Production of Volatile Species during the Oscillatory Electro-oxidation

Article pubs.acs.org/JPCC

Production of Volatile Species during the Oscillatory Electrooxidation of Small Organic Molecules M. V. F. Delmonde,† M. A. Nascimento,† R. Nagao,† D. A. Cantane,† F. H. B. Lima,† and H. Varela*,†,‡ †

Institute of Chemistry of São Carlos, University of São Paulo P.O. Box 780, 13560-970, São Carlos, São Paulo, Brazil Department of Physical Chemistry, Fritz Haber Institute of the Max Planck Society, Faradayweg 4-6, D-14195 Berlin, Germany

‡

S Supporting Information *

ABSTRACT: The study of complex reaction under oscillatory conditions has been proven to be useful in uncovering features that are hidden under close to equilibrium regime. In particular, for the electro-oxidation of small organic molecules on platinum and platinum-based surfaces, such investigations have provided valuable mechanistic information, otherwise unavailable under nonoscillatory conditions. We present here the dynamics of production of volatile species along the oscillatory electro-oxidation of formic acid, methanol, and ethanol on platinum, as measured by online differential electrochemical mass spectrometry (DEMS). Besides the presentation of previously unreported DEMS results on the oscillatory dynamics of such systems, we introduce the use of multivariate linear regression to compare the estimated total faradaic current with the one comprising the production of volatile species, namely: carbon dioxide for formic acid, carbon dioxide and methylformate for methanol, and carbon dioxide and acetaldehyde for ethanol. The introduced analysis provided the best combination of the DEMS ion currents to represent the total faradaic current, or, equivalently, the maximum possible faradaic contribution of the volatile products for the global current. The mismatch between estimated total current and the one obtained by the best combination of partial currents of volatile products was found to be small for formic acid, 4 and 5 times bigger for ethanol and methanol, respectively, evidencing the increasing role played by partially oxidized, soluble species in each case. These results were discussed in connection with the mechanistic aspects of each system. Moreover, we have defined some descriptors to account for the production of volatile species, and discussed dynamics in terms of sample and populational covariances.

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INTRODUCTION There is vast literature on the space and/or time-dependent reaction rates of electrochemical systems.1−14 As virtually all reactions at the electrified solid/liquid interface can display kinetic instabilities under some conditions, most anodic reactions commonly employed in low-temperature polymer electrolyte membrane (PEM) fuel cells are particularly susceptible to undergo oscillatory dynamics,15−17 and a considerable development have been observed in these systems in recent years. From the applied side, the considerably parameter range autonomously visited during oscillations might result in periodic self-cleaning of adsorbed poisonous species. Paradigmatic examples in this direction are the higher performance reported in a PEM fuel cell fed with H2/CO mixtures exhibited when operated under oscillatory regime.18−23 From the fundamental perspective, recent developments have proved the importance of electrochemical instabilities in mechanistic investigations, especially in terms of in situ IR spectroscopy.24−28 On-line mass spectrometry has also been used to study the formation of volatile species during the electro-oxidation of small organic molecules under oscillatory regime. In particular, the use of differential electrochemical mass spectrometry (DEMS) is a very powerful and versatile tool for mechanistic investigations under nonconventional, oscillatory regime. The seminal work by Anastasijevic et al.29 © 2014 American Chemical Society

reported potential oscillations during the electro-oxidation of formic acid on platinum and the concomitant production of carbon dioxide. The oscillatory electro-oxidation of formaldehyde was investigated by means of in situ IR spectroscopy and on-line DEMS; synchronized signal of the electrode potential, the coverage of adsorbed formate and carbon monoxide, and the production of carbon dioxide were followed.30 Seidel et al.31 studied the oscillatory electrooxidation of formaldehyde under galvanostatic regime on a continuous platinum film and compared the obtained results with that on platinum nanodisks supported onto glassy carbon substrate by means of on-line DEMS. The authors used the production of carbon dioxide to quantify the activity on different surfaces, and discussed the role of mass transport on the further oxidation of partially oxidized formic acid. Based on modeling, numerical simulations, and experiments, we have recently decoupled32,33 the parallel routes of CO2 production during the electro-oxidation of methanol on platinum. Finally, we have also followed the CO2 production during the oscillatory oxidation of carbon monoxide-containing hydrogen in a PEM fuel cell, by means of on-line mass spectrometry (OLMS).34 Received: May 7, 2014 Revised: July 15, 2014 Published: July 25, 2014 17699

dx.doi.org/10.1021/jp5044915 | J. Phys. Chem. C 2014, 118, 17699−17709

The Journal of Physical Chemistry C

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= 44, for carbon dioxide, and 60, for methylformate, were simultaneously recorded at 5.7 Hz. While for ethanol, the m/z = 44, with contribution of fragments of carbon dioxide and acetaldehyde, was concomitantly measured with the fragments m/z = 15 and 29, for acetaldehyde at 1.0 Hz. This small frequency acquisition of 1 Hz was used to minimize the impact of noise on the statistical parameters. For the galvanostatic experiments with ethanol, there is no contribution of methane to the m/z = 15 signal, since the potential oscillates at values above 0.40 V.37,38 These ionic currents were normalized through [CO2]+ mass signal during CO stripping. The on-line temporal resolution of these measurements was smaller than 0.1 s, as calculated by the procedure proposed by Wolter and Heitbaum;36 further details are as in ref 32.

The present contribution represents one step further on our recent efforts to investigate mechanistic aspects of the electrooxidation of small organic molecules, particularly simultaneously following the time evolution of volatile species and the oscillatory electrochemical variable. We introduce herein the use of multivariate linear regression (MLR) to estimate the contribution to the total faradaic current of reaction steps that results in the production of volatile species detected by on-line DEMS. The analysis was applied to the oscillatory electrooxidation of formic acid, methanol, and ethanol on platinum, three systems with rather disparate mechanisms. After the Experimental Section, we present details on the modeling and methods used; results are divided in four parts: the experimental results and the comprehensive statistical analysis for the electro-oxidation of each studied molecule, followed by a final discussion on the mechanistic aspects; the obtained conclusions and a few perspectives are then presented.

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MODELING AND METHODS From the charge conservation of the electrochemical circuit, it can be deduced:

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EXPERIMENTAL SECTION The DEMS setup used in our experiments consists of a Pfeiffer Vacuum QMA 200 quadrupole mass spectrometer and two differentially pumping chambers.35 The electrochemical cell was constructed following previously published principles.36 The electrochemical variables were recorded simultaneously with the mass intensity, for selected values of m/z (mass/charge) ionic signals. A high area platinum electrode and a reversible hydrogen electrode served as counter and reference electrodes, respectively. The electrochemical system was controlled by the potentio/galvanostat PGSTAT 30 by Autolab. For the electrooxidation of formic acid and methanol, the working electrode was a platinum-sputtered (thickness around 50 nm) Teflon membrane (Gore-Tex PTFE − thickness of 50 μm and pore size of 0.02 μm). Whereas for ethanol, to ensure a good signal/ noise ratio, the working electrode was prepared with an aqueous suspension consisting of 4.30 g of H2O, 0.0128 g of platinum black, and 65 μL of Nafion 6.0 wt %. After ultrasonic homogenization, 60 μL of this suspension was pipetted at the center of a gold sputtering Teflon membrane with identical dimensions previously mentioned for the platinum electrode. Before use, the electrode was kept in an oven at 60 °C for 10 min in order to evaporate the residual water. The electrode area was evaluated by means of CO stripping. The obtained values for the real areas were estimated as 4.3 ± 0.3 cm2, 3.5 ± 0.3 cm2, and 15.5 ± 0.7 cm2, for the electrodes used in the electrooxidation of formic acid, methanol, and ethanol, respectively. The dispersion and solutions were prepared with high purity water (Milli-Q, 18.2 MΩ cm), H2SO4 (Merck, 98%), HCOOH (Sigma-Aldrich, ≥ 98%), H3COH (J.T. Baker, 99.9%), CH3CH2OH (Merck, 99.8%). The cell temperature was maintained at 20.0 ± 0.1 °C with the aid of a Cole-Parmer Polystat temperature controller. Prior to each galvanostatic experiment, the systems with formic acid, methanol, and ethanol were cycled ten times at 0.10 V s−1, in a potential window between 0.15 and 1.3 V, 0.05 and 1.5 V, and 0.15 and 1.2 V, respectively. Thereafter, a current step to the desired value was applied. At the beginning and at the end of each measurement, the electrochemical systems were left at open circuit potential for sufficiently time to ensure a well-defined baseline (set to zero detection ion current) for mass normalization criterion. The ion current for m/z = 44 assigned to the formation of carbon dioxide was followed during the formic acid electrooxidation with a sampling rate of 4.0 Hz. For methanol, the m/z

jT = Cdl

dϕ + jF dt

(1)

where the total current density flowing through the circuit, jT, is given as the nonfaradaic and the faradic terms, and dφ/dt, jF, and Cdl are the rate of change of the electrode potential, the faradaic current density and the double-layer capacitance, respectively. Under galvanostatic control, the term dφ/dt can be obtained as the time derivative of the measured electrode potential U, so that dU 1 1 = j − j dt Cdl T Cdl F

(2)

In a galvanostatic experiment, the applied current, jT, is kept constant, and, assuming the double-layer capacitance remains constant, vide inf ra, the left-hand side (lhs) term can be simply described as proportional to −jF. In complex reactions, such as the electro-oxidation of small organic molecules, the faradaic current can, in its turn, be given as the sum of contributions from all elementary steps that involve electron transfer. The use of on-line DEMS allows at following the reaction steps that results in the formation of volatile species. The measured ionic currents, ji, contribute thus to the total faradaic current. Therefore, we can use the accessible ji’s to infer on the contribution of volatile species to the total faradaic current. In order to do so, we estimate the rate of change of the potential, now represented as dUp/dt − the predicted derivative, as a function of the ion current intensities, dUp dt

n

=

∑ (αi + βi ji ) i=1

(3)

where αi and βi are regression or unknown parameters for each contribution i. Equation 3 can be finally written as

dUp dt

n

=A+

∑ βi ji i=1

(4)

39

MLR is a statistical methodology for predicting values of one or more dependent variables (responses) from a collection of independent variables (predictors). For a single response (Y), its mathematical relationship with the predictors (Z) can be expressed as Y = A + BZ + ε, where A and B are regression parameters, and ε is the error. We used MLR to predict the response dUp/dt in terms of the ji’s in order to match the 17700



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experimental response dU/dt. Comparing eqs 2 and 4, it becomes apparent that βi is negative when associated with an oxidation, and positive for a reduction reaction current. Therefore, as we discuss here only oxidation reactions, we have implicitly included the constraint βi < 0 to estimate the term dUp/dt. As further clarified below, the main idea is to compare the global faradaic current, approximated by −dU/dt, eq 2, with that associated with the production of volatile products, namely, the predicted term dUp/dt. In this way, the MLR analysis result in the best combination of the DEMS ion currents to represent the total faradaic current. In other words, we have computed the maximum possible faradaic contribution of the volatile products for the global current. The residue was defined at each time as ε(t ) =

dUp dU − dt dt

(5)

As eq 5 suggests, the residue must have the same characteristics of the first time derivate of the electrode potential, and consists of positive and negative values distributed around zero. In anticipation of the next section, the residue includes information about species that are not detected using on-line DEMS, as partially oxidized soluble products with low volatilities and also steps such as dissociative surface reactions. For a comparative quantitative analysis, previous to the MLR, dU/dt, U, j, and the time were normalized to extend from 0 to 1.

Figure 1. Temporal evolution (a) of the electrode potential, and (b) of the ion current for the fragment m/z = 44, jm/z=44, during the electrooxidation of formic acid at j = 0.44 mA cm−2. [HCOOH] = 1.0 mol L−1, [H2SO4] = 0.5 mol L−1 and T = 20 °C. For remaining conditions, see the Experimental Section.

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RESULTS AND DISCUSSION Formic Acid. Concomitantly with the autonomous oscillations of the electrode potential during the electrooxidation of formic acid, it was followed, using on-line DEMS, the ion current m/z = 44 for the production of carbon dioxide, the only detectable volatile product in this system. Figure S1 in the Supporting Information presents the initial voltammetric characterization in terms of the reaction current and of the production of carbon dioxide. Figure 1 shows typical timeseries for the (a) electrode potential and (b) carbon dioxide production. Oscillations in the electrode potential (Figure 1a), are generally similar to the ones previously found on polycrystalline platinum,40−42 and some mechanistic aspects have been reasonably explained.26,43 The time evolution of the production of carbon dioxide (Figure 1b), shows mainly a rather constant profile abruptly interrupted by spikes during the steep variations in the electrode potential. As discussed in the following, this profile is in complete agreement with the total faradaic current, as estimated in eq 2. Following the MLR analysis presented in the previous section, the rate of change of the electrode potential, dUp/dt, was estimated as a function of the ion current m/z = 44, and eq 4 reads dUp dt

= A + β1jm / z = 44

Figure 2. Normalized time-series for formic acid: (a) the experimental rate of change of the potential at j = 0.44 mA cm−2, dU/dt (black line), accompanied by the predict rate of change of the potential, dUp/dt (blue line); and (b) the residual rate of change of the potential, ε. Data in panel a taken from Figure 1 (see text for details).

production of CO2,44,45 which is captured by jm/z=44. This fact is also seen in good agreement between the terms −dU/dt and jm/z=44, and also between the residue, ε, and dU/dt. In order to further compare the estimated total faradaic current with the one due to the production of volatile species, we compute the covariance between different pair of variables. As a statistical parameter, the covariance indicates how two variables change together with respect to its respective mean values, and the general aspect to be considered in these plots is the signal of the covariance, as it reflects the propensity in the linear relationship between a pair of variables. Positive covariance implies that the variables change, i.e., increase or decrease, in the same direction. Accordingly, when the covariance is negative, the variables change in opposite directions.

(6)

and the regression parameters were A = +0.8291 and β1 = −0.5528. Figure 2 shows in panel a that the experimental, dU/dt (black line), and the predicted, dUp/dt (blue line), curves are very similar. As further clarified when comparing this results with that for methanol and ethanol discussed in the following, this similarity results from the fact that all reaction steps involved in the electro-oxidation of formic acid results in the 17701



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formed by the nucleophilic attack of a methanol molecule to an adsorbed “HCO” intermediate specie46 (see below). The term dUp/dt was estimated with the ion currents m/z = 44 and 60,

Figure 3 shows the normalized time-series for the experimental rate of change of the potential, dU/dt, and the

dUp dt

= A + β1jm / z = 44 + β2jm / z = 60

(7)

The obtained parameters in this case were A = +0.9296, β1 = −0.6030, and β2 = −1 × 10−6. The rather small value for β2 corresponds to the tolerance used in the regression, and it is very unlikely that it reflects the actual contribution of the production of methylformate, when compared to the value for β1 for CO2. The MLR analysis assures we compute the best combination of individual currents that would match the estimated total faradaic current. As a consequence, the estimated faradaic contribution represents the maximum possible contribution. In this way, any change in these optimized parameters would result in a worse match between the estimated faradaic contributions. Additional constraints could be used to relate the production of different volatile species using the number of electrons associated with each step (see below). This is beyond the scope of this article but might be useful in future analyzes, in particular when investigating the effect of experimental parameters for a given molecule. Results in Figure 4a show that, differently from that for formic acid, the profiles of the dU/dt and dUp/dt for methanol

Figure 3. Statistical analysis of the oscillatory time series for the electro-oxidation of formic acid: (a) the experimental rate of change of the potential, dU/dt; (b) the populational covariance between ε and dU/dt, Cov(ε, dU/dt); (c) the ion current m/z = 44, jm/z=44; and (d) the populational covariance between ε and jm/z=44, Cov(ε, jm/z=44). Data in panels a and c taken from Figure 1, see text for details.

ion current for m/z = 44, jm/z=44, and their respective populational covariances with respect to ε, Cov(ε, dU/dt), and Cov(ε, jm/z=44). Recalling eq 5, ε has in principle the same characteristics than dU/dt and deviations from the linear relationship between ε and dU/dt, results from the term dUp/dt, so that the covariance Cov(ε, dU/dt) is expected to be positive when deviating from 0. For the case of formic acid, ε is expected to change in the opposite direction than jm/z=44, c.f., eqs 4 and 5, therefore, Cov(ε, j) is projected to be negative when deviating from 0. When more than one individual DEMS currents are available the situation is more complicated, see below. Results in Figure 3 corroborate this aspect for both Cov(ε, dU/dt) and Cov(ε, jm/z=44); and, except at the step transitions in U, the covariances remains zero. We have also computed the sample covariance as a mean to represent the overall covariance displayed as a function of time. In this case, the sample covariance between the ε and dU/dt was +8 × 10−4 and between the ε and jm/z=44, −1 × 10−4. As already mentioned, the signs of the sample covariances agree with the expected relationships between the two pairs of variables. In the following we proceed with the analysis for methanol and then for ethanol. Further mechanistic aspects are discussed in a latter section for all three investigated systems. Methanol. The on-line spectrometric investigation of the oscillatory electro-oxidation of methanol on platinum has been recently reported by our group. 32,33 For the original voltammetric and time-series data, the reader is referred to ref 32; in the following, we proceed with the MLR analysis to the time-series. In addition to the mass fragment m/z = 44 for carbon dioxide, also analyzed in the case of formic acid, we have also followed the m/z = 60 fragment, which corresponds to methylformate. This partially oxidized species is presumably

Figure 4. Normalized time-series for methanol: (a) the experimental rate of change of the potential at j = 0.35 mA cm−2, dU/dt (black line), accompanied by the predict rate of change of the potential, dUp/dt (blue line); and (b) the residual rate of change of the potential, ε (red line). [H3COH] = 2.0 mol L−1, [H2SO4] = 0.5 mol L−1, and T = 20 °C. Raw data published in ref 32.

do not fit so well. Furthermore, the profile of the residue ε in Figure 4b does not follow that of the dU/dt, neither the profiles of carbon dioxide and methylformate (Figures 5c and 5e, respectively). Comparing Figures 2b and 4b, it becomes clear that the residue is considerably more pronounced for the case of methanol. Moreover, it is possible to detect two types of contributions to the residue: one due to the steep change in U, and is thus localized around this region, and another that is discernible also in the regions where U evolves smoothly in time. The first can be caused by changes in the electrode capacitance, which follows abrupt changes in U, and thus primarily affects the estimated total faradaic current, approximated by −dU/dt (c.f. eq 2). When ε is also different from zero in regions of smooth U, one can expect that the mismatch is 17702



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observed in the production of carbon dioxide (c.f. features i−iii in Figure 5c), was uncovered by Nagao et al.32,33 by means of experiments, modeling and simulations. In short, the authors assigned peaks i to the electro-oxidation of adsorbed carbon monoxide, and peaks ii and iii to the, non-CO, direct pathway. The analysis of the covariance between ε and the individual currents ji is more complicated than in the case of formic acid, where only jm/z=44 was available. As already discussed, one can expect that ε changes in the opposite direction than ji, but this is strictly valid if only one current is considered; if more than one current is analyzed, it is possible that a satisfactory adjustment is found by a combination of apparently unexpected trends. In other words, it is possible that a given decrease in one faradaic contribution can be compensated by a greater increase in another to match an overall increase in the total faradaic current (c.f. eqs 4 and 5). Nevertheless, the sample covariance between ε and ji is expected to be negative, as it reflects the general trend. In the case of methanol, the sample covariance between ε and jm/z=44 results in a small, but positive value: + 6 × 10−5. The undoubtedly more pronounced discrepancy in the case of methylformate is evidenced by the wide regions where Cov(ε, jm/z=60) is positive. This is in line with the small portion of this pathway estimated in the MLR. Again, a better composition between jm/z=44 and jm/z=60 could account for this discrepancy but would necessarily result in a worse overall adjustment, and this is what can be done without including any additional constraints. The sample covariance between ε and jm/z=60 was found to amount to +9 × 10−3. Ethanol. Figure 6 shows the time evolution of the electrode potential and for the mass fragments for m/z = 44, 15, and 29, simultaneously registered during the galvanostatic electrooxidation of ethanol. For the electro-oxidation of ethanol, the dUp/dt term was thus estimated with the ion currents for three registered m/z ratios

Figure 5. Statistical analysis of the oscillatory time series for the electro-oxidation of methanol: (a) the experimental rate of change of the potential, dU/dt; (b) the populational covariance between ε and dU/dt, Cov(ε, dU/dt); (c) the ion current for m/z = 44, jm/z=44; (d) the populational covariance between ε and jm/z=44, Cov(ε, jm/z=44); (e) the ion current for m/z = 60, jm/z=60; and (f) the populational covariance between ε and jm/z=60, Cov(ε, jm/z=60). Raw data published in ref 32.

primarily caused by the inaccuracy of dUp/dt to represent dU/ dt. As clearly seen in Figures 2 and 4, the residue for methanol is different from zero everywhere, whereas for formic acid, the discrepancies are almost completely confined in the regions where U changes abruptly. This comparison first reinforces the good agreement between the faradaic current and the one for the production of CO2, in the case of formic acid, but also indicates that the currents associated with the production of CO2 and methylformate poorly represent the total faradaic contribution in the case of methanol, and thus partially oxidized, nonvolatile species are expected to play a significant role. As the estimated faradaic contribution for the production of volatile species represents the maximum possible one, the importance of current carriers associated with the production of partially oxidized solution species is rather clear for methanol. This aspect will be further discussed below. Figure 5 shows the normalized experimental time-series for dU/dt, the ion currents m/z = 44, jm/z=44, and m/z = 60, jm/z=60, and their respective covariances with respect to ε. In Figure 5b, despite the small variations around zero, Cov(ε, dU/dt), the slight negative deviations shortly before the small positive peak attests the worst adjust when compared to that for formic acid (c.f. Figure 3b). The sample covariance between ε and dU/dt was +0.014, and the positive sign is in agreement with the expected tendency, as discussed in Figure 3b. This is clearly also seen, but in terms of negative deviations at this time, for the case of carbon dioxide (Figure 5d). The multipeaked structure

Figure 6. Temporal evolution (a) of the electrode potential, and of the ion currents for the fragments (b) m/z = 44, jm/z=44, (c) m/z = 15, jm/z=15, and (d) m/z = 29, jm/z=29, during the electro-oxidation of ethanol at j = 0.043 mA cm−2. [CH3CH2OH] = 1 mol L−1, [H2SO4] = 0.5 mol L−1, and T = 20 °C. For remaining conditions, see the Experimental Section. 17703


The Journal of Physical Chemistry C dUp dt

= A + β1jm / z = 44 + β2jm / z = 15 + β3jm / z = 29

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Mechanistic Aspects. In the introduced approach, we have essentially compared the global faradaic current, approximated by −dU/dt (c.f. eq 2), with that associated with the production of volatile products, namely, the predicted term dUp/dt. During the electro-oxidation of small organic molecules, the overall reaction current consists of contributions from steps such as dissociative adsorption and the formation of soluble byproducts, besides the production of volatile species. To avoid byproducts and thus favor the complete oxidation to carbon dioxide at low overpotentials is the main target in applications such as fuel cells. Therefore, an important aspect to be explored in the present analysis is the quantification of the overall portion of the faradaic current due to the volatile products, or at least to the ones measured by on-line DEMS. In the discussion of the time-dependent residue ε, the regions of the time-series where the production of volatile species represents the faradaic current became clear. In the following, we compare the relative production of gaseous species for the three systems investigated and discuss the results in connection with some mechanistic aspects for each system. By doing so, we infer on the faradaic contribution of steps that do not result in the production of volatile species. In order to quantify the relative magnitude of the complementary faradaic contribution, not captured by the DEMS signal(s), we define the total residue per oscillatory cycle, εc, as

(8)

The MLR results in the following parameters: A = +0.9799, β1 = −0.1256, β2 = −0.0754, and β3 = −1 × 10−6. As it was described in the Experimental Section, for the case of ethanol, the fragment for m/z = 44 incorporates contributions of carbon dioxide and acetaldehyde, while the ones for m/z = 15 and 29 are attributed to the latter specie. There are few sporadic reports on the oscillatory kinetics during ethanol electro-oxidation,47−49 and no mechanistic discussion regarding the oscillations has been provided so far. Unlike the cases of formic acid and methanol, the individual time-series of the volatile species are somewhat similar to that of the electrode potential. Comparing the individual ji timeseries, the apparent steeper increase for the m/z = 44 profile after it reaches its minimum can be thought of as due to the contribution of carbon dioxide, once the fragments for m/z = 15 and 29 do not carry contributions of CO2. In fact, the coincidence among the three time-series registered with DEMS and the small feature attributed to CO2 at m/z = 44 strongly suggests that the production of acetaldehyde corresponds to most of the faradaic current of the volatile species. Figure 7 shows the (a) comparison between terms dU/dt and dUp/dt, and (b) the corresponding time-series of the

εc =

p t

∫0

t

| ε(t )| d t =

p t

∫0

t

⎛ dU dUp ⎞ − ⎜ ⎟ dt dt ⎠ ⎝ dt

(9)

where p is the oscillation period, and t is the duration of the part of the time-series studied. The module in ε(t) indicates that positive and negative residues in the time-dependent curve are simply summed up, so that the overall deviation is represented by a number. In most cases, we used about four cycles to estimate εc, i.e., t/p ∼ 4. The obtained values for εc amounts to 0.004, 0.020, and 0.016, for formic acid, methanol, and ethanol, respectively. If the absolute values of εc are not physically meaningful, comparison among them can be discussed in the light of some general mechanistic aspects. As already anticipated, the smaller value found for formic acid is not a surprise, as all reaction steps that involve electron transfer result in the formation of CO2. When compared to this base-system, the total residue per cycle for methanol and ethanol were 5 and 4 times larger, respectively. As an additional descriptor to quantify the maximum faradaic current attributable to the production of volatile species, one can divide the absolute area of the curve ε(t) versus t by the absolute area of the dU/dt curve. The resulting term would inform on the percentage of dU/dt that is not captured by the MLR adjust. The obtained values were 2.3%, 15%, and 7.8%, for formic acid, methanol, and ethanol, respectively. The presented results can be discussed in terms of Figure 9, which shows the simplified schemes for the electro-oxidation of (a) formic acid, (b) methanol, and (c) ethanol. Emphasis is put on the electrons involved in each reaction and on the assignment of volatile species detected by DEMS (in blue) and partially oxidized soluble species (in red). Note that the arrows are not aimed to represent elementary steps and that species such protons, water molecules and free surface sites, are omitted for the sake of clarity. Furthermore, the stoichiometry is also neglected in this scheme.

Figure 7. Normalized time-series for ethanol: (a) the experimental rate of change of the potential at j = 0.043 mA cm−2, dU/dt (black line), accompanied by the predict rate of change of the potential, dUp/dt (blue line); and (b) the residual rate of change of the potential, ε. [CH3CH2OH] = 1.0 mol L−1, [H2SO4] = 0.5 mol L−1, and T = 20 °C. Data in panel a taken from Figure 6; see text for details.

residue ε. As in the case of formic acid (Figure 2b), and unlike that for methanol (Figure 4b), it is clear in Figure 7(b) that appreciable deviations from zero in ε are confined to the neighborhood of abrupt changes in dU/dt. As already discussed, this fact indicates a better representation of the faradaic current as a function of the volatile products for ethanol with respect to methanol. The normalized experimental time-series for dU/dt, and the ion currents for m/z = 44, 15, and 29, together with their respective populational covariances with respect to ε are presented in Figure 8. The sample covariances observed for ethanol follow comparable trend to that found for methanol, i.e., a positive, and expected, value between ε and dU/dt (+ 0.021), but positive values between the other pairs: ε and jm/z=44 (+ 9 × 10−4), ε and jm/z=15 (+ 4 × 10−4), ε and jm/z=29 (+ 9 × 10−3). 17704



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Figure 8. Statistical analysis of the oscillatory time series for the electro-oxidation of ethanol: (a) the experimental rate of change of the potential, dU/dt; (b) the populational covariance between ε and dU/dt, Cov(ε, dU/dt); (c) the ion current m/z 44, jm/z=44; (d) the populational covariance between ε and jm/z=44, Cov(ε, jm/z=44); (e) the ion current m/z 15, jm/z=15; (f) the populational covariance between ε and jm/z=15, Cov(ε, jm/z=15); (g) the ion current m/z = 29, jm/z=29; and (h) the populational covariance between ε and jm/z=29, Cov(ε, jm/z=29). Data in panels a, c, e, and g extracted from Figure 6; see text for details.

Figure 9. Simplified reaction scheme of the electro-oxidation of (a) formic acid, (b) methanol, and (c) ethanol on platinum. Species in blue are the ones followed by DEMS, and those in red are the nonvolatile ones.

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electron) oxidation.38,71−77 The term x (= 1, 2, or 3) denotes the number of H atoms in the adsorbed residue (CHx)ad, and the dashed arrow represents the possible further oxidation of CH3CHO to CO2. As it was described in the Experimental Section, the fragment for m/z = 44 incorporates contributions of carbon dioxide and acetaldehyde, while the ones for m/z = 15 and 29 are attributed to the latter specie. Since all time-series were normalized and the MLR analysis results in the best combination of the currents of the volatile products to represent the total faradaic current, there is no need to extract individual m/z signals as commonly done. This observation can be of course extrapolated to any m/z signal that subsumes different contributions. Following the reasoning used for methanol, the electrooxidation of 3 mols of ethanol to produce 1 mol of CH3COOH, CH3CHO, and of CO2, the ratio between the faradaic current for the gaseous species and the total current, would be 7/9. In fact, unlike the situation of methanol, at high concentration of ethanol, it has been shown that the CO2 production during the electro-oxidation of the latter is very small, and most of the reaction current arises from the oxidation of ethanol to acetaldehyde.74,77,78 The apparent disagreement detected in the time-evolution of the residue (c.f. Figure 7b) might indicate the role of nonvolatile, acetic acid formed under oscillatory regime. Further investigations to clarify this point are currently in progress. Comparing the portion of the total current that is not captured by the best combination of the currents for all volatile species, the theoretical values of 3/8 and 2/9 are obtained for methanol and ethanol, respectively. Despite all aspects previously mentioned in this respect, these values are in agreement with the trend found in the two descriptors discussed above. There are reports of rather sophisticated procedures to quantify the production of different species based on DEMS results.77−80 Herein we determine the maximum possible contribution of the volatile species, by means of the best combination of the ion currents. On the other hand, the introduced approach does not require any specific knowledge of calibration constants and specific mechanistic assumptions. The method was tested in the investigation of three oscillatory reactions and were able to order the contribution of volatile products to the total oxidation in the sequence formic acid > ethanol > methanol. Finally, it is noteworthy that there is apparently no obvious conclusions to be drawn when comparing the individual time-series for ion currents. This was actually our initial motivation to undergo the analysis that resulted in the proposed approach. The application of MLR to estimate the maximum contribution of the relative production of volatile species can be classified as a successful strategy to reach this purpose. Following this initial report, we are planning to use this approach to data under different conditions, namely, under potentiostatic control mode, in which the faradaic current is directly measured.

According to this scheme (Figure 9a), formic acid follows the triple pathway,44,50−52,45,42,53 and the two electrons involved result in the formation of carbon dioxide, which is measured on line by DEMS and is used to estimate the faradaic current. Given the good correspondence between the current estimated for the CO2 production and the total faradaic current, this simplified scheme seems representative of the actual situation observed during the oscillations. This observation further corroborates the role of the oscillatory electro-oxidation of formic acid as our base system and validates the introduced approach. Despite the apparent similarity between the mechanisms for methanol and acid formic, there are experimental proofs of the production of formaldehyde, formic acid, and methylformate during the electro-oxidation of the first.54,55 Figure 9b shows the schematic mechanism for the case of methanol. This scheme is based on the current literature46,56−63,54,64−66 and include the production of gaseous species, which are followed by DEMS, viz., HCOOCH3 and CO2, and of non-detected ones, HCHO and HCOOH, that diffuses to the solution bulk. Readsorption and further oxidation of HCHO and HCOOH are possible but are not considered in this simplified scheme. In addition, methylformate could be formed via the ester formation of methanol with formic acid formed, e.g., in competitive reaction of HCO with water. The complete electro-oxidation of methanol to carbon dioxide involves the transference of six electrons. By comparing the number of electrons involved in each step, as illustrated in Figure 9(b), it is possible to infer on the relative weight of all faradaic contributions. Independently of the actual production of each species, it is seen that the production of formic acid and formaldehyde proceed via a four- and two-electron pathway, respectively. The route to methylformate, also measured by DEMS, follows a four-electron route. For the sake of comparison, if the electro-oxidation of 4 mols of methanol would produce 1 mol of HCHO, HCOOH, HCOOCH3, and of CO2, the current measured by the volatile species, i.e., HCOOCH3 and CO2, would correspond to 5/8 of the actual faradaic current. The suggested considerable contribution of nonvolatile species, is reflected in the estimated εc (5 times that of formic acid) and also supported by independent experiments in the literature.46,54,60,62−64 Once the MLR evaluated the maximum possible contribution of the current for the volatile species and all series were normalized, the actual ratio would not affect the adjustment. This would correspond to a stationary, nonoscillatory, current−time response. However, under oscillatory regime, the relative production of different species continuously varies in time as the electrode potential visits different regions. Oscillations in the registered time-series reflect the self-organized time-evolution of the coverage of different adsorbates, therefore, as the changes in the electrode potential induces ad/desorption, oxidation, etc., the production of (partially) oxidized species. This is more transparent for methanol,32,33 but also for ethanol (c.f. Figure 8). This makes the systems indisputably more complex, but also opens the perspective of estimate the contribution of groups of reaction pathways, as proven here in the introduced approach. The occurrence of oscillatory instabilities can thus bring about new insights to the study of electrocatalytic reactions, as it has been claimed in our recent research in this topic.32,33,43,67−70 The electro-oxidation of ethanol is schematically depicted in Figure 9c, and it comprises mainly the production of solution, CH3COOH, and CH3CHO, besides CO2 in the full (12-

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CONCLUSIONS In the present contribution, we have investigated the oscillatory electro-oxidation of formic acid, methanol, and ethanol on platinum, and the production of volatile species was followed by means of on-line DEMS. We introduced the use of MLR to compare the estimated total faradaic current with the one comprising the production of volatile species. In this way, the faradaic current estimated by the first derivative of the time evolution of the electrode potential was compared to the 17706


The Journal of Physical Chemistry C current for production of volatile species: carbon dioxide for formic acid, carbon dioxide and methylformate for methanol, and carbon dioxide and acetaldehyde for ethanol. As computed, the faradaic current estimated with the DEMS ionic currents reflects the maximum possible current for all volatile products in each case. The comparison between the time-series estimated for the total faradaic current and for the one due to the gaseous products allowed us to infer the role of volatile products along the time-series. This analysis was performed with the aid of a time-dependent residue, obtained as the difference between the total and partial currents. It was possible to state, for instance, where in the potential time-trace the production of partially oxidized, soluble products, plays a more significant role. In addition, we have also discussed the correlation between pairs of variables, by means of sample and populational covariances. In order to compare the contribution of the relative production of volatile species in the three oscillatory systems investigated, we defined the total residue per oscillatory cycle, εc. As defined, this descriptor accounts for the mismatch between estimated total current and the one obtained by the best combination of partial currents of volatile products. When compared to that for formic acid, our base system, the obtained values for εc were 5 and 4 times bigger for methanol and ethanol, respectively. These values were discussed in connection with the reaction mechanism for the three systems, and it became clear that, despite the assumptions done in our method, the relative production of volatile species under oscillatory regime is in agreement with the expected faradaic contributions of partially oxidized, nonvolatile species. More important than the absolute values, the maximum contribution of volatile products increases in the sequence methanol < ethanol < formic acid, which is in agreement with independent, semiquantitative results, previously reported for experiments under conventional, nonoscillatory regime. In summary, we have presented the dynamics of production of volatile species along the oscillatory electro-oxidation of formic acid, methanol, and ethanol on platinum. Besides the presentation of previously unreported DEMS results on the oscillatory dynamics of such systems, we introduced a method to estimate the maximum faradaic contribution of the volatile species. The developed methodology is applicable to other systems and present an additional step toward our recent efforts to take advantage of the self-organized surface dynamics to reveal relevant mechanistic information on the kinetics of electrocatalytic systems.

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ACKNOWLEDGMENTS

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REFERENCES

M.V.F.D., F.H.B.L., and H.V. acknowledge Conselho Nacional ́ de Desenvolvimento Cientifico e Tecnológico (CNPq) for financial support (Grants: #160511/2011-9, #306213/2013-3, #477153/2013-5, #306151/2010-3, and #304458/2013-9). R.N., D.A.C., F.H.B.L., and H.V. acknowledge São Paulo Research Foundation (FAPESP) for financial support (Grants #2009/11073-3, #2009/00153-6, #2009/07629-6, #2011/ 10982-0, #2012/24368-4, and #2012/24152-1). H.V. acknowledges Dr. Markus Eiswirth (FHI) for fruitful discussions.

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ASSOCIATED CONTENT

* Supporting Information S

Voltammetric profiles and ion currents for the electro-oxidation of formic acid and ethanol, and the application of the proposed method to numerically obtained data. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected] (H.V.). Notes

The authors declare no competing financial interest. 17707



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Production of Volatile Species during the Oscillatory Electro-oxidation

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