that Tafel analysis was combined with EIS, even though its theoretical background was not clearly established. Tafel analysis is based on dc measurement, and EIS is on an ac one, respectively. Here, inspired by the second generation of EIS from chronoamperometry, we try to find how those techniques are correlated by investigating an amperometric response from EIS. The first step is Fourier transform of an arbitrary dc potential signal in the time domain to obtain the amplitudes and phases of the Fourier series which are equivalent to ac signals of each frequency. Second, with the Fourier series being applied onto the impedance data, the responding currents of each frequency are calculated by Ohm's law. Third, the current in the frequency domain is transferred back to the time domain by inverse Fourier transform to yield chronoamperometric or Tafel plots depending on the type of the applied dc potential. Finally, we can study Tafel plots based on EIS at different conditions and their correlations which are expected to be a better indicator for characterizing electrocatalysts instead of the slope of the classical Tafel analysis.
Electrochemical energy
conversion has drawn much attention as a
renewable energy. The key is the development of efficient and cost-effective
electrocatalysts for various redox reactions such as hydrogen evolution,
hydrogen oxidation, oxygen evolution reaction, oxygen reduction, and
CO2 reduction. Understanding mechanisms and estimating
the efficiencies have frequently been sought using the Tafel analysis
based on voltammetry. Although the slope of the Tafel plot offers
both the exchange current (i0) and the
transfer coefficient (α) for an electrocatalyst, it is often
complicated by non-faradic currents, iR-drops, and conductivity of
the catalyst. Besides, the linear region for the slope on the plot
of log(current) versus potential is arbitrarily selected depending
on the personal aspect, which makes the analysis unreliable. Even
a small difference in the values of the slope caused by different
region selection can bring about a big difference in the values of
kinetic parameters such as i0 and α,
making the comparison unfair. Electrochemical impedance spectroscopy
(EIS) has been an alternative method to characterize electrocatalysts.[1,2] While voltammetry measures current (i) signals
upon dc potential (E) and shows the i–E relationship, EIS measures impedance (Z) of the
electrochemical cell using ac potentials, and shows Z dependent on frequency. Here, note that Z describes the relationship
between the potential and the current. Typically, the impedance spectra
are analyzed by employing a proper equivalent circuit composed of
various combinations of resistors and capacitors. Those electric components
are equivalent to physical phenomena such as charge transfer, mass
transfer, electrical double layer, film resistance, medium conductivity,
and so forth. Once experimental data are fitted to the appropriate
equivalent circuit, the values of the equivalent electric components
describe the parameters of the corresponding phenomena. The long measuring
time of the conventional EIS apparatus especially for low frequency,
however, prohibited further application of EIS. As an alternative
method, EIS based on Fourier transform (FT-EIS) has been introduced
by superposition of sine wave with several frequency.[3,4] Recently, FT-EIS was applied to the characterization of biosensros,[5] and to the development of the electrochemical
technique combined with scanning electrochemical microscopy called
scanning electrochemical impedance microscopy.[6−9] Although EIS is generally useful
in studying on electrocatalysts and characterization of films including
polymers,[10] graphene,[11] metal organic framework,[12] and
biomolecules, comparisons between the results reported in other literatures
are not straightforward because impedance measurements are made at
different dc bias potentials in the individual reports.Taking
only advantages of voltammetry for Tafel analysis and EIS
into account, Vrubel et al. recently developed a modified Tafel plot
based on EIS. The charge transfer resistances (Rct) at various potentials are measured by EIS and plotted along
the potential, and finally a voltammetric resistance plot is obtained.[13] The exchange current (i0) is calculated using the reciprocal relationship between Rct and i0. This
approach successfully circumvents the drawback of the classical Tafel
analysis with the help of EIS and was applied to the characterization
of various electrocatalysts.[14−17] Even though the method has been effectively applied
to research on electrocatalysts, conversion from electrochemical impedance
to the voltammetric curve has not been clearly studied and should
be discovered for further utilization and deeper insight for the electrocatalytic
reaction.The biggest hurdle for finding the correlation is
that those two
techniques measure dc and ac currents in two different domains, respectively;
Tafel analysis is based on current measurement in the time domain
while electrochemical impedance in the frequency domain. Fortunately,
those two measurements are known to be related to each other through
Fourier transform. In the reports on the second generation Fourier
transform EIS (2G FT-EIS), a current response is recorded upon a dc
voltage step of 10 mV, namely, chronoamperometry (CA), and converted
to the impedance spectrum that would be obtained using ac voltage
waves in the conventional impedance technique. A potential step is
the integral of the dirac δ function containing ideally all
the frequencies with the identical phases. As shown in Scheme A, the resulting current is
apparently a dc signal, but its derivative is practically responsible
for the dirac δ function, and can give us the information of
ac currents in the frequency domain after Fourier transform assuming
the linear system for the electrochemical processes.[1,2]
Scheme 1
Schematic Diagrams of (A) the FT-EIS Measurement and the Reverse
FT-EIS Measurement, and (B) Prediction of Current for Arbitrary Potential
Perturbation from Electrochemical Impedance Data
In this report, we take a reverse process of the 2G FT-EIS
to investigate
the correlation between the Tafel plot and EIS, where ac signals of
electrochemical impedance data are used to obtain a chronoamperometric
curve resulting from a voltage step as shown in Scheme B. In addition, as long as the electrochemical
system is constant for small perturbations within a limited potential
region, the voltage step can be replaced with any arbitrary dc signal
to predict an electrochemical current stimulated by a virtual potential.
To prove our concept and find the relationship between EIS and voltammetry
or the Tafel analysis, we first simulate CA to predict a current signal
from electrochemical impedance data by our mathematical model based
on Fourier series and their inverse transform. Then, this model is
applied to find a virtual current response to a perturbation of potential
such as the dirac δ function, which is hard to acquire from
practical experiments. Finally, analysis of Tafel plot is compared
with our prediction from EIS at various dc bias constructing a typical
Tafel plot. Our work demonstrates the successful prediction of an
amperometric signal from EIS and better indicator for characterizing
electrocatalysts instead of the slope of classical Tafel analysis.
Results
and Discussion
Scheme B outlines
the overall process to predict the amperometric curve from electrochemical
impedance. Two independent processes are conducted, and then joined
to generate the current. One is the preparation of arbitrary potential
stimuli in the frequency domain using home-built software called the
virtual frequency function generator. The program creates proper signals
of frequencies by Fourier transforming the desired voltage–time
signals such as a potential-step. As a result of that, we obtain complex
numbers versus frequencies of which both amplitudes and phases comprise
the applied voltage in frequency domain, Vappl(ω). The other process is reconstruction of impedance data
which has been measured by an EIS analyzer. As the experimentally
measured impedance spectra are sampled at nonequal frequency intervals
such as 10 points per decade, they need to be re-sampled at the equal
intervals in order to provide the signal sets of frequencies sufficient
for complete inverse Fourier transform. In the present report, the
frequency interval is set at 10 Hz, and re-sampling is carried out
using a home-built code called the equal frequency interval resampler
composed of sub-routines provided by MATLAB. After those two processes
are done and calculation by Vappl(ω)/Z(ω), we obtain the current in the frequency domain, I(ω). Finally, the current in the time domain, I(t), is calculated by inverse Fourier
transform from summing the cosine waves of each frequency with considering
their magnitudes and phase shifts as written in eq S4. The theory on the prediction of the amperometric curve
from electrochemical impedance data is based on the Fourier series
and its details are described in the Supporting Information.In order to confirm the validity of our
approach, we apply the
scheme above to a chronoamperometric curve simply responding to a
constant potential step. A small potential step of 10 mV described
by the Heaviside function is generated by the virtual frequency function
generator code shown in a black solid line in Figure A. This step signal is Fourier-transformed
to yield complex numbers that are Fourier series represented by the
amplitude and phase of frequency and shown along the frequency in Figure B,C, respectively.
Red dots of Figure A are made by the inverse Fourier transform of the complex numbers.
The successful rebuilding of the potential step clearly proves that
the conversion of the signal between time and frequency domains operates
accurately for user-defined sampling frequencies. The second step
is the acquisition of impedance data as complex numbers with the equal
interval in frequency domain. A frequency sweep in COMSOL is ranged
from 10 Hz to 100 kHz with 10 points/decade. Figure D shows a Nyquist plot for a one-electron
transfer redox couple with k0 = 1 ×
10–4 m/s, diffusion coefficient of both oxidant
and reductant DOx = DRed = D = 1 × 10–10 m2/s, both concentrations of oxidant and reductant COx = CRed = 1 mol/m3, and T = 298 K. Capacitance of the electrode is 20 μF/cm2. The hemisphere in the high frequency region is attributed to the
charge transfer resistance and the capacitance on the working electrode,
and the linear line in the low frequency region is dominated by Warburg
impedance of diffusion, which is in good accordance with the ideal
result of an electrochemical system. In order to provide the signal
sets of frequencies sufficient for complete inverse Fourier transform,
the impedance data need to be re-sampled with a constant, sufficiently
short interval. We use 10 Hz for the data from 10 Hz to 100 kHz using
equal frequency interval resampler coded in MATLAB.
Figure 1
(A) Potential step vs
time signals for CA described by the Heaviside
function (solid line), and rebuilt from its Fourier series (red dot).
Amplitude (B) and phase (C) vs frequency of the potential step after
the process of the virtual frequency function generator. (D) A Nyquist
plot for the one-electron transfer redox couple Ox/Red with k0 = 1 × 10–4 m/s simulated
using COMSOL. Crosshairs and red dots are the results obtained before
and after re-sampling with a 10 Hz interval, respectively.
(A) Potential step vs
time signals for CA described by the Heaviside
function (solid line), and rebuilt from its Fourier series (red dot).
Amplitude (B) and phase (C) vs frequency of the potential step after
the process of the virtual frequency function generator. (D) A Nyquist
plot for the one-electron transfer redox couple Ox/Red with k0 = 1 × 10–4 m/s simulated
using COMSOL. Crosshairs and red dots are the results obtained before
and after re-sampling with a 10 Hz interval, respectively.I(ω), the responding current in the
frequency
domain is obtained as a Fourier series by calculation of Vappl(ω) (in Figure B,C) divided by Z(ω) (Figure D). Then, the Fourier
series of the current signal are processed to inverse Fourier transform
by the eq S4 in Supporting Information. Figure shows curves of
the current response versus time for a potential step of 10 mV obtained
from the above Fourier series (red line) and a theoretical calculation
using known equations[8] (solid line) at
different k0. The theoretically predicted
current decreases rapidly because of the effect of the charging current
decay. Then, it seems to gradually decrease until it reaches the steady
state. This is in good accordance with the previous CA,[2] indicating the validity of our method. The black
dotted line in Figure is the theoretically predicted current from eq S9 with a 10 mV potential step. In the very early region
up to 0.01 s, our method predicts the current to be higher. Nevertheless,
both currents converge into the same magnitude indicating the validity
of our approach with a time restriction. We speculate that the limited
frequency range of EIS prohibits the exact prediction in the transient
time. For example, 100 kHz ac signal cannot catch up with fast electrode
processes including both charging and Faradaic current. However, this
restriction is practically of no effect for CA experiments because
that time region is a mixture of Faradaic and non-Faradaic currents,
so that it is seldom used for electrochemical analysis, especially
for electrocatalytic processes.
Figure 2
Curves of current vs time responding to
a potential step of 10
mV with different standard rate constants. (A) k0 = 1 × 10–4 m/s, (B) k0 = 1 × 10–5 m/s, and (C) k0 = 1 × 10–6 m/s.
Curves of current vs time responding to
a potential step of 10
mV with different standard rate constants. (A) k0 = 1 × 10–4 m/s, (B) k0 = 1 × 10–5 m/s, and (C) k0 = 1 × 10–6 m/s.Our approach can predict electrochemical currents
responding to
various potential waves, not limited to a potential step. A potential
signal most close to the dirac delta function is applied by extending
the potential step signal to a potential pulse with controlled width
because a current response on the dirac delta function is hard to
measure in experiments. First, a relatively longer potential pulse
of 10 ms was applied as shown Figure A. A complex number for the current at a specific frequency
is calculated by the complex number of voltage divided by the complex
number of impedance at the same frequency, whose amplitude is shown
in Figure B. Then,
the Fourier series of the current are processed to predict the amperometric
current as shown in Figure C. The result is very similar to that of double-step CA, which
confirms the validity of our approach. When the width of the potential
pulse decreases to 4 ms (Figure D,E), the responding current rises very high up to
200 A/m2. Finally, when the width of the pulse is extremely
decreased down to 2 ms, frequency analysis of the pulse shows a signal
very similar to the ideal dirac delta function; here, 2 ms is the
sampling time of our home-built code. Figure I shows an extremely high current, which
was predicted in a previous report.[1] These
results explain that an electrochemical experiment with a short potential
pulse may give us information of the electrochemical impedance, but
practically the high current will cause several issues such as range
saturation of the analogue-digital converter, limited resolution in
current, and probable electric damage to the circuit. The oscillation
of current after the short potential pulse may be artifact originated
from the symmetry of our calculation because circuits based on EIS
can generate both anodic and cathodic currents. It is also worth mentioning
that the current response keeps changing even after the short potential
pulse owing to the low frequency components originating from slower
electrochemical processes. Thus, in a sufficient time scale the current
should be recorded to characterize electrochemical behaviors after
a short pulse.
Figure 3
Potential pulses with different widths of (A) 10, (D),
4, and (G)
2 ms, and the amplitudes of the Fourier series for the predicted currents
in (B, E, and H), respectively. The phases are also obtained but not
shown here. Current responses to the potential pulses above are calculated
with the amplitudes and phases and shown in (C, F, and I). k0 = 1 × 10–6 m/s, D = 1 × 10–10 m2/s, COx = CRed = 1 mol/m3.
Figure 4
(A) Liner sweep potential applied and (B) its
voltammogram obtained
by our approach. (C) Nyquist plots of electrochemical impedance with
dc biases (overpotential) of 0 mV (blue), −50 mV (black), −100
mV (green), −150 mV (cyan), and −200 mV (magenta). k0 = 1 × 10–6 m/s, D = 1 × 10–10 m2/s, COx = CRed = 1 mol/m3. (D) Tafel plots converted from the voltammograms obtained
using the impedance data in (C). Colors of the plots are matched to
those of the curves in (C) by the dc biases.
Potential pulses with different widths of (A) 10, (D),
4, and (G)
2 ms, and the amplitudes of the Fourier series for the predicted currents
in (B, E, and H), respectively. The phases are also obtained but not
shown here. Current responses to the potential pulses above are calculated
with the amplitudes and phases and shown in (C, F, and I). k0 = 1 × 10–6 m/s, D = 1 × 10–10 m2/s, COx = CRed = 1 mol/m3.(A) Liner sweep potential applied and (B) its
voltammogram obtained
by our approach. (C) Nyquist plots of electrochemical impedance with
dc biases (overpotential) of 0 mV (blue), −50 mV (black), −100
mV (green), −150 mV (cyan), and −200 mV (magenta). k0 = 1 × 10–6 m/s, D = 1 × 10–10 m2/s, COx = CRed = 1 mol/m3. (D) Tafel plots converted from the voltammograms obtained
using the impedance data in (C). Colors of the plots are matched to
those of the curves in (C) by the dc biases.Both the Tafel plot and EIS have been widely used to evaluate the
catalytic activity of an electrocatalyst but their correlation has
not been studied rigorously. To reveal their relationship, linear
sweep voltammograms (LSVs) are derived from the electrochemical impedance
by the same approach used for the CA above. Figure A is the potential sweep of 1 V/s and Figure B represents the
corresponding LSV predicted through our method. The high currents
above 20 mV and below −20 mV may have originated from the distortion
of EIS data itself because EIS data are only valid with potential
perturbations of small amplitude. In other words, the impedance data
outside of the linearity conditions is not reliable, and we should
not consider the result. The current near the standard reduction potential
seems to be linear because of the very small overpotential. This is
very reasonable because the current from the Butler–Volmer
theory for a small overpotential can be approximated to a linear equation
with the following slope[18]where i0 is the
exchange current and RCT is the charge
transfer resistance. The slope of Figure B is the same as the value calculated by eq . In order to accomplish
a Tafel plot, the currents are supposed to be collected at the large
overpotential region where one of the redox terms of Butler–Volmer
equation is neglected. Here, we encounter a contradiction that the
electrochemical impedance data are reliable for small perturbations
of potential while the Tafel plot is composed of currents at large
overpotentials. To go around the trouble, we find voltammograms using
small perturbations overlaid on large overpotentials. Figure C shows the Nyquist plots calculated
at various dc bias (equivalent to overpotential). The larger the overpotential
is, the smaller Rct is. The same procedure
done for the LSV in (B) is applied to each set of frequency the electrochemical
impedance in (C), and then the results are plotted in (D). The solid
lines and dashed lines are in and out of the linearity conditions
for impedance, respectively. For a clear display of the plots, we
add appropriate constants on the voltammetric curves to make the stitched
voltammograms look continuously. The constructed Tafel plot represents
characteristic of the ideal Tafel plot which is composed of the linear
part at the large overpotential region and the abruptly decreasing
part at the small overpotential region. The slope of the Tafel plot
is found to be around 10.6 which slightly deviate from the theoretical
value, 8.47. The discrepancy probably comes from the interference
by the capacitance current or added arbitrary constant. Such interference
is not rarely faced in electrochemical measurements. To make the signal
of interest free from interference, Vrubel and co-workers fitted impedance
data to an equivalent circuit and extracted the values of components
purely related to the catalytic processes. Instead of direct conversion
of EIS to Tafel analysis, we suggest a modified Tafel analysis to
characterize electrocatalyst based on the following procedure shown
in Scheme . (1) Run
the voltammetry and find the catalytic current in the range of sub
mA/m2 to ensure the sufficient forward chemical reaction.
(2) Measure the EIS at a few selected bias point (more than three)
for EIS. (3) Find Rct from the suitable
equivalent circuit in order to remove the side parameters in voltammetry.
(4) Plot bias potential versus log(1/Rct) to find the slope. Compared with the Tafel analysis, the suggested
model does not require background subtraction of non-Faradaic current
or the iR compensation because the fitting process with an equivalent
circuit eliminates those background signals. In addition, the electroactive
surface area can be inferred from the capacitance, which may make
the judgement for the electrocatalyst fair. Although the process of
fitting may induce some errors in values of components, this modified
Tafel analysis enables the determination of both i0 and α without side effects of non-Faradaic current,
iR drop, and arbitrary selection for the linear range within Tafel
analysis.
Scheme 2
Suggested Characterization of the Electrocatalyst
from the Modified
Tafel Analysis Combined with EIS
Conclusions
In conclusion, inspired by the second generation of FT-EIS, we
investigated the reverse process of the FT-EIS to predict amperometric
responses from electrochemical impedance data upon potential applications
such as a step, a pulse, the dirac delta function, and a linear sweeping
potentials. First, the potential signals for amperometry are generated
and analyzed based on Fourier transform using a home-made code called
Virtual Function Generator. Second, virtual impedance data with an
equal frequency interval are obtained from the experimentally measured
impedance data using another home-built code called the equal frequency
interval resampler. Then, the current at each frequency is calculated
by applying the potential signals onto the re-sampled impedance data,
followed by the inverse Fourier transform to predict the current response.
The current obtained from a potential step demonstrates the validity
of our approach showing the good accordance with theoretical values.
This approach is also applied to carry out a virtual experiment of
CA for impulse potential whose implementation in the real world is
impractical because of the limited resolution in current and time.
Finally, a virtual Tafel plot calculated from electrochemical impedance
spectra demonstrates the correlation between the Tafel plot and the
EIS implying that our new Tafel analysis is the better indicator for
characterizing electrocatalysts.
Experimental Section
EIS data were obtained using COMSOL Multiphysics 5.3 with an electrochemistry
module to simulate the ac response. The diffusion equation in the
simple 1D system was solved with harmonic perturbation. 2 species
of Ox and Red was considered. Because the standard reduction potential
for Ox/Red was assumed 0, dc bias was also 0. For numerical calculation
of CA, MATLAB R2019a with in-house code was employed. Details on simulation
were described in Supporting Information.
Authors: I Morkvenaite-Vilkonciene; P Genys; A Ramanaviciene; A Ramanavicius Journal: Colloids Surf B Biointerfaces Date: 2015-01-10 Impact factor: 5.268