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Nov 05, 2024

Effect of Mo and Sn co-regulation on low alloy steel corrosion in tropical marine atmosphere | npj Materials Degradation

npj Materials Degradation volume 8, Article number: 92 (2024) Cite this article 437 Accesses 1 Altmetric Metrics details The influence of co-regulating Mo and Sn on the corrosion resistance of low

npj Materials Degradation volume 8, Article number: 92 (2024) Cite this article

437 Accesses

1 Altmetric

Metrics details

The influence of co-regulating Mo and Sn on the corrosion resistance of low alloy steel in tropical marine atmospheric was investigated. The combined addition of Mo and Sn has been found to significantly improve the corrosion resistance of low alloy steel, augmenting the protective capabilities of the rust layer. This combined addition promotes the formation of protective compounds like α-FeOOH and FeCr2O4 within the alloy rust layer. Furthermore, it facilitates the conversion of Cr, Ni and Cu into corrosion-resistant oxides such as Cr2O3, NiFe2O4 and CuO, thereby enhancing the density of the rust layer. Additionally, as corrosion progresses over time, higher levels of Sn addition lead to increased Sn content within the inner rust layer, consequently bolstering the protective qualities of the rust layer. This comprehensive understanding sheds light on the synergistic effects of Mo and Sn in fortifying the corrosion resistance of low alloy steel, offering insights for the development of advanced corrosion-resistant materials in marine environments.

Low alloy steel is extensively employed in various industries, including offshore platforms, island and reef construction, as well as bridge infrastructure, owing to its excellent formability and resistance to atmospheric corrosion1,2,3. Nevertheless, when exposed to demanding conditions characterized by high temperatures, elevated humidity and intense salt spray, its corrosion phenomenon4,5,6,7,8 is still relatively severe.

In recent years, the optimization of the corrosion resistance of traditional low alloy steel has attracted widespread attention from scholars. Cr, as one of the world’s recognized major corrosion-resistant elements, has been extensively researched9,10,11. Studies12 have shown that with the increase of Cr content in steel, the uniform corrosion resistance of steel in harsh tropical marine atmospheric environments also significantly improves, but it is accompanied by the phenomenon of vertical development of pits under the rust, posing a great threat to the long-term safe service of low alloy steel. Therefore, without reducing the original uniform corrosion resistance of low alloy steel, further optimizing the overall performance of the rust layer, hindering the infiltration of corrosive Cl−, and inhibiting the formation of an acidic environment under the rust has become an urgent problem to solve in optimizing the corrosion resistance of low alloy steel.

Microalloying, as the mainstream research method for optimizing the performance of steel materials, is widely used7,13,14. Research works15,16 have shown that both Mo and Sn can promote the formation of α-FeOOH, thereby improving the protectiveness of the rust layer. In addition, Mo and Sn are recognized as corrosion-resistant elements, and trace additions can effectively improve their localized corrosion resistance in acidic environments17,18,19,20. Zhang et al.21 found that Sn can increase the release potential of hydrogen, which is conducive to inhibiting the hydrogen evolution reaction, thereby effectively improving the overall corrosion resistance of ferritic stainless steel in H2SO4. Kamimura22 reported that the dissolution of Sn at local anodic sites can inhibit the anodic reaction and hydrolysis reaction. Hao23 research found that in a simulated cargo oil tank bottom environment, compared with carbon steel, the corrosion resistance of low alloy steel with the sole addition of Sn and the composite addition of Mo and Sn improved by 20% and 37.5%, respectively. His research shows that uniformly distributed metal Sn and Mo can improve the corrosion resistance of steel by inhibiting the anodic dissolution of ferrite and the cathodic hydrogen evolution reaction on the residual Fe3C, and inhibiting the current effect.

In conclusion, it is theoretically feasible to inhibit the acidification of the local microenvironment under rust by adding Mo and Sn. However, in the face of harsh service environments of high temperature, high humidity and high salt spray, there are currently no reports on the research of the addition of Mo and Sn to low alloy steel for corrosion resistance. Whether there is a synergistic effect between Mo and Sn is still unknown, and whether the targeted design of micro-alloy element synergistic systems can achieve the goal of optimizing the rust layer performance still requires a large amount of experimental discussion.

Therefore, this study fabricated four variations of low alloy steel with varying Mo and Sn compositions. The microstructure of the low alloy steel was assessed using metallographic microscopy and scanning electron microscopy (SEM). The influence of Mo and Sn on the corrosion behavior and corrosion resistance mechanism of low alloy steel within a tropical marine atmospheric environment was examined through electrochemical experiments, dry/wet cycle corrosion experiments, and microscopic characterization experiments of corrosion products. The research findings are anticipated to lay the theoretical and experimental groundwork for the development of corrosion-resistant low alloy steel.

Figure 1a–d displays the SEM microstructure of the four experimental steels. The 1M steel, when Mo is added exclusively, is predominantly characterized by a typical granular bainite structure, primarily composed of bainitic ferrite and island-like or granular carbon-rich phases. When adding Sn, the sample exhibits a typical lath-like bainitic structure, primarily composed of bainitic ferrite and lath-like carbon-rich phases. Upon the combined addition of Mo and Sn, the microstructure manifests as a mixed composition, with a predominant presence of lath-like bainite and a supplementary occurrence of granular bainite.

a–d SEM microstructure 1M, 1S, 1MS and 6MS steel, respectively. e–h EBSD analysis of 1M, 1S, 1MS and 6MS steel, respectively. The grain size and the percentage of high-angle grain boundaries measured by EBSD are annotated.

Figure 1e–h presents the EBSD analysis results of the four types of experimental steels. As can be seen from the IPF maps, the addition of Mo and Sn has no significant effect on the grain orientation of the steel samples. From the grain size and high-angle grain boundary statistical results, the average grain sizes of the four steels are similar, ranging from 7.5 to 9 μm. The 6MS steel has a slightly smaller average grain size than the other three steels.

Studies24 indicate that due to the low melting point of Sn, it tends to segregate toward inclusions and defects, adversely affecting the overall performance of the steel. Figure 2 shows the energy dispersive spectroscopy (EDS) results of inclusions in the four types of steel. The inclusions in the steel consist of composite oxides of Al, Mg, Si and Ca. No segregation of Sn and Mo was observed around the inclusions, and their impact on the overall corrosion resistance performance can be neglected.

a 1M, b 1S, c 1MS and d 6MS.

Figure 3a presents the dynamic potential polarization curves of the four types of experimental steels in tropical marine atmospheric simulation fluid. There is little difference in the cathodic curves of the four steels, with the polarization curve of 1M steel being the farthest to the right, indicating a significantly lower corrosion resistance. The anodic and cathodic polarization curves of 1MS and 6MS steels both slightly shift to the left, implying that the combined addition of Mo and Sn can inhibit both the anodic dissolution of the steel and the de-polarization process of oxygen. However, when the Sn content increases to 0.6 wt%, the anodic polarization curve slightly shifts to the right, indicating that excessive addition of Sn inhibits the initial corrosion anodic reaction in the steel.

a Dynamic potential polarization curves; b corrosion potential (Ecorr) and corrosion current (icorr). The error bar is the standard deviation of three electrochemical curves; c Nyquist curves and equivalent circuit diagram for fitting curves (Rs is the solution resistance, Qf and Rf are the constant phase element and resistance of the corrosion product film, respectively. Qdl and Rct are the constant phase elements of the surface double layer and the charge transfer resistance of the steel, respectively). d Bode plots.

The Tafel fitting results of the polarization curves for the four steels are shown in Fig. 3b. Comparing the corrosion potential (Ecorr), it is evident that the combined addition of Mo and Sn significantly increases the surface potential compared to individual additions. The addition of Mo and Sn can enhance the corrosion resistance of low alloy steel. The icorr of 1S steel is slightly lower than that of 1M steel, indicating that the effect of Sn addition alone in reducing the corrosion rate of steel is superior to that of Mo addition alone. With the combined addition of Mo and Sn, the icorr of 1MS and 6MS steels significantly decreases, particularly for 1MS steel, suggesting that the combined addition of Mo and Sn effectively enhances the corrosion resistance of the steel.

Figure 3c, d presents the Nyquist and Bode plots of the four types of experimental steel in the tropical marine atmospheric simulation fluid. The four types of steel show the same shape of the capacitive reactance arc, and the radius of the capacitive reactance arc of 1MS steel is the largest, followed by that of 6MS steel. This suggests that the combined addition of Mo and Sn significantly enhances the corrosion resistance of the steel. However, the excessive addition of Sn results in a slight decrease in original corrosion resistance.

The corrosion weight loss and corrosion rates of the four experimental steel types were calculated, the results are presented in Fig. 4a, b. As Fig. 4a illustrates, the corrosion weight loss for all four steel types increases as the corrosion time progresses. Notably, 1M steel exhibits the most severe corrosion, followed by 1S steel. When both Mo and Sn are added to the steel, the weight loss of 1MS steel is initially less than that of 6MS steel, but as corrosion continues, 1MS steel surpasses 6MS steel in weight loss. Similarly, the corrosion rate decreases as the corrosion time extends, with 1M steel showing the highest corrosion rate, followed by 1S steel. The initial corrosion rate of 1MS steel is the lowest, but over time, 6MS steel exhibits the lowest corrosion rate, observed at 567 h.

a Corrosion weight loss. The error bar is the standard deviation of three measurement results; b corrosion rate derived from corrosion weight loss; c cross-sectional morphology after 72 and 576 h of corrosion. The area marked by the yellow dashed line represents the relatively dense inner rust layer, while the area marked by the pink dashed line indicates the loosely structured outer rust layer.

Both corrosion weight loss and corrosion rate adhere to a power exponential function (V = Atn)12,25,26,27,28, with the fitting results for corrosion weight loss provided in Table 1. In this power function, a lower functional exponent ‘n’ signifies a more effective protective quality of the rust layer on the low alloy steel. As shown in Table 1, except for 1M steel, ‘n’ values for the other three Sn-containing steel types are all ~0.5, indicating that the influence of Sn on the rust layer is notably more significant than that of Mo. When Mo and Sn are combined, particularly as the Sn content increases, the ‘n’ value decreases further. This suggests that the synergistic impact of Mo and Sn substantially augments the rust layer’s protective properties, reduces the steel’s corrosion rate, and becomes more pronounced with higher Sn content.

During long-term corrosion, the protective function of the rust layer is crucial. Figure 4c shows the cross-sectional morphology at different periods for the four types of experimental steel after the completion of the dry/wet cycle corrosion experiment. It can be observed that all four types of steel exhibit a double-layer structure from the beginning of corrosion, namely, a relatively dense inner rust layer (area indicated by yellow dashed line) and a loosely structured outer rust layer (area indicated by pink dashed line). After 72 h of corrosion, the ranking of the thickness of the inner rust layer is as follows: 1M > 1S > 6MS > 1MS, consistent with the order of corrosion rate. With prolonged corrosion time, the thickness of the inner rust layer increases, enhancing its protective effect on the substrate, leading to a reduction in the corrosion rate of the alloy. Referring to the work of Pattnaik et al.29, the inner layer is the stable α-FeOOH, while the outer layer comprises γ-FeOOH and Fe3O4.

Compared to thickness changes, the addition of elements has a more significant impact on the structure and composition of the rust layer. After 72 h of corrosion, noticeable cracks can be seen in the inner rust layers of all four types of steel, indicating that the rust layers of the four types of steel are relatively brittle in the early stage of corrosion, and a dense rust layer structure has not yet formed, with the rust layer defects of 1M steel being more pronounced. As corrosion continues, the cracks in the inner rust layer significantly decrease, suggesting that the rust layers of all four types of steel exhibit good stability and compactness. At the interface of 1M steel, there are slight pores, and the cracks in the rust layer present a growth pattern perpendicular to the base, providing a direct path for corrosive media, damaging the protective nature of the rust layer. On the other hand, there are no obvious defects at the interface of 1S steel, and the cracks do not have a clear growth direction, indicating that the addition of Sn alone improves the compactness of the rust layer more than Mo. With the combined addition of Mo and Sn, especially in 6MS steel, as corrosion time extends, the growth of the inner rust layer is uniform, with almost no visible defects, and it is tightly bonded to the base. This suggests that the combined addition of Mo and Sn is more conducive to the formation of a dense rust layer, and this effect becomes more pronounced with the further addition of Sn.

To more clearly demonstrate the changes in element content in the rust layers of the four types of Mo–Sn steel, EDS analysis was used to quantitatively characterize the content of the main elements in the inner rust layer, as shown in Fig. 5. The Cr content in the rust layers of 1M and 1S steel does not differ significantly, both being around 15 wt%, but the Ni and Cu content in 1S steel slightly increases, suggesting that Sn can promote the enrichment of Ni and Cu in the inner rust layer, while the Cl content slightly decreases. With the combined addition of Mo and Sn, the alloy element content in 1MS and 6MS steel increases, where the changes in Cr and Ni content do not follow an obvious pattern over time. The results indicate that the content of each alloy element in the inner rust layer of 1MS and 6MS steel is much higher than its own content in the base, suggesting that the combined addition of Mo and Sn promotes the enrichment of alloy element (Cr, Ni, Cu, Mo and Sn) products in the inner rust layer. Comparing the elemental distribution of 1MS and 6MS in Fig. 5c, d, the additional addition of Sn can promote further enrichment of various alloy elements in the steel, thereby enhancing the protective role of the rust layer. After 72 h of corrosion, the Sn content in the inner rust layer of 6MS steel is consistent with that of 1MS steel. However, with prolonged corrosion time, the Sn content in the rust layer of 6MS steel becomes significantly greater than in 1MS steel. This substantial enrichment of Sn in the inner rust layer after extended corrosion markedly improves the corrosion resistance of the alloy.

a 1M, b 1S, c 1MS and d 6MS. The error bar is the standard deviation of three measurement results.

X-ray diffraction (XRD) was used to analyze the phase of the rust layers of different Mo–Sn steels after the dry/wet cycle corrosion experiment, as shown in Fig. 6. The phase composition of the rust layers of the four types of steel is consistent, composed of Fe3O4, α-FeOOH, γ-FeOOH and NaCl, where NaCl primarily comes from the solution, and the phase composition does not change with the variation of corrosion time. The semi-quantitative analysis of the rust layer composition was carried out using the relative intensity ratio method3, and the α/γ* (α-FeOOH/γ-FeOOH + Fe3O4) ratio in each rust layer was calculated, as shown in Fig. 7. The content of α-FeOOH in the rust layer of all four steels increases with the extension of corrosion time. This indicates that both individual and combined addition of Mo and Sn can enhance the content of α-FeOOH, thereby improving the protective properties of the rust layer. However, in 1M and 1S steels, the content of Fe3O4 is unstable, increasing in the later stages of corrosion. In contrast, in 1MS and 6MS steels, which contain combined Mo and Sn additions, the Fe3O4 content gradually decreases with time, and the α-FeOOH content is higher than in 1M and 1S steels. This suggests that the combined addition of Mo and Sn can further promote the transformation of γ-FeOOH to more stable α-FeOOH, reducing the conversion to the metastable state of Fe3O4 and thereby enhancing the protective nature of the rust layer. After 576 h of dry/wet cycle corrosion experiment, the α/γ* value in the rust layer of 6MS steel reaches 38.5%, while that of 1MS steel is 36.9%. This indicates that the continued addition of Sn can further enhance the protective properties of the rust layer.

a 1M, b 1S, c 1MS and d 6MS.

a 1M, b 1S, c 1MS and d 6MS.

Further analysis of other alloy elements in the rust layer is performed through X-ray photoelectron spectroscopy (XPS). Figure 8a–f shows the XPS spectra of the Fe 2p3/2, Cr 2p3/2, Ni 2p3/2, Cu 2p3/2, Mo 3d and Sn 3d3/2 peaks in the inner rust layer of four types of Mo–Sn steels after 576 h of dry/wet cycle corrosion experiment. The Fe peaks at binding energies of 710.6, 711.7 and 713.1 eV are divided into three groups, corresponding to FeCr2O4, Fe3O4 and FeOOH, as shown in Fig. 8a. It indicates that compared to 1M and 1S steels, the peak intensities of FeOOH and FeCr2O4 in 1MS and 6MS steels are higher, while the Fe3O4 peak intensity is lower. This suggests that the combined addition of Mo and Sn promotes the presence of FeOOH and FeCr2O4 in the rust layer, which is consistent with the XRD results. Cr in the rust layer of the four types of Mo–Sn steels still exists in the forms of FeCr2O4, Cr2O3 and CrO3, indicating that the addition of Mo and Sn does not change the state of Cr in the rust layer. The Ni 2p3/2 spectrum is divided into three constituent peaks, corresponding to NiFe2O4 (855.3 eV), NiO (857.4 eV) and Ni(OH)2 (861.8 eV). Cu has a single constituent peak at a binding energy of 940.5 eV, representing CuO. Given the content of Cu in the rust layer, the amount of CuO is highest in 6MS steel, which is beneficial for enhancing the corrosion resistance of the rust layer. Due to the limitations of the content and uniformity in the rust layer, the products of Mo are only detected in 6MS steel, mainly existing as metallic Mo, MoO2 and MoO3. Products containing Sn were detected in both 1MS and 6MS steel, mainly present as SnO2.

a Fe 2p3/2, b Cr 2p3/2, c Ni 2p3/2, d Cu 2p3/2, e Mo 3d and f Sn 3d3/2 and proportion calculation of each phase in the rust layer: g Fe 2p3/2, h Cr 2p3/2 and i Ni 2p3/2.

Figure 8g–i presents the changes in the proportion of major alloy elements in the rust layers of the four types of Mo–Sn steel. As shown in Fig. 8g, 1M and 1S steel have the highest content of Fe3O4, while 1S steel has a slightly higher content of FeCr2O4 and FeOOH than 1M steel. This suggests that the addition of Sn alone, compared to the addition of Mo alone, is more beneficial for the formation of the more protective FeCr2O4 and α-FeOOH. With the combined addition of Mo and Sn, the Fe3O4 content in 1MS and 6MS steel significantly decreases, the FeCr2O4 content significantly increases, and the α-FeOOH content also increases, with the effect being more pronounced in 6MS steel. This indicates that the synergistic effect of Mo and Sn promotes the formation of protective substances in the rust layer. Similarly, the addition of Sn and the combined addition of Mo and Sn greatly promote the formation of Cr2O3, a Cr product in the rust layer. As a major corrosion-resistant material in the passive film of stainless steel30, Cr2O3 can also enhance the protectiveness of the rust layer in low alloy steel. In addition, as shown in Fig. 8h, the content of CrO3, which is harmful to the corrosion resistance of the rust layer, also significantly decreases with the combined addition of Mo and Sn. Figure 8i shows the changes in the proportion of Ni-containing products. The contents of NiFe2O4 and Ni(OH)2 in the four types of steel do not differ much, but the NiO content in 1S, 1MS and 6MS steel significantly decreases. This suggests that the addition of Sn and the combined addition of Mo and Sn can significantly promote the formation of protective substances NiFe2O4 and Ni(OH)2, and the effect of combined addition of Mo and Sn is more pronounced.

The Nyquist plots of the four types of Mo–Sn steel after 576 h of dry/wet cycle corrosion experiment were measured, as shown in Fig. 9a. The curves of the four steels are all composed of multiple capacitive arcs with different radii, indicating that multiple time constants appear in this system, and the rust layer undoubtedly plays a crucial role in its corrosion resistance mechanism. From the impedance arc radius after 576 h, it shows that the arc radius size follows: 6MS > 1MS > 1S > 1M. This order agrees well with the corrosion rates obtained from the corrosion weight loss results.

a Nyquist plots, and the 10 mHz point corresponding to the curve is marked. b Equivalent circuit (Rs is the solution resistance, Qf and Rf are the constant phase element and resistance of the corrosion product film, respectively. Qdl and Rct are the constant phase elements of the surface double layer and the charge transfer resistance of the steel, respectively). c Fitting results of Rs, Rf, Rct and Rtotal.

The electrochemical impedance spectra of the four types of Mo–Sn steel were fitted with the equivalent circuit31 shown in Fig. 9b. Rs represents the solution resistance, Qf and Rf represent the constant phase angle element and resistance of the rust layer, Qdl and Rct represent the double-layer constant phase angle element and charge transfer resistance at the substrate interface, respectively.

The magnitudes of Rs, Rf and Rct values are closely related to the protectiveness of the rust layer, so their fitting results are statistically analyzed, as shown in Fig. 9c and Table 2. The combined addition of Mo and Sn increases both the Rct and Rf values of the rust layer compared to individually adding Mo or Sn. This indicates that under the combined action of Mo and Sn, the rust layer is denser, resulting in greater diffusion resistance for ions and suppression of surface electrochemical processes. After 576 h, the total resistance of the rust layer of 6MS is greater than the other three alloys.

Using laser confocal technology, the 3D morphology of pits after corrosion of the four types of Mo–Sn steel with 72 and 576 h was analyzed, as shown in Fig. 10. It can be seen that in the early stages of corrosion, all four steels exhibit good corrosion resistance, and local areas still retain the mechanical processing traces from before the experiment. As corrosion progresses, a protective rust layer forms on the steel surface, and all four types of steel exhibit a uniform corrosion morphology. However, deep and narrow pits are still observable, especially in the 1M steel. The number of pits on the surface of 1S steel decreases, which suggests that the addition of Sn alone can obtain a denser rust layer compared to Mo, thereby reducing rust layer defects. By observing the two types of Mo–Sn composite added steels, it can be seen that the number of deep and narrow pits on the surface of 1MS and 6MS steel is significantly reduced, and the steel as a whole presents’ uniform corrosion characteristics. The above results indicate that the combination of Mo and Sn could alleviate the development of corrosion pits toward depth. Additionally, the pitting depth of 6MS is greater than that of 1MS, which may be related to the initial alloy microstructure and the diffusion of H+ in the rust layer.

The maximum depth of the pitting is marked.

According to the Tafel fitting results (Fig. 3b), it can be seen that adding 0.1 wt% Mo to the basis of 1S steel can effectively reduce the icorr of the steel, thus enhancing the corrosion resistance of the steel. This is because the non-equilibrium electrode potential of the Mo is −0.2 V, which is higher than the potentials of the major alloying elements Fe and Cr in steel. Therefore, the addition of Mo can cause a positive shift in the base potential32.

According to the cross-sectional morphology of the rust layer of 1M steel (Fig. 4c) and the alloy element content (Fig. 5a), it can be seen that the compactness of the rust layer gradually increases with the extension of time. When the time reaches 288 h, the presence of Mo can be detected in the rust layer. This implies that the addition of Mo is advantageous for the development of protective rust layers on the surface of the steel. However, due to its low content, Mo is only detected in the rust layer in the later stages of corrosion when Mo-containing products increase. E-pH diagrams are valuable tools in understanding and controlling the behavior of metals and other materials in aqueous environments33,34.

According to the E-pH diagram of the Fe–Cr–Mo–H2O system at 298.15 K (Fig. 11), under the experimental conditions, Mo mainly exists as MoO2 in the rust layer. As an insoluble oxide, it can effectively fill cracks and other defects in the rust layer, thereby enhancing the compactness of the rust layer35, as shown in Eqs. (1) and (2). In addition, as can be seen from the XRD results in Fig. 7, the addition of Mo can promote the formation of α-FeOOH in the rust layer, thereby further enhancing the protection of the rust layer.

The yellow area within the red dashed lines represents the main reaction region, and the product phases of each region are labeled on the right.

Literature points out36,37,38 that Mo produces MoO42− in solution. As a typical anodic inhibitor, it preferentially adsorbs onto the steel surface, reducing the adsorption sites for Cl−, and inhibiting the active dissolution of the steel. In addition, near existing pits, it can inhibit further expansion of the pits, and the combined effect leads to the enhancement of the steel’s localized corrosion resistance by Mo39. However, as can be seen from Fig. 11, MoO42− can only form in near-neutral or high pH environments, and cannot stably exist under the solution conditions of this experiment, which is consistent with XPS results. Regardless of whether Mo is present in the rust layer in the metallic state or oxidized state, it can enhance the resistivity and densification degree of the rust layer, thereby improving the protection of the rust layer. Therefore, the addition of Mo mainly serves to slow down the trend of pit longitudinal development by improving the performance of the rust layer, rather than its own products having an inhibitory effect on the base. Furthermore, the addition of Mo in steel can promote the formation of FeCr2O4 and Ni(OH)2 products in the rust layer, indicating that Mo and Cr have a certain synergistic effect, facilitating the conversion of alloy elements in the rust layer into corrosion-resistant products, thereby further enhancing the protective properties of the rust layer.

Based on the results of the dynamic potential polarization curve, the addition of Sn mainly inhibits the anodic polarization process of steel and has little effect on the cathodic process. This suggests that the addition of Sn can inhibit the anodic dissolution process of steel, which is clearly related to its more positive non-equilibrium electrode potential (−0.138 V).

According to the corrosion rate results, 1S steel exhibits better corrosion resistance than 1M steel, indicating that the impact of Sn on the rust layer is greater than that of Mo. From the perspective of the rust layer cross-section, compared with 1M steel, the defects in the rust layer of 1S steel are significantly reduced, and the compactness of the rust layer gradually increases with time. According to XRD results in Fig. 7, Sn can increase the content of α-FeOOH, which has been confirmed in the literature40. From the elemental distribution, due to the addition of Sn, the contents of Cr, Ni and Cu in the rust layer also increase. Combined with the XPS results, the contents of excellent corrosion-resistant FeCr2O4, Cr2O3, NiFe2O4 and Ni(OH)2 in the rust layer are all higher than those in 1M steel. This suggests that Sn can promote the formation of products of other alloy elements in the steel. According to the E-pH diagram of the Fe–Cr–Sn–H2O system at 298.15 K (Fig. 12), under the experimental conditions, Sn mainly exists in the rust layer in the form of SnO2. As an insoluble stable oxide, it can not only effectively fill defects in the rust layer, thereby enhancing the compactness of the rust layer, but also enhance the ability of the rust layer to resist the intrusion of corrosive media. Therefore, the pore resistance and charge transfer resistance of the rust layer increase24,41, as shown in:

The yellow area within the red dashed lines represents the main reaction region, and the product phases of each region are labeled on the right.

The dissolved Sn2+ can undergo hydrolysis in solution and further react with Cl− to form insoluble chlorides. This substance adheres to the anodic dissolution area, hindering further corrosion of the steel. On the other hand, Fe3+ and Cr3+ will continue to undergo hydrolysis reactions, reducing the local pH. However, due to the simultaneous occurrence of multiple element hydrolysis reactions, a competitive effect of H+ production occurs, mutually inhibiting each other, which actually improves the local pH value, thereby inhibiting the pit growth of steel under the rust layer, as shown in:

Based on the electrochemical analysis (Fig. 3), it can be seen that compared to 1M and 1S steel, the corrosion current density of 1MS and 6MS steel with combined Mo and Sn additions are lower, indicating that the combined addition of these two elements can effectively improve the corrosion resistance of the steel. According to XRD and XPS results, the combined addition of Mo and Sn in steel promotes the transformation of γ-FeOOH in steel to thermodynamically stable α-FeOOH. This promotion effect is significantly higher than that of 1M and 1S steel, especially for 6MS steel, where the protective factor α/γ* of its rust layer reaches 38.5%. The combined addition of Mo and Sn causes more Cr to dope into Fe3O4, thereby improving its stability. In addition, the products of Cr and Ni are also converted more into corrosion-resistant Cr2O3 and NiFe2O4, and the conversion effect becomes more obvious with the increase of Sn content. According to the E-pH diagram of the Fe–Mo–Sn–H2O system at 298.15 K (Fig. 13), under the experimental conditions, the combined addition of Mo and Sn does not change their existence forms, and they still produce MoO2 and SnO2, respectively. Comparing with Fig. 11 and Fig. 12 reveals that the addition of Sn and Mo enhances the corrosion resistance of low alloy steel consistently with Cr. As can be seen from Fig. 8e, due to the limited content and uneven distribution, MoO2 is not detected in 1MS steel, while 6MS steel clearly shows the presence of Mo-containing products, indicating that the addition of Sn can promote the uniform distribution of Mo in the inner rust layer and the formation of more Mo-containing products.

The yellow area within the red dashed lines represents the main reaction region, and the product phases of each region are labeled on the right.

In the short corrosion time, the depth of corrosion pits is primarily related to the protective nature of the rust layer. Among the four alloys, 1MS steel exhibits the strongest protective effect of the rust layer, with the shallowest and least numerous corrosion pits. For the two types of Mo–Sn steel with different Sn additions, at the initial stage of corrosion when the steel surface has not yet formed a complete rust layer, 1MS exhibits better corrosion resistance. This may be related to the structural differences between the two, where 1MS steel shows a uniform and fine bainite structure, while the bainite structure of 6MS steel is significantly coarser, the size of the carbon-rich phase increases, the uniformity of the steel decreases, and the corrosion resistance of the matrix is damaged. With the growth of the rust layer on the steel surface, the corrosion rate of 6MS steel begins to be lower than that of 1MS steel, indicating that the increase of Sn content has a more significant effect on the protection of the rust layer in the later stages of corrosion. However, due to the increase in Sn content, the inhibitory effect of 6MS steel on the longitudinal development of pitting corrosion decreases. This may be due to the excellent protection of the 6MS steel rust layer, which makes the mass transfer process inside and outside the rust layer more difficult. The content of Fe3+, Cr3+, Sn2+ and Cl− at the interface continues to increase, while the hydrolysis product H+ cannot diffuse outward from the rust layer, leading to a more adverse microenvironment under the rust, and the steel exhibits a trend of developing in depth.

Four variations of low alloy steel with distinct micro-alloy element compositions were prepared by independently introducing Mo, Sn and a combined addition of both Mo and Sn to the base low alloy steel, as detailed in Table 3. Apart from the introduced Mo and Sn, the content of other elements remained largely uniform. To provide a clearer distinction between the four steel types, they were assigned numerical designations based on differences in Mo and Sn content within the steel.

A 10 mm × 10 mm × 3 mm sample was cut for structural observation. The sample was ground step by step with SiC sandpaper to 2000#, then polished sequentially with 1.5 and 0.5 μm polishing paste, and rinsed with deionized water and alcohol before being dried with cold air. The polished samples were observed for inclusions under the FEI Quanta 250, and the element distribution was determined in combination with EDS. After the polished samples were etched for 10 s with 4 vol% nitric alcohol, the microstructure of the experimental steel was observed through metallographic microscopy and SEM. The crystallographic information of the experimental steel was analyzed using EBSD. The samples for EBSD test were electropolished after mechanical polishing. The electropolishing solution was a 10 vol% perchloric acid + 90 vol% ethanol solution42,43,44. The polishing voltage and time were 25 V and 10 s, respectively. The EBSD test scan step size was 0.3 μm, and the voltage was 30 kV. Analysis was subsequently performed using OIM 7.3 software.

Electrochemical tests were conducted using a traditional three-electrode system, where the experimental steel served as the working electrode with dimensions of 10 mm × 10 mm × 3 mm, a platinum sheet as the auxiliary electrode, and a saturated calomel electrode as the reference electrode. After spot welding the copper wire to the back of the working electrode, it was embedded with epoxy resin while preserving a working area of 1 cm2. The working surface was ground to 2000# with sandpaper, then swiftly dried after washing with deionized water and alcohol. The area of the auxiliary electrode is 4 cm2. The electrochemical test solution was a tropical marine atmospheric simulation solution45, composed of 0.1 wt% NaCl + 0.05 wt% CaCl2 + 0.05 wt% Na2SO4.

Electrochemical tests were performed on a Princeton 3F electrochemical workstation. Prior to testing, open circuit potential was monitored for at least 30 min to stabilize the system. The frequency test range for alternating current impedance was 100 kHz~10 mHz, with an alternating sinusoidal wave amplitude of 10 mV. Data analysis was performed using ZsimpWin 3.5 software after the test. The scanning frequency for the polarization curve test was 0.333 mV/s, and the potential scanning range was set to OCP ± 500 mV. Data fitting was done by EC-Lab software. All tests were conducted at room temperature, and each test was repeated three times to ensure the reliability of the results.

Plate samples of 50 mm × 25 mm × 3 mm were cut, ground to 800#, and then cleaned with deionized water and alcohol before being dried. The samples were then weighed and measured. Each dry/wet cycle in the corrosion experiment lasted 30 min, with 7.5 min of immersion and 22.5 min of drying. The experiment temperature and humidity were 40 ± 1 °C and 90%, respectively, and the solution was a tropical marine atmospheric acceleration simulation solution of 5 wt% NaCl + 0.05 wt% CaCl2 + 0.05 wt% Na2SO446. The corrosion cycles were 72, 144, 288 and 576 h. To improve the accuracy of the experiment, three parallel samples of each type of experimental steel were prepared for each cycle.

At the end of each experimental cycle, the samples were removed for derusting. The derusting solution was 500 mL H2O + 500 mL HCl + 3.5 g hexamethylene tetramine, and the samples were then dried after washing with deionized water and alcohol. The weight was then measured, and the corrosion rate was calculated. The formulas for calculating corrosion loss and corrosion rate are as follows47:

where w is the corrosion loss (g/cm2), v is the corrosion rate (mm/y), m0 is the original weight of the sample (g), mt is the weight of the sample after rust removal (g), S is the exposed area of the sample (cm2), ρ is the density of the steel (7.8 g/cm3) and t is the exposure time (h).

The cross-sectional morphology of the rust layer on the experimental steel was observed using SEM, and EDS was utilized for element distribution and content analysis. XRD was employed to analyze the phase composition of the rust layer, with a working voltage and current of 40 kV and 150 mA, respectively. The scanning rate was 6°/min, and the diffraction angle scanning range was 10°–90°. XPS was used to determine the presence of various elements in the rust layer of the steel. Its power was 150 W, and its working voltage and current were 14.8 kV and 1.6 A, respectively. An Al target was used as the X-ray source, and the beam diameter was 650 μm. The XPS test peaks needed to be calibrated with the standard peak (Cls, 284.6 eV) and fitted using XPS-PEAK 4.1 software. Additionally, the surface morphology of the specimens after removing the corrosion products was observed using a 3D confocal laser scanning microscope (LCM, Keyence VK-X250). Taking the median of five random locations on the surface after rust removal.

Tian, H. Y. et al. Corrosion evolution and stress corrosion cracking behavior of a low carbon bainite steel in the marine environments: effect of the marine zones. Corros. Sci. 206, 110490 (2022).

Article CAS Google Scholar

Tian, H. Y. et al. Electrochemical corrosion, hydrogen permeation and stress corrosion cracking behavior of E690 steel in thiosulfate-containing artificial seawater. Corros. Sci. 144, 145–162 (2018).

Article CAS Google Scholar

Xu, X. X. et al. Optimizing the resistance of Ni-advanced weathering steel to marine atmospheric corrosion with the addition of Al or Mo. Constr. Build. Mater. 279, 122341 (2021).

Article CAS Google Scholar

Cai, F. F. et al. Characteristics and mechanisms of low-alloy high-strength steel corrosion behavior under barnacle adhesion based on a comparison experiment. Corros. Sci. 217, 111146 (2023).

Article CAS Google Scholar

Jiang, S. et al. Effect of Ni on the oxidation behavior of corrosion products that form on low alloy steel exposed to a thin electrolyte layer environment. Corros. Sci. 206, 110471 (2022).

Article CAS Google Scholar

Sun, Y. P. et al. Understanding the role of alloyed Ni and Cu on improving corrosion resistance of low alloy steel in the simulated Beishan groundwater. J. Mater. Sci. Technol. 130, 124–135 (2022).

Article CAS Google Scholar

Wei, X. et al. Data mining to effect of key alloying elements on corrosion resistance of low alloy steels in Sanya seawater environmentAlloying Elements. J. Mater. Sci. Technol. 64, 222–232 (2021).

Article CAS Google Scholar

Zhang, W., Yang, S., Geng, W.-T. & Hu, Q. Corrosion behavior of the low alloy weathering steels in stagnant water. Mater. Chem. Phys. 302, 127745 (2023).

Article CAS Google Scholar

Sun, M. H., Pang, Y. J., Du, C. W., Li, X. G. & Wu, Y. M. Optimization of Mo on the corrosion resistance of Cr-advanced weathering steel designed for tropical marine atmosphere. Constr. Build. Mater. 302, 124346 (2021).

Article CAS Google Scholar

Yuan, X. Y., Zhao, Y., Li, X. & Chen, L. Q. Effect of Cr on mechanical properties and corrosion behaviors of Fe-Mn-C-Al-Cr-N TWIP steels. J. Mater. Sci. Technol. 33, 1555–1560 (2017).

Article CAS Google Scholar

Zhang, S. H. et al. Alloy design employing Ni and Mo low alloying for 3Cr steel with enhanced corrosion resistance in CO2 environments. J. Mater. Res. Technol. 24, 1304–1321 (2023).

Article CAS Google Scholar

Sun, M. H. et al. Fundamental understanding on the effect of Cr on corrosion resistance of weathering steel in simulated tropical marine atmosphere. Corros. Sci. 186, 109427 (2021).

Article CAS Google Scholar

Wu, W. et al. Roles of Sb addition on the corrosion resistance of the low‐alloy steel in a real tropical marine atmosphere. Mater. Corros. 73, 733–746 (2022).

Article CAS Google Scholar

Wu, W., Liu, Z., Li, X., Du, C. & Cui, Z. Influence of different heat-affected zone microstructures on the stress corrosion behavior and mechanism of high-strength low-alloy steel in a sulfurated marine atmosphere. Mater. Sci. Eng. A 759, 124–141 (2019).

Article CAS Google Scholar

Xiao, X. M., Peng, Y., Ma, C. Y. & Tian, Z. L. Effects of alloy element and microstructure on corrosion resistant property of deposited metals of weathering steel. J. Iron Steel Res. Int. 23, 171–177 (2016).

Article Google Scholar

Sun, M. et al. The influence of microstructures on the corrosion resistance of Cr–Mo–Sn low alloy steel in a tropical marine atmospheric. Corros. Sci. 233, 112058 (2024).

Article CAS Google Scholar

Sugimoto, K. & Sawada, Y. The role of alloyed molybdenum in austenitic stainless steels in the inhibition of pitting in neutral halide solutions. Corrosion 32, 347–352 (1976).

Article CAS Google Scholar

Jargelius‐Pettersson, R. & Pound, B. Examination of the role of molybdenum in passivation of stainless steels using AC impedance spectroscopy. J. Electrochem. Soc. 145, 1462 (1998).

Article Google Scholar

Li, H. X. et al. Effect of tin on the corrosion behavior of sea-water corrosion-resisting steel. Mater. Des. 84, 1–9 (2015).

Article CAS Google Scholar

Luo, H., Su, H. Z., Li, B. S. & Ying, G. B. Electrochemical and passive behaviour of tin alloyed ferritic stainless steel in concrete environment. Appl. Surf. Sci. 439, 232–239 (2018).

Article CAS Google Scholar

Zhang, X.-J., Gao, F. & Liu, Z.-Y. Effect of Sn on corrosion behavior of ultra-pure 17 mass% Cr ferritic stainless steels in sulphuric acid. J. Iron Steel Res. Int. 23, 1044–1053 (2016).

Article Google Scholar

Kamimura, T., Kashima, K., Sugae, K., Miyuki, H. & Kudo, T. The role of chloride ion on the atmospheric corrosion of steel and corrosion resistance of Sn-bearing steel. Corros. Sci. 62, 34–41 (2012).

Article CAS Google Scholar

Hao, X. H. et al. Influence of Sn and Mo on corrosion behavior of ferrite-pearlite steel in the simulated bottom plate environment of cargo oil tank. J. Mater. Sci. Technol. 35, 799–811 (2019).

Article CAS Google Scholar

Li, Y., Han, J. P., Jiang, Z. H. & He, P. Effect of tin addition on the microstructure and properties of ferritic stainless steel. Int. J. Miner. Metall. Mater. 22, 37–44 (2015).

Article CAS Google Scholar

Panchenko, Y. M., Marshakov, A., Igonin, T., Kovtanyuk, V. & Nikolaeva, L. Long-term forecast of corrosion mass losses of technically important metals in various world regions using a power function. Corros. Sci. 88, 306–316 (2014).

Article CAS Google Scholar

Xiao, X. et al. Corrosion mechanism and corrosion behavior prediction of Cu-10Ni-X alloys in NaCl solution combining DFT calculation and experiments. Corros. Sci. 227, 111671 (2024).

Article CAS Google Scholar

Kong, D. et al. Mechanical properties and corrosion behavior of selective laser melted 316L stainless steel after different heat treatment processes. J. Mater. Sci. Technol. 35, 1499–1507 (2019).

Article CAS Google Scholar

Wu, W., Qin, L., Cheng, X., Xu, F. & Li, X. Microstructural evolution and its effect on corrosion behavior and mechanism of an austenite-based low-density steel during aging. Corros. Sci. 212, 110936 (2023).

Article CAS Google Scholar

Pattnaik, A. B., Roy, S., Raja, V. S. & Parida, S. Understanding the structure and electrochemical behavior of the rust layer formed on a high-strength low-alloy structural steel under cyclic exposure to polluted marine atmosphere. J. Mater. Eng. Perform, 1–14 (2024).

Zhang, T. Y., Xu, X. X., Li, Y. & Lv, X. W. The function of Cr on the rust formed on weathering steel performed in a simulated tropical marine atmosphere environment. Constr. Build. Mater. 277, 122298 (2021).

Article CAS Google Scholar

Pan, C., Cui, Y., Liu, L., Guo, M. & Wang, Z. Effect of temperature on corrosion behavior of low-alloy steel exposed to a simulated marine atmospheric environment. J. Mater. Eng. Perform. 29, 1400–1409 (2020).

Article CAS Google Scholar

Yang, W., Ni, R.-C., Hua, H.-Z. & Pourbaix, A. The behavior of chromium and molybdenum in the propagation process of localized corrosion of steels. Corros. Sci. 24, 691–707 (1984).

Article CAS Google Scholar

Dong, C. et al. Integrated computation of corrosion: modelling, simulation and applications. Corros. Commun. 2, 8–23 (2021).

Article Google Scholar

Zhang, H. et al. Different corrosion behaviors between α and β phases of Ti6Al4V in fluoride-containing solutions: influence of alloying element Al. Corros. Sci. 169, 108605 (2020).

Article CAS Google Scholar

Belfrouh, A. et al. The cumulative effect of alloying elements N, W, Mo and Cu on the corrosion behaviour of 17Cr-13Ni stainless steel in 2 N H2SO4. Corros. Sci. 38, 1639–1648 (1996).

Article CAS Google Scholar

Pardo, A. et al. Effect of Mo and Mn additions on the corrosion behaviour of AISI 304 and 316 stainless steels in H2SO4. Corros. Sci. 50, 780–794 (2008).

Article CAS Google Scholar

Hashimoto, K., Asami, K., Kawashima, A., Habazaki, H. & Akiyama, E. The role of corrosion-resistant alloying elements in passivity. Corros. Sci. 49, 42–52 (2007).

Article CAS Google Scholar

Moon, J. et al. Effect of Mo and Cr additions on the microstructure, mechanical properties and pitting corrosion resistance of austenitic Fe-30Mn-10.5 Al-1.1C lightweight steels. J. Alloy. Compd. 775, 1136–1146 (2019).

Article CAS Google Scholar

Kodama, T. & Ambrose, J. Effect of molybdate ion on the repassivation kinetics of iron in solutions containing chloride ions. Corrosion 33, 155–161 (1977).

Article CAS Google Scholar

Liu, B. et al. Effect of tin addition on corrosion behavior of a low-alloy steel in simulated costal-industrial atmosphere. J. Mater. Sci. Technol. 35, 1228–1239 (2019).

Article CAS Google Scholar

Nam, N. D., Kim, M. J., Jang, Y. W. & Kim, J. G. Effect of tin on the corrosion behavior of low-alloy steel in an acid chloride solution. Corros. Sci. 52, 14–20 (2010).

Article Google Scholar

Xu, X. X. et al. Effect of 0.1 wt% Nb on the microstructure and corrosion fatigue performance of high strength steels. Corros. Sci. 219, 111242 (2023).

Article CAS Google Scholar

Xu, X. X. et al. Corrosion fatigue behavior of Fe-16Mn-0.6C-1.68Al twinning-induced plasticity steel in simulated seawater. Corros. Sci. 182, 109282 (2021).

Article CAS Google Scholar

Xu, X. X., Cheng, H. L., Wu, W., Liu, Z. Y. & Li, X. G. Stress corrosion cracking behavior and mechanism of Fe-Mn-Al-C-Ni high specific strength steel in the marine atmospheric environment. Corros. Sci. 191, 109760 (2021).

Article CAS Google Scholar

Dong, C. F. et al. Electrochemical behavior of 304 stainless steel in marine atmosphere and its simulated solution. Anal. Lett. 46, 142–155 (2013).

Article Google Scholar

Jia, J. H., Cheng, X. Q., Yang, X. J., Li, X. G. & Li, W. A study for corrosion behavior of a new-type weathering steel used in harsh marine environment. Constr. Build. Mater. 259, 119760 (2020).

Article CAS Google Scholar

Kong, D. et al. Insight into the mechanism of alloying elements (Sn, Be) effect on copper corrosion during long-term degradation in harsh marine environment. Appl. Surf. Sci. 455, 543–553 (2018).

Article CAS Google Scholar

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The authors gratefully acknowledge the financial support of Shandong Postdoctoral Science Foundation (No. SDBX2023016), National Science and Technology Resources Investigation Program of China (No. 2021FY100604), China Postdoctoral Science Foundation (No. 2023M733875), National Natural Science Foundation of China (Nos. 52101068 and 52101144).

These authors contributed equally: Meihui Sun, Xingyu Xiao.

Institute for Advanced Materials and Technology, University of Science and Technology Beijing, Beijing, China

Meihui Sun, Xingyu Xiao, Jiangwen Li, Cuiwei Du & Xiaogang Li

State Key Laboratory of Metal Materials for Marine Equipment and Application, Anshan, Liaoning, China

Meihui Sun, Jiangwen Li & Tan Zhao

Ansteel Beijing Research Institute Co., Ltd., Beijing, China

Meihui Sun & Jiangwen Li

School of Materials Science and Engineering, China University of Petroleum (East China), Qingdao, China

Xuexu Xu

Key Laboratory for Advanced Materials of Ministry of Education, School of Materials Science and Engineering, Tsinghua University, Beijing, China

Li Gong

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Meihui Sun: conceptualization, methodology, data curation, writing–original draft. Xingyu Xiao: methodology, data curation, writing–reviewing and editing. Xuexu Xu: supervision, conceptualization, methodology, writing–reviewing and editing, funding acquisition. Jiangwen Li: methodology, data curation. Tan Zhao: methodology, data curation. Li Gong: data curation, writing–reviewing and editing. Cuiwei Du: supervision, conceptualization, methodology, writing–reviewing and editing. Xiaogang Li: supervision, resources.

Correspondence to Xuexu Xu or Cuiwei Du.

The authors declare no competing interests.

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Sun, M., Xiao, X., Xu, X. et al. Effect of Mo and Sn co-regulation on low alloy steel corrosion in tropical marine atmosphere. npj Mater Degrad 8, 92 (2024). https://doi.org/10.1038/s41529-024-00507-0

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Received: 20 March 2024

Accepted: 20 August 2024

Published: 03 September 2024

DOI: https://doi.org/10.1038/s41529-024-00507-0

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