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1.
Initial metallographic image of 304L SS.
| Cite this article as: |
Liang Li, Yanxin Qiao, Lianmin Zhang, Aili Ma, Enobong Felix Daniel, Rongyao Ma, Jian Chen, and Yugui Zheng, Effect of surface damage induced by cavitation erosion on pitting and passive behaviors of 304L stainless steel, Int. J. Miner. Metall. Mater., 30(2023), No. 7, pp.1338-1352. https://dx.doi.org/10.1007/s12613-023-2602-0
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Cavitation erosion (CE) is one of the most common failure forms, which is attributed to shock waves and micro-jets produced by the collapse of bubbles impacting the surfaces of materials in rapidly oscillating or high-speed flowing liquids [1–3]. It is frequently encountered with flow-handling components such as propellers, valves, and pipes. In corrosive media, the flow-handling components made of metallic materials (e.g., stainless steels, titanium alloys, copper alloys, and carbon steels), are suffering from the combined interactions of mechanical impact and chemical (or electrochemical) corrosion [4–6]. Austenitic stainless steel is a common material used as flow passage parts, which has a passive film to protect materials from corrosion in corrosive solutions. However, the protective properties of passive films are easily affected by metallurgical processes (e.g., smelting temperature and heat treatment temperature) and microstructure [7–10], especially the internal carbide content and the number of high-energy grain boundaries can seriously affect the corrosion resistance of the materials. Furthermore, corrosion causes the formation of surface defects of materials, at which CE damage originates preferentially. Meanwhile, the passive film or corrosion products formed on the surfaces of these materials can be partially or totally damaged by CE, thus decreasing the corrosion resistance of materials (i.e., the resistance to pitting corrosion and the ability to passivation). However, the influence of CE-induced surface damage on corrosion behavior has not been mentioned. Especially the pitting and passive behaviors of stainless steel after CE have not been investigated.
The pitting corrosion and the passive behaviors of materials are closely related to the degree of CE damage because the surface state and conditions of materials have a significant influence on the corrosion performance of materials [11]. In corrosive media, a rough surface is beneficial to the formation and growth of stable pitting [12]. On the other hand, the rough surface can remarkably weaken the passivation performance and in turn enhance the depassivation effect, leading to the deterioration in the corrosion resistance of materials. The passivation and depassivation of materials occur simultaneously and compete with each other. When the passivation effect is far beyond the depassivation effect, the surface of materials maintains a spontaneous passive state. While the initiation and propagation of metastable pitting, even the formation of stable pitting, occur when the passivation effect is equivalent to the depassivation one. Active dissolution occurs when the passivation effect is weaker than that of the depassivation effect. Therefore, it can be inferred that the surface damage induced by CE may have a significant impact on the pitting and passive behaviors of materials.
Electrochemical noise (EN) is widely used in the field of corrosion and is a powerful tool to characterize localized corrosion, especially pitting corrosion [13], stress corrosion cracking [14], and CE damage [15]. EN can continuously monitor the corrosion behaviors of materials under an unstable state caused by random non-equilibrium fluctuation of electrode potential or external measured current [14,16–17]. The pitting corrosion of several materials was studied by Almeraya-Calderón et al. [18] using transient analysis, and they found that the transient change corresponds to the activity of pitting nucleation on the electrode surface. With the help of EN, the corrosion behavior of AZ91D magnesium alloy in NaCl aqueous solution was investigated, showing that the growth, development, and inhibition processes of pitting corrosion could be successfully detected using transient analysis [13]. Meanwhile, it was also reported by Zhang and Wu [19] that wavelet analysis could provide more information about pitting corrosion at different stages. Additionally, based on shot noise theory, Sanchez-Amaya et al. [20] derived the average charge of a single event and the frequency of the event, and they correlated these parameters with the corrosion mechanism well. Besides the application of EN, the potentiostatic polarization technique can be used to evaluate the passive behaviors of materials. The passivation ability of UNS N08031 at different applied potentials was studied by Fernández-Domene et al. [21], suggesting that the passivation ability decreased with the rising potentials. Moreover, the interactions between pitting corrosion and critical flow velocity (CFV) of 304L SS under jet impact conditions were clarified by Li et al. [22], who proposed a method to quickly determine the CFV based on a potentiostatic polarization test. Thus, it is anticipated that the combination of EN and potentiostatic polarization methods would shed light on the influence of CE-induced surface damage on the pitting and passive behaviors of materials.
In this paper, the aim was to investigate the influence of CE-induced surface damage on the pitting and passivation behavior of 304L SS. To study the corrosion responses of 304L SS in 3.5wt% NaCl solution after different CE times, EN and potentiostatic polarization techniques were used to monitor the corrosion behavior of the 304L SS. EN signal combined with the measurement of CE mass loss and the observation of surface morphology was analyzed to evaluate the pitting sensitivity and passivation ability of 304L SS after different CE times. The influence of CE-induced surface damage on the corrosion mechanism of 304L SS was further discussed, which could be beneficial to a more comprehensive and in-depth understanding of the CE damage mechanism of 304L SS in corrosive media.
In recent years, wavelet analysis of EN data has been widely used in the corrosion field. The specific details of wavelet analysis can be explained using the research of others [23–25]. The essence of wavelet analysis is to divide time series xn(t) (n = 1, 2, 3, …, N) into the combination of two basic functions, ψj,n(t) and φj,n(t) (j = 1, 2, 3, …, J), as shown in Eq. (1) [24]:
|
xn(t)≈N∑n=1sJ,nφJ,n(t)+N∑n=1dJ,nψJ,n(t)+N∑n=1dJ−1,nψJ−1,n(t)+⋯+N∑n=1d1,nψ1,n(t) |
(1) |
where wavelet detail coefficient dj,n (j = 1, 2, 3, …, J) and smoothed coefficient sj,n (j = 1, 2, 3, …, J) represents the Wavelet coefficient. The method of wavelet analysis was as follows: the test noise signal xn = x1, x2, ..., xN was initially divided into two sets of wavelet coefficients d1 and s1. The set of detail coefficients d1 = (d1,1, d1,2, …, d1,N/2) contains the local fluctuations in the signal, while the set of smoothed coefficients s1 contains the overall trend of the signal. Subsequently, the detail coefficients d1 were retained and the set of smoothed coefficients was analyzed by high-pass and low-pass filtering to obtain again the new coefficient sets d2 and s2. This process was iterated J times in succession to decompose the original data to obtain the desired set of wavelet detail coefficients d1, d2, …, dJ. Each of these sets of coefficients was referred to as a crystal [23]. The time scale of each crystal (Cj1,Cj2) can be expressed by the following equation [26]:
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(Cj1,Cj2)=(2jΔt,2j−1Δt),j=1,2,3,⋯,J |
(2) |
The relative energy fraction of each coefficient was calculated according to Eq. (3) [26], and the energy dispersive spectroscopy (EDS) was used to show the contribution of the relative energy Ejd of each crystal under corrosion.
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Ejd=1EN/2j∑n=1d2j,n;j=1,2,3,⋯,J,andE=N∑n=1xn(t)2 |
(3) |
Corrosion noise signals are usually regarded as a series of short-time constant charge events caused by shot noise [15,27]. In the corrosion process, the current is carried by discrete carriers, which produces shot noise. The movement of discrete carriers is a relatively independent and random process. Therefore, it can be assumed that two characteristic parameters (i.e., q and fn) are extracted from the shot noise of corrosion, and the average corrosion current (ˉIcorr) in shot noise caused by corrosion is expressed by the following equation [28]:
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ˉIcorr=q×fn |
(4) |
where fn is the frequency of corrosion event, and q is the average charge of event. fn and q can be calculated according to the following equations [28]:
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fn=ˉIcorrq=B2ψEA |
(5) |
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q=√ψEψIB |
(6) |
where B is the Stern–Geary constant, A is the electrode area, ψE and ψI is the power spectral density of potential noise and current noise at low frequency, respectively.
To obtain the cumulative probability F(fn), all fn data are arranged from small to large, and F(fn) can be calculated as C/(D+1), where C and D are the order and the total number of fn data, respectively. Weibull analysis is an analytical method based on shot noise, which is often used to predict the life problem [29]. It can quantitatively analyze data, even when multiple failure modes are present simultaneously [30]. Based on the failure model, the cumulative probability of the failure system can be calculated based on the following equation [27]:
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F(t)=1−exp(−tcd) |
(7) |
Eq. (7) can be converted into Eq. (8):
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ln[ln11−F(t)]=clnt−lnd |
(8) |
where c and d is the shape and the scale parameters respectively, determined by the slope and the intercept of curves. The rate of event occurrence can be defined as the following equation [27]:
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r(t)=cdtc−1 |
(9) |
where r(t) corresponds to the rate of pitting initiation with time.
The Nonlinear Markov process can be used to simulate the growth of pitting corrosion. The model can predict the maximum corrosion growth probability based on the limit value in statistical theory [31]. The corrosion charge of event q based on shot noise theory is calculated by Eq. (6), and the mass loss of material in the event is given by combining Faraday theory [32]. The specific operations using limit value statistical analysis are as follows: all q data are arranged from large to small, the cumulative probability F(Y) of decreasing variable Y can be obtained using Eq. (10), where E and F are the order and the total number of q data, respectively. The value of Y can be obtained using Eq. (11). Gumbel distribution diagram can be established using Y as abscissa and q as ordinate, in which, b and a is the slope and the intercept of the linear part of Gumbel distribution curve, respectively. According to the scale parameter α and the location parameter μ obtained by Eqs. (12) and (13), the growth probability of pitting corrosion can be calculated using Eq. (14). The following formulas are derived from reference [33].
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F(Y)=1−EF+1 |
(10) |
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Y=−ln{−ln[F(Y)]} |
(11) |
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a=1/b |
(12) |
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μ=−a/b |
(13) |
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Pc=1−exp{−exp[−(q−μ)a]} |
(14) |
where Pc is the probability that at least one corrosion event reaches a given charge q at the same time.
The material used in the experiment was 304L SS plate (Solution annealing at 1150°C for 1 h, water quenching) provided by Taiyuan Iron and Steel (Group) Co., Ltd, China and its chemical composition was as follows: 0.03wt% C, 0.64wt% Si, 2.00wt% Mn, 18.67wt% Cr, 9.25wt% Ni, 0.98wt% Cu, and Fe balanced. Fig. 1 shows the initial metallographic image of 304L SS. It is clear that there are equiaxed grains in 304L stainless steel, and the grain size is about 300–500 μm. According to ASTM Standard G32-10 [34], the CE parameters of the ultrasonic cavitation tester are composed of a vibration frequency of 20 kHz, output power of 1.25 kW, and peak-to-peak amplitude of 60 μm. Fig. 2 shows the schematic illustration of the test equipment. The dimensions of the sample used for mass loss tests could be referred to literature [35]. The samples were wet ground to 2000 grit with sandpaper and polished using 0.5 μm diamond polishing paste, then degreased with acetone and dried with cold air. The samples for CE tests were placed on a fixture at a distance of 5 mm from the end of the ultrasonic horn, which was immersed in 3.5wt% NaCl solution. To maintain the experimental temperature of (25 ± 2)°C, it was controlled using a circulating cooling device. The sample was weighed using an analytical balance to monitor the mass change. The mass loss rate (MLR) is calculated by the following equation [36]:
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MLR=ΔMΔt |
(15) |
where ΔM was the mass loss (mg) and Δt represented the CE time (h). Three parallel samples were used to ensure the accuracy of the mass loss data.
The electrochemical sample size was 10 mm × 10 mm × 4 mm, and its back was welded with copper wire and then sealed with epoxy resin. To ensure the accuracy of surface morphology, two cavitation pieces of equipment of the same specification were used for simultaneous CE, followed by plasma water cleaning, alcohol dehydration, drying, and a quick start of the electrochemical noise experiment. A three-electrode device consisting of two identical samples as working electrodes, saturated calomel electrode (SCE) as reference electrode, and Pt plate as the counter electrode was used for EN tests in the Faraday cage. The corrosion medium was 3.5wt% NaCl solution and the solution temperature was (25 ± 2)°C. The EN data after different CE times (0, 0.5, 1, 1.5, 2, 3, 5, 8 h) were collected using ES410 (Reference 600, Gamry Instruments, Inc., USA) at a sampling frequency of 5 Hz, at an interval of 1024 EN data points, and at a test time of 5 h. The transient analysis of the EN data was denoised by a 5-order polynomial, and Sym8 wavelet was selected to evaluate EN data in wavelet analysis. All data analyses of EN were processed using the Matlab 2016a software.
The open circuit potential (OCP) experiments were performed for 1800 s before potentiostatic polarization tests to ensure the stability of the corrosion system, and potentiostatic polarization tests were then carried out at 0.1 V vs. SCE for 600 s. The surface morphologies of the samples after different CE times were observed using scanning electron microscopy (SEM, INSPECT F50), and their roughness was measured using a white light interferometer (MicroXAM-1200). As well, the phase compositions of these samples after CE for different times were identified using an X-ray diffractometer (XRD, D8 ADVANCE) with Cu Kα radiation at 20 kV and 30 mA at a scanning rate of 3°/min.
Fig. 3 displays the mass loss plots of 304L SS in 3.5wt% NaCl solution against the CE time. The variation in the cumulative mass loss of 304L SS with CE time is shown in Fig. 3(a). It is obvious that the cumulative mass loss of 304L SS increased with the prolongation of CE time. The cumulative mass loss of the sample was almost zero at <1 h CE, indicating that only slight plastic deformation occurred on the sample surface at this stage corresponding to the incubation period of CE. For the samples after 1 h CE, the values of cumulative mass loss increased continuously with the extension of CE time and finally reached 75 mg at 8 h CE. Fig. 3(b) shows the plot of the cumulative mass loss rate with the CE time, which is a typical CE curve for stainless steel without cold working. The change in cumulative mass loss rate clearly shows that there were three periods of CE present: incubation period, rising period, and stable period. Although the cumulative loss rate of 304L SS at the incubation period was almost zero, it increased dramatically in the rising period and maintained a relatively stable value in the stable period.
Fig. 4 shows the XRD spectra of 304L SS after different CE times. The 304L SS selected in this experiment had a typical austenite structure (standard card number 33-0397), and its main characteristic peaks detected in the XRD spectrum prior to CE corresponded to (γ(111)), (γ(200)), and (γ(220)). After CE for 2 h or 3 h, a small diffraction peak (α′(110)) emerged at the angle of 2θ = 44.5°, indicating the formation of deformation-induced martensite (standard card number 44-1290). Extending the CE time to 5 h, the second diffraction peak of (α′(200)) and the third diffraction peak of (α′(211)) corresponding to deformation-induced martensite appeared at the angle of 2θ = 64.6° and 2θ = 82.1°, respectively. However, the relative intensity of the main diffraction peak (α′(110)) decreased after 8 h CE compared with the case after 5 h CE, implying the decreasing martensite content. This may be related to the change in surface microstructure.
Fig. 5 shows the evolution of surface morphologies of 304L SS after different CE times. Compared with the smooth surface of the sample prior to CE (Fig. 5(a)), some slip bands and convex grain boundaries appeared on the sample surface after 0.5 h CE (Fig. 5(b)). After CE for 1 h, the number of slip bands increased remarkably, and deformation twins were seen in the grain interior (Fig. 5(c)). Microcracks were observed at slip bands and grain boundaries after CE for 1.5 h or 2 h (Fig. 5(d) or (e)), whereas there were no obvious cracks inside the grains. The cracks resulted from CE was mainly attributed to two factors. The first factor should be related to the stress concentration at slip bands and grain boundaries because of the accumulation of dislocations caused by CE. The cracks would eventually occur when the cumulative stress exceeded the tensile strength of the sample [37]. The second one can be attributed to the preferential formation of deformation-induced martensite with a poor deformation ability, which could accelerate the propagation of microcracks [38]. Both the grain boundaries and the grain interior were severely damaged after CE for 3 h (Fig. 5(f)). Extending the CE time to 5 h, the surface of the sample was completely destroyed, and distinct exfoliation was observed (Fig. 5(g)). After CE for 8 h, the entire surface presented some big CE holes, indicating extremely severe surface damage (Fig. 5(h)).
Fig. 6 shows the surface roughness (Sa) of 304L SS after different CE times. The sample prior to CE had a relatively smooth surface with a Sa value of 29 nm. According to the change of Sa before 3 h CE, it is clear that the value of Sa increased remarkably from 2 to 3 h compared with the cases from 1 to 1.5 h or from 1.5 to 2 h. This may be attributed to the distinct damage degrees since the material deterioration mainly concentrated on the grain boundaries and slip bands before 2 h CE, whereas both the grain boundaries and the interior of the grains were seriously damaged after 3 h CE. The Sa value of the sample after 5 h CE increased by 5.7 times compared with the Sa value of the sample after 3 h CE and reached 16888 nm, which can be attributed to both the serious surface cracks and a large number of surface exfoliation under the action of CE stress impact. Extending the CE time to 8 h, the Sa value further increased to 25073 nm, implying that the sample underwent serious surface damage. These results indicate that the Sa of the sample displayed an increasing trend with the prolongation of CE time, which is consistent with the results of CE morphologies.
Fig. 7 presents the electrochemical potential noise (EPN) and electrochemical current noise (ECN) signals of 304L SS after different CE times using a 5-order polynomial method to remove direct current (DC) drift. According to the fluctuation and amplitude of the EN signal, the corrosion characteristics of the electrode surface can be judged, such as the intensity of the corrosion reaction and the corrosion type. The research shows that the initiation of pitting occurs in a very short time scale (a few seconds), the growth of metastable pitting requires a relatively medium time scale (tens of seconds), and the growth of stable pitting has the largest time scale (more than hundreds of seconds) [39–40]. The EPN and ECN signals of 304L SS without CE show some transient peaks of different time scales at the beginning of immersion. It indicates that both the initiation and the annihilation of pitting occurred frequently on the surface of 304L SS. However, the EN signals of the sample without CE were relatively stable after immersion for 3 h, showing typical passivation characteristics. It implies that a complete passive film was formed on the surface of 304L SS [13]. After CE for 0.5 and 1 h, the passive film formation time was gradually shortened. For the sample after CE for 1.5, 2, and 3 h, the passivation period was about 0.4, 0.6, and 0.8 h, respectively, which means that the time required to form a layer of the passive film gradually increased. For the samples with 5 h and 8 h CE, the passivation performance was significantly weakened, making it difficult to form a passive film layer. The results of EPN and ECN indicate that 304L SS with 1 h CE had the best passivation ability.
Fig. 8 shows the energy distribution plots (EDP) of the current noise of 304L SS after different CE times. It is generally known that the initiation, growth, and annihilation of metastable pitting precede stable pitting, and the activities of metastable pitting are much faster than ion diffusion or removal of corrosion products [41–42]. The fast and slow processes of corrosion events correspond to a small timescale and a large time scale, respectively. The time scale of crystal d is in an inceasing series from d1 to d8. Therefore, the relative energy in d1–d3, d3–d6, and d6–d8 represents the pitting initiation (passivity), metastable pitting growth, stable pitting growth, or diffusion control, respectively. The corrosion evolution of 304L SS after different CE times could be divided into two different stages. The main feature of the sample after different CE times was that the relative energy accumulation was mainly distributed in the crystal d6–d8 at the initial stage of immersion (the first stage), which indicates that the passive film was gradually formed on the surface of samples [42–43]. In addition, the passive film stability of CE samples with different surface damage degrees was different. There was a transition of the relative energy accumulation from d1–d3 to d6–d8, which indicates that the signal of stable pitting existed on the sample surface. The relative energy mainly accumulated in d1–d3 at the later stage of immersion (the second stage), which implies the presence of a relatively complete passive film on the surface of samples. With regard to the sample prior to CE, the relative energy was randomly distributed in d1–d8 before 2 h immersion, which reflected the growth/annihilation process of metastable pitting on the sample surface. This may be attributed to the unstable growth of the passive film caused by the inherent defects of the sample. After CE for 0.5 and 1 h, the relative energy accumulation time of d6–d8 region decreased to 1.2 h and 0.2 h (the sample was in a passive state before immersing for 0.6 h), respectively, indicating that the passivation ability of the material was improved during the incubation period. For the samples undergoing 1 h to 5 h CE, the time that the relative energy mainly accumulated in the d6–d8 region continuously increased from 0.2 to 3 h. In the rising period, the increase in passive film formation time indicates that the passivation ability of the material gradually decreased. In the stable period, the accumulation time of relative energy in the d6–d8 region after CE for 8 h was lower than that after CE for 5 h, implying that the passivation ability of the material was improved after 8 h CE.
Fig. 9 shows the frequency (fn) and charge (q) of events of 304L SS in 3.5wt% NaCl solution after different CE times. The increase of fn indicates that more corrosion events occurred on the metal surface and the corrosion morphology tended to be uniform corrosion; by contrast, the decrease in fn makes known that corrosion morphology tended to be localized corrosion. Concerning q, the increasing value implies that the amount of electricity released by each corrosion event was large and the corrosion morphology tended to be localized corrosion; on the contrary, its corrosion morphology tended to be in uniform corrosion or passive state [44–46]. Therefore, it can be considered that the high fn and low q represent uniform corrosion, the low fn and high q correspond to localized corrosion, the high fn and high q represent severe non-uniform overall corrosion, and the low fn and low q correspond to the passive state. Compared with the samples without CE, the samples after CE for 0.5 h and 1 h had lower values of fn and q, indicating that the passivation ability of the material was enhanced and the localized corrosion was weakened. The fn of the samples gradually increased while q remained nearly unchanged after CE for 1–3 h, demonstrating that the number of corrosion events gradually increased. The values of fn and q increased significantly after CE for 5 h and 8 h, indicating that severe localized corrosion occurred on the sample surface, which can be related to the seriously damaged passive film on the sample surface. The above results indicate that the changes in frequency and charge of local corrosion events after different CE times could be closely related to the development of pitting corrosion on the surface of the sample.
To investigate the effect of different CE times on the pitting corrosion generation and growth of 304L SS, Weibull and Gumbel analyses were performed on the noise signals. Fig. 10 is the Weibull distribution of the incubation rate of pitting initiation of 304L SS after different CE times. In Fig. 10(a), the slope of the high-frequency linear region was related to passivation, while the slope of the low-frequency linear region was correlated with pitting corrosion. The shape parameter (m) and the scale parameter (n) were obtained by fitting the low-frequency curve, which could be substituted into Eq. (9) to obtain the incubation rate of pitting (Fig. 10(b)). The results show that compared with the samples without CE, the incubation rate of pitting initiation gradually increased after CE for 0.5 h and 1 h. However, the incubation rate of pitting initiation continued to decline after CE for 1 h and reached the minimum rate after 3 h CE. With regard to the samples after 5 h and 8 h CE, the incubation rate of pitting initiation rose again. The results of these changes may be attributed to the further development of initial pitting.
Fig. 11 is the Gumbel distribution curve of 304L SS in 3.5wt% NaCl solution after CE various times. As seen in Fig. 11(a), two linear regions could be observed, and the distribution of charge from the smallest to the largest corresponded to the passive region and the pitting region, respectively. Eqs. (12)–(14) were used to calculate α and μ of pitting parameters under different CE times. Fig. 11(b) shows the growth probability (Pc) of pitting for the sample after different CE times under a given value of q. The results show that the growth probability of the pitting of the samples after 0.5 h and 1 h CE was lower than that of the samples without CE. For the samples after 1–3 h CE, the growth probability of the pitting increased slightly with the rising CE time. Extending the CE time to 5 h and 8 h, the growth probability of pitting increased substantially.
Based on the results of shot noise data, it can be found that the incubation rate of pitting initiation on the sample surface increased after CE for 0.5 h and 1 h compared with the samples without CE, while the growth probability of pitting decreased, which indicates that the sample surface was dominated by pitting initiation (Fig. 12(a)). This phenomenon may be attributed to the absence of obvious defects on the surface of the sample during the incubation period, and pitting initiation occurred at the energy concentration of the slip band and grain boundary. For the samples after 1–3 h CE, the incubation rate of pitting initiation gradually decreased, and the growth probability of pitting slightly increased. Hence, the charge of the corrosion behavior had not changed significantly, which could be attributed to the fact that the initial pitting at the surface defect was more likely to develop into metastable pitting, and good passivation ability inhibited the growth of stable pitting. For example, the metastable pitting can be clearly seen on the surface of the sample after 1.5 h CE (Fig. 12(b)). With regard to the samples after CE for 3 h to 5 h, the incubation rate of pitting does not change much and the growth probability of pitting increases significantly, indicating that more metastable pitting on the sample surface develops into stable pitting (Fig. 12(c)). Both the incubation rate of pitting initiation and the growth probability of pitting were dramatically increased when the CE time was extended to 5–8 h, which was resulted from the serious CE damage on the whole surface. At this stage, a large number of initially-formed pitting developed into stable pitting, causing serious localized corrosion on the sample surface (Fig. 12(d)).
To obtain an appropriate polarization potential for potentiostatic polarization tests, the potentiodynamic polarization curve of 304L SS in 3.5wt% NaCl solution was measured (Fig. 13(a)). Based on the potentiodynamic polarization curve, an intermediate polarization potential of 0.1 V vs. SCE was selected for potentiostatic polarization test. In addition, when the potential is higher than −0.53 V vs. SCE, the current density (i) of 304L SS increases rapidly, which may be due to the oxygen absorption reaction on the material surface. Sabzi et al. [47–48] also found that X60 and X70 pipe steel also show this phenomenon in H2S, which is believed to be caused by a hydrogen evolution reaction on the surface of materials in H2S. Fig. 13(b) shows the i–tp response of 304L SS in 3.5wt% NaCl solution. The decrease and the increase in the current density were related to the formation of the passive film and the growth of pitting, respectively [21,49]. In the incubation period of CE, no obvious metastable pitting peaks suggestthat a stable passive film was formed on the surface of 304L SS. During the rising period of CE, a large number of metastable pitting peaks grew and annihilated simultaneously after 1.5 h and 2 h CE. The occurrence time of the pitting peak was shortened, and the peak current density increased gradually with the extension of CE time, indicating the weakening passivation ability of materials. This could be attributed to the increasing surface defects of the sample. After CE for 3 h, the current density gradually increased with time, which may be due to the significantly reduced passivation ability comparable to the depassivation ability. At the stable period, the overall current density became the largest for the sample after 5 h CE, implying the worst passivation ability. However, the current density of the sample after CE for 8 h was lower than that after 5 h CE, which implies that the passivation performance of the material was improved at this stage. The passivation ability of materials could be evaluated by the following equations [21]:
|
i(t)=G×t−Kp |
(16) |
|
lgi(t)=lgG−Klgtp |
(17) |
where i(t) is the current density, G is a constant, tp is the time of the potentiostatic polarization test, and K is the passivation index. The value of K is the slope of the linear region in Fig. 13(c). It is well known that the parameter K can indirectly indicate the formation rate of the passive film [49–50]. K with a positive value represents the growth of passive film, but K with a negative value corresponds to pitting growth [21,51]. Fig. 13(c) shows the logarithmic curve of the passivation current density of 304L SS with time. The result show that the curve had two obvious stages before 2 h CE, while the third stage appeared after CE for 3 h. In the third stage, the slope of the double logarithmic curve was positive, indicating that pitting continued to grow on the surface of the sample since the passive film could not be repaired in time. Fig. 13(d) shows the change of K in the first two stages of lgi vs. lgt after different CE times. The specific K values in Fig. 13(c) are shown in Table 1. According to the results of the K value, it is found that the changes of K of passive film at the first stage after different CE times were consistent with the results of wavelet analysis. However, the K values of the passive film changed dramatically in the second stage. Under the action of applied potential, the K values of passive film at the second stage increased before 2 h CE compared with that at the first stage, which implies that the passivation ability of the sample was much higher than the depassivation ability. For the cases with more than 3 h CE, in addition to the first two stages, the K values of the passive film decreased remarkably under the applied potential, indicating that the passivation ability of the material was close to the depassivation ability. It corresponded to the growth of pitting at the third stage.
| CE time / h | K1 (1st stage) | K2 (2nd stage) | K3 (3rd stage) |
| 0 | 0.163 | 0.745 | — |
| 0.5 | 0.273 | 0.447 | — |
| 1 | 0.297 | 0.585 | — |
| 1.5 | 0.274 | 0.568 | — |
| 2 | 0.268 | 0.545 | — |
| 3 | 0.266 | 0.190 | −2.17 |
| 5 | 0.255 | 0.100 | −1.78 |
| 8 | 0.281 | 0.012 | −2.55 |
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CSV
Essentially, an antagonistic effect between passivation and depassivation existed in the corrosion process of 304L SS in 3.5wt% NaCl solution. During the incubation period, the passivation ability of the sample was dominant. The surface of 304L SS without CE was smooth, while the initial passive film was poor. Based on the results of wavelet analysis and potentiostatic polarization, it could be inferred that the passivation ability of 304L SS increased in the incubation period of CE, which can be attributed to the fact that the CE pulse stress was easy to form the compressive stress on the sample surface, which delayed the initiation of surface cracks and slowed down the propagation of microcracks in depths [52–53]. On the other hand, some twins were produced in 304L SS after CE, and the increasing twin grain boundaries could lead to an increase in corrosion resistance [36,54–56]. The results of shot noise show that the major corrosion characteristic of the sample during the incubation period was the initiation of pitting, which is closely related to the dislocation accumulation effect, causing a large number of slip bands and protruding grain boundaries on the surface [57]. However, the passivation ability of the sample was much higher than the depassivation ability, which inhibited the further development of initially-formed pitting.
During the rising period of CE, the passivation ability of the sample decreased and the depassivation ability increased. According to the results of wavelet analysis and potentiostatic polarization, it is obvious that the passivation ability of the sample after 1–3 h CE was much higher than the depassivation ability, and the passivation ability of the sample after 3 h CE was close to the depassivation ability, while the depassivation ability of the sample after 5 h CE was stronger than the passivation ability. The results of shot noise and potentiostatic polarization show that the initially-formed pitting on the sample surface developed into metastable pitting after CE for 1–3 h, and the main corrosion characteristics were the growth of metastable pitting. After CE for 3–5 h, the metastable pitting further grew into stable pitting, and serious localized corrosion occurred on the surface of the samples. These changes could be attributed to both the evolution of surface morphology and the increase of deformation-induced martensite [58–60]. The continuously increasing surface defects led to the rising roughness. Meanwhile, the enhanced content of deformation-induced martensite reduced the plastic deformation ability of 304L SS. The combined action of the two aspects weakened the passivation ability and accelerated the depassivation ability of 304L SS.
At the stable period of CE, depassivation was predominant for 304L SS. According to the results of wavelet analysis and potentiostatic polarization, it is clear that the passivation ability of 304L SS deteriorated after CE for 5 h and it improved after 8 h CE again. The results of shot noise show that the major corrosion characteristics were serious localized corrosion at this period. A large amount of deformation-induced martensite was produced and serious surface damage occurred after 5 h CE, resulting in a sharp decline in passivation ability and a significant increase in depassivation ability. However, the passivation ability of 304L SS was improved after 8 h CE. It could be attributed to the decreasing martensite content and the increasing exposure surface of the fresh metal substrate, and even grain refinement [36,61–62], which restrained the growth of stable pitting to a certain extent.
In this work, the effect of CE-induced surface damage on the pitting and the passive behaviors of 304L SS was investigated by EN and potentiostatic polarization. CE-induced surface damages had a significant impact on the pitting behavior of 304L SS. The change in the pitting behavior after different CE times was related to the antagonism effect between passivation and depassivation. The main conclusions could be drawn as follows.
(1) The passivation ability of 304L SS was much greater than that of depassivation during the incubation period of CE. The major corrosion characteristic of the sample surface was pitting initiation since the strong passivation ability inhibited the pitting growth.
(2) At the rising period of CE, the passivation ability of the sample gradually decreased with the increasing CE time. For the samples with 1–3 h CE, the passivation ability was higher than the depassivation ability, so the surface of the samples was mainly characterized by metastable pitting growth. After CE for 3–5 h, the passivation ability of the samples was further weakened due to more serious surface damage, which was lower than the depassivation ability, thus metastable pitting on the sample surface began to grow into stable pitting.
(3) At the stable period of CE, the depassivation ability of the sample was predominant, and serious localized corrosion occurred on the surface of the sample.
This work was financially supported of the National Natural Science Foundation of China (Nos. 52101105 and 51975263).
The authors declare no competing financial interests.
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Figures(13) / Tables(1)
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| CE time / h | K1 (1st stage) | K2 (2nd stage) | K3 (3rd stage) |
| 0 | 0.163 | 0.745 | — |
| 0.5 | 0.273 | 0.447 | — |
| 1 | 0.297 | 0.585 | — |
| 1.5 | 0.274 | 0.568 | — |
| 2 | 0.268 | 0.545 | — |
| 3 | 0.266 | 0.190 | −2.17 |
| 5 | 0.255 | 0.100 | −1.78 |
| 8 | 0.281 | 0.012 | −2.55 |
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