Atomic emission spectroelectrochemistry applied to dealloying phenomena: I. The formation and dissolution of residual copper films on stainless steel

Electrochimica Acta 54 (2009) 5163–5170

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Atomic emission spectroelectrochemistry applied to dealloying phenomena: I. The formation and dissolution of residual copper films on stainless steel K. Ogle ∗ , J. Baeyens, J. Swiatowska, P. Volovitch Laboratoire de Physico-Chimie des Surfaces, CNRS-ENSCP (UMR7045), Ecole Nationale Supérieure de Chimie de Paris, 11 rue Pierre et Marie Curie, 75005 Paris, France

a r t i c l e

i n f o

Article history: Received 3 November 2008 Received in revised form 20 December 2008 Accepted 7 January 2009 Available online 21 January 2009 Keywords: Stainless steel Copper Selective dissolution Polarization ICP-OES

a b s t r a c t The rates of elemental dissolution were measured for a 304 stainless steel containing 0.19% Cu in real time during linear sweep voltammetry experiments using the atomic emission spectroelectrochemistry (AESEC) method. The results demonstrate that Fe, Cr, Ni, Mn, and Mo dissolve simultaneously leaving a residual copper film that inhibits the steel dissolution. The formation and dissolution of the copper film leads to the appearance of two peaks in the anodic dissolution transient, one due to inhibition of steel by residual copper and the other due to the formation of the passive film. The addition of NaCl to the electrolyte results in a marked increase in the intensity of the second dissolution peak, while hardly affecting the first peak. This is interpreted in terms of the lowering of copper dissolution potential by chloride ions due to the stabilization of CuCl2 − . A simple phenomenological kinetic model is used to simulate the variation of dissolution rate with potential. © 2009 Published by Elsevier Ltd.

1. Introduction The surface properties of alloys are often determined by component elements present only in low concentration. This occurs when selective dissolution of the less noble elements leaves a residual film of the more noble elements on the surface of the alloy. The mechanism of selective dissolution is poorly understood but usually is thought to involve either simultaneous dissolution of all elements followed by redeposition of the more noble elements, a surface diffusion/structural rearrangement mechanism, or a percolation model. These mechanisms have been recently reviewed [1]. Considerable research has been devoted to the selective dissolution of binary alloys either from the perspective of corrosion [2–13] or as a means of preparing porous metals [14], for example as catalyst supports [15]. There have been recent attempts to model the phenomenon [16]. Very little is known about the selective dissolution of alloys of several elements such as stainless steel despite the technical importance of these materials and the important role selective dissolution plays in determining surface properties. One of the major difficulties is experimental: a stainless steel alloy contains many elements often distributed over several phases greatly complicating the interpretation of electrochemical data. Elements that are present in concentrations below 5% will make a negligible contribution to the faradaic current during an electrochemical experiment or to

∗ Corresponding author. Tel.: +33 1 47 27 26 40. E-mail address: [email protected] (K. Ogle). 0013-4686/$ – see front matter © 2009 Published by Elsevier Ltd. doi:10.1016/j.electacta.2009.01.037

mass loss during a corrosion experiment. The use of conventional electrochemical technology to measure elemental dissolution rates (ring – disk, jet flow cell) is feasible but the large number of elements complicates the use of methods that depend upon secondary electrochemical detection. In previous work [17], we reported the development of a novel spectroelectrochemical technique (AESEC, atomic emission spectroelectrochemistry) based on the use of an inductively coupled plasma optical emission spectrometer (ICP-OES) placed downstream from an electrochemical flow cell. In the original publication, the AESEC technique was used to monitor the elementary dissolution rates of the components of a 304 stainless steel as a demonstration of the AESEC method. Subsequent publications involved application of the method to the selective dissolution of Fe–Cr alloys [18], Zn–Al alloys [19], the alkaline dissolution of conversion coatings [20–22], and, coupled with the quartz crystal microbalance, the study of dissolution-precipitation reactions during zinc phosphating [23], chromating [24]; alkaline degreasing [25], and the effect of complexing agents on the alkaline dissolution of Zn [26]. Other groups have used this method to investigate the effect of organic complexing agents on the dissolution of Al [27]. The ICP-OES method is particularly well adapted to kinetic measurements of leaching and dealloying as it offers the possibility of simultaneous real time analysis of most elements in the periodic table. ICP-OES has a very simple quantification scheme using normalized standards, extremely low detection limits, a dynamic range of linear emission intensity vs. concentration of over five to six orders of magnitude, and a very low sensitivity to matrix effects.

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In this series of papers, we investigate selective dissolution phenomena for a 304 stainless steel in sulfuric acid solution. This paper deals with the enrichment of copper and its subsequent inhibition effect on the active dissolution of the alloy, and how these effects vary with chloride ion concentration. In a following paper (Part II of this work), we investigate the enrichment of Cr during passive film formation. Copper is often added to stainless steel to reduce the work hardening rate so as to provide superior cold working properties and to stabilize the austenite crystal structure [28]. Moreover, copper is known to improve general corrosion resistance in acid solutions [29–31] and increase the pitting corrosion resistance in chloride containing media [32–37]. Below about 3%, copper is homogeneously distributed in the steel matrix [38] and replaces Fe in the austenite crystal structure. Above 3%, the copper may precipitate in the epsilon-copper phase leading to the possibility of galvanic corrosion. Much of the literature on copper containing stainless steel concerns products in which copper has been intentionally added. However most industrial stainless steels contain small amounts of copper due to the use of scrap metal in the fabrication process. In this work, we apply the AESEC method to directly observe the effect of these copper present at only 0.2% on the electrochemical activity of a 304 stainless steel in sulfuric acid solutions. 2. Experimental 2.1. Materials A commercial-grade stainless steel was used in this work with elemental analysis as given in Table 1. The elemental analysis is consistent with the 304 grade specifications as defined by the ASTM [39]. The sample was used as received following degreasing in reagent grade ethanol. All chemical products were reagent grade and solutions were prepared from 18.2 M water purified with a MilliporeTM system. 2.2. AESEC method A block diagram of the AESEC technique is shown in Fig. 1. The instrumentation may be divided into several modules: (A) an electrochemical flow cell where a flat solid material is exposed to a flowing electrolyte; (B) a downstream ICP-OES spectrometer that is used to analyze the elemental composition of the electrolyte leaving the flow cell; and (C) a special electronic system that is used to collect the emission intensities and electrochemical data as a function of time. Table 1 Elemental analysis in of 304 grade stainless steel used in this work (wt%). C S P Si Mn Ni Cr Mo Cu Sn Al V Ti Co Nb W N2

0.040 0.0011 0.023 0.361 1.370 9.03 17.57 0.172 0.190 <0.003 <0.005 0.087 <0.003 0.133 0.009 0.1 0.0234

All measurements were made using inductively coupled plasma optical emission spectrometry except C, S—fusion and infrared, N2—fusion with infrared and thermal conductivity.

2.2.1. Electrochemical flow cell The electrochemical cell used in this work was similar to that previously described [17]. A functional block diagram of the cell and a computer generated image are shown in Fig. 1B. The cell is composed of a two-compartment system in which the working electrode (we) is exposed to a flowing electrolyte (f = 3 ml/min) in a small volume (0.2 ml) flow cell. The geometrical area of the sample exposed to the electrolyte was 0.5 cm2 defined by the contour of the o-ring (j). The flow channel has an entrance at the bottom and exit at the top so that the electrolyte passes through the cell from bottom to top such that any gas generated during the experiment flows out of the cell. A 10 ml cylindrical secondary compartment of stagnant electrolyte (cec) is separated from the working electrode compartment by a porous membrane (m). This membrane allows ionic current to pass from one compartment to the other while preventing bulk mixing of the two electrolytes. A Pt counter electrode (ce) and an Ag/AgCl reference electrode (re) were placed in the secondary compartment. A spring system (s and ss) was used to homogenize the force of the sample against the o-ring. An EG&G PAR M273A potentiostat/galvanostat was used for all electrochemical experiments. The signals were specially adapted so that they could be channeled into the ICP-OES spectrometer and collected simultaneously with the ICP-OES software as described below. The current range was altered manually during these experiments. 2.2.2. ICP-OES spectrometer A commercial ICP atomic emission spectrometer from HORIBA Jobin Yvon, SAS. (Ultima 2CTM ) was used in this work. The Ultima 2CTM consists of a 40.68 MHz inductively coupled Ar plasma, operating at 1 kW, interfaced to independent polychromator (poly) and monochromator (mono) optical modules. Radiation emitted from the plasma (h) was collected in the radial direction and split between a polychromator for the simultaneous detection of 30 predetermined wavelengths and a monochromator that could be used for the detection of an adjustable wavelength. The polychromator used a Paschen–Runge configuration with a 0.5 M focal plane and was equipped with a holographic grating of 3600 grooves/mm and 30 independent photomultiplier tubes. The theoretical resolution of the polychromator was 0.025 nm in the first order and 0.015 nm in the second order covering a spectral range from 165 to 408 nm. The monochromator used Czerny–Turner configuration with a 1.0m focal plane and was equipped with a holographic grating of 2400 grooves/mm with practical resolution of 0.005 nm in a spectral range from 120 to 320 nm and a resolution of 0.010 nm in a range from 320 to 800 nm. Both polychromator and monochromator were nitrogen purged. The electrolyte was continuously feed into the plasma using a peristaltic pump. The pump served to transfer the electrolyte from the electrochemical flow cell into a concentric glass nebulizer and a cyclonic spray chamber and to control the flow rate in the electrochemical cell at 3.0 ml/min. The hydraulic system was specially optimized to give the best temporal resolution without undue lowering of the detection limits. However, it should be noted that the detection limits obtained in this work are not as good as could be obtained at the recommended flow rate of 1 ml/min. The faster flow rates are used to improve the temporal resolution which is not usually a consideration in conventional ICP-OES analysis. 2.2.3. Fast electronics The signals from the phototubes (mono and poly) were monitored in real time using the QuantumTM software and data acquisition package developed by HORIBA Jobin Yvon, SAS for use with glow discharge spectroscopy. In brief, three 16-bit A/D converters operating at a frequency of 250 kHz are used to con-

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Fig. 1. (A) Schematic block diagram of the atomic emission spectroelectrochemistry experiment. (A) Reaction cell with electrolyte reservoir (res) and peristaltic pump. Arrows indicate direction of electrolyte flow during an experiment: (b) background experiment with cell bypass and (r) reaction experiment. The valve (v) is used to switch between a background and a reaction measurement. (B) ICP-OES spectrometer. (P) indicates the plasma. Photons (h) emitted from the plasma are collected in a monochromator (mono) and a polychromator (poly) unit. (C) Fast electronics allows real time monitoring the emission intensity of up to 31 wavelengths, 30 from the polychromator + 1 from the monochromator as well as four analog signals for electrochemical measurements (not shown). The emission intensity is used to calculate the concentrations of specific elements, CM . (B). A functional diagram of the electrochemical cell (left) and a computer image of the cell as constructed (right). wec = working electrode compartment; cec = counter electrode compartment; j = o-ring; m = membrane. we = working electrode; ce = counter electrode. re = reference electrode; s = spring; ss = spring support. Dashed arrows indicate the direction of solution flow.

tinually monitor the output of the 31 photomultipliers. The data is transferred to the computer after averaging over a user defined integration period, in this work set for 1 s. This means that each measured value of intensity corresponds to the average of 250,000 data points. The result is that the dynamic range of the experiment is vastly increased over that of a single measurement with a 16bit A/D converter and the data from the different channels may be considered as true simultaneous measurements. The electronic system was further modified for the AESEC experiment so as to permit the introduction of four supplementary analog channels, two of which were used in this work to collect current and potential data from the M273 potentiostat. These channels were amplified and offset so as to be consistent with the spectroscopic emission signals. Analysis of electronic noise demonstrated that potential measurements with this system were stable to approximately 0.05 mV. This modification ensured that spectrometer and electrochemical data were collected with the same time base greatly simplifying the correlation of the transitory signals. 3. Results 3.1. Characterization of the system Fig. 2 shows a calibration curve on a log-log scale for Fe, Cr, Ni, Mn, Mo and Cu emission covering four orders of magnitude of concentration. The intensity values are in arb units and the curves

Fig. 2. Calibration curves on a log–log axis showing the atomic emission intensity as a function of concentration. The wavelengths used for each element are given in Table 2.

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Table 2 Detection limits (mg/l = ppb) of the ICP-OES under the conditions of these experiments.

␭/nm C2␴ /ppb

Fe

Cr

Ni

Mn

Mo

Cu

259.940 9.7

267.716 3.8

231.604 9.5

257.610 0.37

202.032 1.0

324.754 4.7

have been offset from one another for clarity. The excellent linear relationship demonstrates the large dynamic range mentioned in the introduction. Deviations at 0.001 mg/l (1 ppb) are noted for Ni and Mo as the intensity level at this concentration is very close to the background noise. Concentrations higher than 10 mg/l were not used in this work so as to avoid contaminating the nebulization system, however linearity is normally maintained to concentrations above 100 mg/l. Deviations from linearity at high concentration are due to self-absorption [40] in which photons emitted in the center of the plasma are absorbed by unexcited atoms in the cooler outer part of the plasma. Table 2 gives the performance conditions typical of the experiments performed in this work. The “detection limit” is defined in this work as C2␴ = 2/ where sigma is the relative standard deviation of background noise. This measurement is made by passing the blank electrolyte (with no analyte) into the plasma and measuring the intensity of the signal at a given wavelength for a preset integration period, usually several minutes. 3.2. Anodic dissolution of a 304 stainless steel in 2 M H2 SO4 Fig. 3 gives the AESEC polarization curve for stainless steel in 2 M H2 SO4 measured after approximately 10 min exposure to the electrolyte. The polarization experiment began with a prepolarization at −478 mV for 360 s followed by a potential sweep in the anodic direction at a rate of 0.5 mV/s. We refer to the polarization current as the external current, Iex , to distinguish it from the elemental currents, IM , that are in fact calculated from the concentration transients. The electrochemical polarization curve (Iex vs. E) is shown in Fig. 3A. Four different features are visible in the polarization curve: (a) a cathodic branch, (b) an anodic maximum, (c) a second cathodic minimum, and (d) a passive current. The second cathodic minimum and the passive region are highlighted by two expanded scale insets in Fig. 3, labeled A1 and A2, respectively. Note that only the current scale has been expanded, the potential scale is identical for all the data in Fig. 3. All potentials are given relative to the normal hydrogen electrode (NHE). The entire cathodic region (a) is characterized by an intense negative current with significant hydrogen gas evolution as evidenced by the appearance of gas bubbles in the capillaries between the cell and the ICP-OES spectrometer. During the prepolarization at −478 mV the current is at a minimum value between −40 to −60 mA/cm2 . The current then rises steadily with the increasing potential, crossing the zero point around −230 mV. The anodic passivation peak (b) obtains a maximum of 1.1 mA/cm2 . Following the maximum, the current drops off sharply and becomes cathodic again reaching a minimum at −0.046 mA/cm2 (c). This second cathodic minimum is clearly visible in the expanded current scale, A1, (−0.1 mA/cm2 to 0.2 mA/cm2 ) between −100 and 650 mV. Following the second minimum, the current increases steadily to enter the passive region (d) where approximately 0.084 mA/cm2 were measured, as seen in the expanded current scale inset, A2 (0.004–0.01 mA/cm2 ). The current in the passive region varies slightly throughout the remainder of the experiment. The ICP-OES spectrometer is used to measure the concentrations of various elements downstream from the electrochemical flow cell.

Fig. 3. Total external current and partial elementary currents for the polarization of a 304 stainless steel sample in 2 M H2 SO4 . Electrode surface area = 0.5 cm2 and potential sweep rate = 0.5 mV/s. (A) Conventional polarization curve giving external current, Iex , as a function of potential. The two insets, A1 and A2 show an expanded current scale for potential regions of particular interest. The labels a, b, c, and d are defined in the text. (B) Partial elementary dissolution currents for IM,M for M = Fe, Cr, Ni, and Mn as measured by ICP-OES spectrometry. The values have been multiplied by arbitrary factors  as indicated for clarity. The point data gives the sum of the IM,M . (C) Partial elementary dissolution currents IM,M with elemental currents, for M = Mo and Cu. These have been offset due to the high noise level.

The concentration transients may be expressed as an “elemental currents”, IM , that is to say the contribution of the dissolution of a single element to the total current. These elemental currents are calculated from the downstream concentration using IM = nM F f CM

(1)

where n is the valence of the metal ion in solution, f is the flow rate of the electrolyte (l/s), CM is the concentration (moles/l), and F is the Faraday constant. The valance of the dissolved ions must be known independently as ICP-OES only detects the element and not the oxidation state. Fig. 3B shows the correlation of the elemental dissolution curves obtained by AESEC as compared with the total electrical current. The curves are shown for IM with M = Fe/Fe2+ , Cr/Cr3+ , Ni/Ni2+ , Mn/Mn2+ , Mo/Mo2+ , Cu/Cu2+ , and the sum of the elemental currents indicated as IM . The elemental currents shown in Fig. 3B have been multiplied by various factors as indicated so as to make visual comparison easier. The concentration levels for Cu and Mo were very low and have been separated into Fig. 3C, with an expanded current scale and with the copper signal offset for clarity. Three unique features are visible in the elemental current transients. There is a significant dissolution peak observed during the cathodic prepolarization period (a). This peak is probably associated with the reduction of surface oxides and will be discussed in a future paper. This is followed by the anodic dissolution peak (b) from −278 mV to +122 mV. Note that the rise of the elemental dissolution currents is clearly visible well before the total current changes

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sign demonstrating the capacity of this technique to observe anodic reactions despite a strong overall cathodic current. The anodic dissolution rates obtain a maximum around −78 mV and then decrease forming a relatively symmetric dissolution curve. These results demonstrate that the anodic peak corresponds to the simultaneous dissolution of all analyzed elements with the exception of copper. In fact, the sum of the elemental currents (points) is seen to be in good agreement with the total current at least at the anodic maximum and during the descending part of the curve. Discrepancies in these domains are attributed to a strong interfering cathodic current. The dissolution of copper only begins at much higher potential, approximately −20 mV. Note that the peak maximum for copper dissolution is only 0.002 mA/cm2 and makes a negligible contribution to the total current even in the passive region. In fact, the overall current is cathodic during the early stages of copper dissolution. No elemental dissolution other than copper was detected in the passive region, suggesting perhaps the formation of insoluble oxides, the oxidation of adsorbed hydrogen atoms [36], and/or the oxidation of other species present in the electrolyte.

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Table 3 Integration of the anodic dissolution peaks for the six elements investigated in this work. Ni

Mn

Mo

Cu

0 M NaCl

% ␮g/cm2

Fe 72.8 86.8

Cr 16.7 19.9

9.0 10.70

1.3 1.58

0.11 0.13

0.17 0.20

0.1 M NaCl

% ␮g/cm2

72.6 141.2

17.1 33.2

8.88 17.28

1.23 2.4

0.15 0.30

0.15 0.30

0.2 M NaCl

% ␮g/cm2

71.6 509.4

17.4 123.6

9.4 67.0

1.3 9.46

0.17 1.20

0.12 0.86

3.3. The effect of NaCl The addition of either 0.1 M or 0.2 M NaCl to the sulfuric acid solution leads to a notable increase in the rate of anodic dissolution and an extension of the dissolution reaction over a wider potential range. This is shown in Fig. 4, an overlay of the anodic dissolution curves obtained for solutions of 2 M H2 SO4 with 0 M, 0.1 M, and 0.2 M NaCl. The dissolution of the 304 stainless steel in 2 M H2 SO4 gave rise to only one dissolution peak. The presence of NaCl gives rise to a second peak that is poorly resolved from the first, especially in 0.2 M NaCl. For simplicity, the two peaks will be referred to as the ␣ and ␤ dissolution peaks, respectively. The addition of NaCl to the electrolyte leads to the growth of the ␤ dissolution peak. Integration of the dissolution peaks (Table 3) indicates that the total amount of steel dissolving increases markedly with the addition of NaCl: a factor of 1.6 for 0.1 M NaCl, and 5.9 for 0.2 M NaCl. The enhanced dissolution induced by chloride is primarily in the ␤ peak; the leading edge of the dissolution peak does not vary significantly with the addition of NaCl indicating that the ␣ peak is practically independent of NaCl concentration. The curve at 0 M NaCl shows this peak shifted slightly in the cathodic direction with respect to the other curves. However the effect is slight, about 25 mV. The integration results of Table 3 are presented as both ␮g/cm2 and as mass percent calculated from the sum of all elements. The



Fig. 4. Anodic dissolution curve (

IM ) of 304 stainless steel in 2 M H2 SO4 with

0 M, 0.1 M, and 0.2 M NaCl as indicated in the figure. Electrode surface area = 0.5 cm2 , potential sweep rate = 0.5 mV/s.

Fig. 5. Elemental dissolution profiles of 304 stainless steel in 2 M H2 SO4 with 0.1 M NaCl. All of the elements except copper have been normalized to demonstrate simultaneous dissolution. Mo has been offset for clarity due to a low signal to noise ratio. Electrode surface area = 0.5 cm2 , potential sweep rate = 0.5 mV/s. Multiplicative factors are Fe (1), Cr (2.65), Ni (8.4), Mn (57), Mo (300), and Cu (550).

results obtained at 0.2 M NaCl are in good agreement with the values given in Table 1. The later were also measured by ICP-OES but with complete dissolution of the steel sample. This demonstrates that the anodic dissolution occurring in 0.2 M H2 SO4 is consistent with that of the bulk steel sample. The elemental dissolution profiles for 0.1 M and 0.2 M NaCl are shown in Figs. 5 and 6. The dissolution rates of Fe, Cr, Ni, and Mn have been normalized so as to overlap. It is clear that the dissolution rates of these four elements correlate perfectly throughout the active anodic dissolution domain. The signal for Mo is much lower and because of the high noise component, the curve for Mo has been

Fig. 6. Elemental dissolution profiles of 304 stainless steel in 2.0 M H2 SO4 with 0.2 M NaCl. All of the elements except copper have been normalized to demonstrate simultaneous dissolution. Mo has been offset for clarity due to a low signal to noise ratio. Electrode surface area = 0.5 cm2 , potential sweep rate = 0.5 mV/s. Multiplicative factors are Fe (1), Cr (2.65), Ni (8.4), Mn (57), Mo (300), and Cu (550).

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of dissolved species in the flow cell. Nevertheless, the data points in Fig. 7 indicate that the onset potential for copper dissolution follows closely the predicted value for log CCu in the range of −5 to −6. 4. Discussion 4.1. Mechanistic interpretation The combined electrochemical and concentration transients may be interpreted in terms of three generalized reactions: k1

(M, Cu) (s)−→Cu(s) + Mz+ + ze− k2

Cu (s)−→Cuy+ + ye− k3

M (s) + xH2 O−→MOx + 2xH+ + 2xe−

Fig. 7. Equilibrium predominance area diagram for the Cu–Cl− system. The experimental points shown give the potential measured from the onset potential of copper dissolution for the different chloride ion concentrations.

offset for clarity. Nevertheless the Mo dissolution rate is seen to follow that of the other elements very closely. Copper dissolution, on the other hand, shows a very different behavior. It is detected only in the later part of the dissolution peak and in particular appears to be associated with the ␤ peak. It is also of interest to note that copper dissolution continues after the other elements have dropped down to the background level. The copper dissolution peak shifts to more negative values with increasing Cl− ion concentration. The shift in the copper dissolution potential may be explained by the formation of stable Cu(I) complexes in Cl− containing solutions. This effect is demonstrated by an equilibrium predominance area diagram of Fig. 7 for the Cu/Cl− system at [H+ ] = 4 M. The diagram was calculated with the Hydra-MedusaTM equilibrium software and database [41]. The diagram shows the predominate species existing over a potential and log[Cl− ] range. Calculations were performed for various total concentrations of dissolved copper using thermodynamic data for a total of 35 soluble copper complexes and solid-state compounds. Sulfate was not included in this calculation as a simplification. The presence of sulfate would favor the complex CuSO4 rather than Cu2+ on the right hand side, however, this has only a minor effect on the potential for Cu(s) oxidation. On the left hand side, thermodynamic calculations including sulfate species would predict many highly stable complexes and solid species that form between copper ions and reduced sulfate species including CuS and CuS2 O3 . However previous studies indicate that these species do not form under conditions similar to our work [42,43] and a TOF-SIMS analysis in our laboratory of stainless steel samples exposed to 2 M H2 SO4 did not show the presence of sulfur in the condensed phase. Over the range of chloride concentration and potential investigated here, the major species are Cu, Cu2+ , and CuCl2 − . A narrow domain of uncomplexed Cu+ is observed for 10−6 M total copper concentration. The stabilizing effect of Cl− is demonstrated by the area of CuCl2 − above 10−3 M Cl− . This result shows that the potential for the dissolution of copper decreases linearly with log[Cl− ]. Of course, the continuous flow dissolution experiments do not reflect an equilibrium condition since no copper ion is initially present in the electrolyte and the copper ion concentration will otherwise depend on the copper dissolution rate and the time constant distribution

(I) (II) (III)

Reaction (I) represents the simultaneous dissolution of the alloy components in the active region where M = Fe, Cr, Ni, Mn, and Mo. For simplicity, we refer to reaction (I) as anodic dissolution. Slight deviations from simultaneous dissolution may be observed for Fe and Cr due to the formation or dissolution of a Cr-rich passive film. However, these deviations are negligible for the dissolution in the active peak described here. The dissolution of the elements, M, leads to the formation of a Cu-enriched surface as either the copper remains behind or is dissolved and is redeposited. The copper film is presumed to have an inhibiting effect on reaction (I). In 2 M H2 SO4 without NaCl, reaction (I) continues until the surface is totally blocked by the copper film. The presence of this copper film explains the second cathodic minimum as copper is a more effective cathode than stainless steel [32,33,44]. Hermas et al. [36,45] have observed similar secondary cathodic “loops” and attributed this phenomenon to the lower overpotential of the accumulated copper film for H+ reduction. In this solution, the potential range of copper dissolution is more positive than that of passivation. Therefore, once copper dissolution begins, the cathodic current decreases and metal passivation (III) occurs. The experiments performed in the absence of NaCl indicate that complete s = 0.20 ␮g/cm2 (Table 3). Assuming a deninhibition occurs at QCu sity of 8.95 g/cm3 , this would yield an average film thickness of approximately 0.2 nm. This very small thickness (atomic radius of copper is 0.13 nm) suggests that either the copper distribution is uneven on the surface or a single monolayer of copper is sufficient to inhibit the anodic dissolution of the stainless steel sample. These results do not rule out the possibility of an insoluble (oxidized) form of copper which might also contribute to the inhibiting effect. However, the quantity of copper is very low as it was undetectable by scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDS) measurements in our laboratory. Similar observations have been made by Pardo et al. [32] for inhibiting copper films deposited on stainless steel by cementation. They found that the very thin film of copper deposited by cementation was as effective for corrosion inhibition as a thicker electrodeposited film. In 0.1 and 0.2 M NaCl, the situation is different. The presence of Cl− shifts the dissolution potential of reaction (II) to a value below the passivation potential. In 0.1 M NaCl, this gives rise to two partially resolved peaks; the first maximum is due to the inhibiting effect of the copper film on the anodic dissolution (I), however copper dissolution (II) occurs before total inhibition takes place leading to a reactivation of the surface. This reactivation continues until passivation (III) occurs. This leads to a rapid decline in the rate of reaction (I). Once reaction (I) has been completely inhibited, the copper film is no longer being replenished and copper dissolution

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continues until the copper film is gone. This is demonstrated in Figs. 4 and 5 by the fact that the copper dissolution peak is shifted to slightly more positive values than the ␤ anodic dissolution peak. Also copper dissolution decreases over a longer time period (potential range) than that of the anodic dissolution reaction. During the later phase, copper dissolution will expose fresh alloy surface, however in this potential range, the exposed surface will be instantly passivated by reaction (II). In 0.2 M NaCl a similar observation is made, however, the copper dissolution peak is shifted to even more negative potentials. The inhibiting effect of copper appears as a shoulder on a larger activation peak. 4.2. Kinetic model of selective dissolution The mechanistic ideas proposed intuitively in the previous paragraph may be developed into a simple phenomenological model for selective dissolution. This model is used to demonstrate the effect of simultaneous passive film formation coupled with copper enrichment and the effect on the overall anodic dissolution rate as a function of potential. Our goal is to produce the simplest mathematical model possible that demonstrates the qualitative phenomena observed in Section 4.1. We assume that inhibition of metal dissolution may result from either the accumulation of residual copper on the surface and/or the formation of a passive film. We further assume that the copper dissolution rate is directly proportional to the amount of copper on the surface and that complete inhibition occurs at a critical quantity s . The elemental dissolution rates measured by the ICP-OES of Cu, QCu may be written as



a = k1 (1 − Cu )(1 − p )

s QCu



Cu

s ) Cu = k2 (QCu

(2) (3)

where  Cu is the fraction of the surface covered by the copper film s ) and ␹ ( = Q/QCu Cu is the fraction of Cu in the alloy.  p is the fraction of the surface covered by the passive film. Passive film formation is also due to selective dissolution leaving behind a Cr-rich oxide on the surface. Note that the model treats the reactive surface as if it were completely uniform. The assumption is probably valid for, as previously mentioned, it is well known that copper is uniformly distributed in the alloy below 3%. Nevertheless, if some localization of the anodic dissolution/inhibition did occur,  would simply refer to the active surface rather than the total surface and the model would be essentially unchanged. The kinetics of anodic dissolution may be explored by consideration of the series of differential equations (4)–(7). Passivation (4) is assumed to be independent of the formation of the copper film. Within the framework of this model, the formation of the copper film (first term of Eq. (5)) does depend upon the presence of the passive film since the later inhibits anodic dissolution, however, the dissolution of the copper film (second term of Eq. (5)) is considered to be independent of passivation. A Tafel expression is assumed for all rate constants (6) which for simplicity are assumed to be independent of  p and  Cu . The linear potential sweep (7) completes the model. dp = k3 (1 − p ) dt

(4)

dCu = k1 (1 − Cu )(1 − p ) − k2 Cu dt



kj = kj exp E = E◦ + ˇ t

(5)



E − Ej ba,j

(6) (7)

Fig. 8. Simulated anodic polarization (lower) and copper dissolution (upper) curves from the system of Eqs. (4)–(7) for variable Cu dissolution potential as indicated. Parameters used for these simulations where kj = 0.001 s−1 ; b1 , b2 = 50 mV, b3 = 25 mV; EM = −250, Epass = 0, ECu = variable as indicated in the figure, and ˇ = 0.5 mV/s and t = 0.1 s.

A fourth-order Runge–Kutta program was used to solve Eqs. (4)–(7) in the time domain using a time step of 0.1 s (0.05 mV). Typical results from a series of simulated polarization curves are shown in Fig. 8. The values of the constants used in these simulations are given in the figure caption. Note that two curves are shown for each simulation: the rate of copper dissolution (reaction (II)) in Fig. 8A and the rate of anodic dissolution (reaction (I)) in Fig. 8B. For this series of simulations, the passivation potential, Epass , (E3 in Eq. (3)) and the anodic dissolution potential, EM (E1 in Eq. (3)) were held constant at 0 mV and −250 mV, respectively. The copper dissolution potential, ECu (E2 in Eq. (3)) was varied. To simplify the presentation, the polarization curve is therefore shown as a function of (E − Epass ). Note that we have made no attempt to “fit” the data. A truly predictive model is beyond the scope of this work. Indeed, the exponential nature of Eq. (6) leads to numerical instability at high potential for some choices of constants making this quite difficult. The results demonstrate that the system of Eqs. (4)–(7) leads to two separate anodic dissolution peak, analogous to the ␣ and ␤ peak observed in the experimental data. Fig. 9 shows that the ␤ peak is present even when ECu − Epass is quite large, although it is undetected in the linear current scale of Fig. 8. The position and intensity of the ␣ peak does not vary with ECu . However the ␤ peak increases markedly as ECu becomes more negative. At ECu − Epass copper dissolution is almost simultaneous with anodic dissolution. In our experimental system, the copper dissolution potential is controlled by the chloride ion concentration and a good qualitative agreement is seen between the data of Fig. 8 and the results in the previous section (Fig. 4 for example).

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Chapon and O. Rogerieux of HORIBA Jobin Yvon for electronic and software modifications and support of the Ultima 2CTM ICP-OES system; Meriem Mokaddem of the ENSCP for technical assistance; and Jerôme Peultier of ArcelorMittal for the donation of electrochemical equipment, the elemental analysis of the stainless steel sample, and useful discussions. References

Fig. 9. Simulated anodic polarization curve on a log scale showing the variation of the ˇ peak intensity with the copper dissolution potential.

5. Conclusions In this work we have demonstrated the utility of the AESEC method for measuring the elementary dissolution reactions that occur during the anodic dissolution of complex alloys. This method has allowed us to quantify the accumulation and subsequent dissolution of copper on the surface of a 304 stainless steel during anodic polarization. The rate of copper dissolution was measured as a function of potential in sulfuric acid solution containing variable amounts of NaCl. It was found that the potential of the copper dissolution peak shifts in the cathodic direction as the chloride ion concentration increases. This is explained by the stabilization of the Cu+ state by the formation of CuCl2 − as demonstrated by thermodynamic calculations. The residual copper film is shown to exert an inhibiting effect on the anodic dissolution reaction and to accelerate the cathodic reaction. This leads to the appearance of two partially resolved anodic dissolution peaks in the polarization curve. The resolution of the two peaks and the intensity of the second peak depend upon the copper dissolution potential which in turn depends upon the chloride ion concentration. In the absence of chloride, the acceleration of the cathodic reaction, leads to a second cathodic minimum after the active dissolution peak. The AESEC method allows us to isolate and independently measure the elementary dissolution reactions throughout the polarization curve. A simple model is proposed, taking into account the simultaneous formation and dissolution of a residual copper film and the formation of a passive film, involving only two differential equations. It is demonstrated that this model adequately simulates the appearance of the anodic dissolution peaks and their variation with the copper dissolution potential. Acknowledgements The authors would like to thank the Agence Nationale de Recherche (Reference ANR-05-BLAN-0379) for financial support; P.

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