Exploring corrosion protection evolution of rust layer on high-Cr-content weathering bridge steel in simulated tropical marine atmosphere

Abstract

The rust layer is a critical factor in determining the corrosion resistance performance of weathering bridge steel. Understanding the evolution mechanism of this rust layer is fundamental for the design and optimization of such steel. This study investigates the evolution of the rust layer on high-Cr-content weathering bridge steel, using an atmospheric corrosion monitoring (ACM) sensor and big data mining techniques in a simulated tropical marine atmosphere. Results reveal that the protective properties of the rust layer follow a periodic pattern of “ascending-constant” rather than a continuous ascending. Correlation analysis indicates that this phenomenon is attributed to the introduction of Cr, which promotes the formation of FeCr₂O₄ in the rust layer. FeCr₂O₄ helps prevent chloride ions from penetrating the rust layer, exerting a protective effect. These findings provide a strong scientific foundation for the design and improvement of new high-Cr-content weathering bridge steels.

Keywords

high-Cr-content steel / rust layer / bridge steel corrosion / chloride corrosion / corrosion rate

References

[1] WangCS, TanCXIn Bridge Maintenance, Safety, Management, Life-cycle Sustainability and Innovations, 2021, Yokota. The CRC Press. 632639

[2] YangFL, HanJK, YangJB, LiZ. Study on the application of weathering and cold-formed steel in transmission tower. Asia-Pacific Power and Energy Engineering Conference, 20091

[3] H.X. Liu, F. Huang, W. Yuan, Q. Hu, J. Liu, and Y.F. Cheng, Essential role of element Si in corrosion resistance of a bridge steel in chloride atmosphere, Corros. Sci., 173(2020), art. No. 108758.

[4] HuangF, ChengP, ZhaoXY, LiuJ, HuQ, ChengYF. Effect of sulfide films formed on X65 steel surface on hydrogen permeation in H₂S environments. Int. J. Hydrogen Energy, 2017, 4274561

[5] QinLZ, WuW, ChengXQ, XuFF, LiuC, LiXG. Study of the mechanism influencing the initial corrosion behaviour of B2 phase Fe–Mn–Al–C–Ni lightweight steels in 3.5% NaCl solution. JCM, 2023, 7572212

[6] W. Wu, L.Z. Qin, X.Q. Cheng, F.F. Xu, and X.G. Li, Microstructural evolution and its effect on corrosion behavior and mechanism of an austenite-based low-density steel during aging, Corros. Sci., 212(2023), art. No. 110936.

[7] M. Pathirana, M. Laleh, A. Somers, B. Hinton, and M.Y. Tan, The critical effect of rust layers on localised corrosion of steel exposed to waterline environments, Corros. Sci., 221(2023), art. No. 111333.

[8] B.Z. Jiang, K. Doi, and K. Tsuchiya, Characterization of microstructures and micromechanical properties of naturally generated rust layer in 60-year old reinforced concrete, Constr. Build. Mater., 366(2023), art. No. 130203.

[9] T.L. Zhao, K. Liu, and Q. Li, Comparison of the rusting behaviors of S450EW weathering steel under continuous spray and wet/dry cycling, Constr. Build. Mater., 309(2021), art. No. 125211.

[10] M.H. Sun, C.W. Du, Z.Y. Liu, C. Liu, X.G. Li, and Y.M. Wu, Fundamental understanding on the effect of Cr on corrosion resistance of weathering steel in simulated tropical marine atmosphere, Corros. Sci., 186(2021), art. No. 109427.

[11] W.H. Zhang, S.W. Yang, W.T. Geng, Q. Hu, and L.J. Zhou, Corrosion behavior of the low alloy weathering steels coupled with stainless steel in simulated open atmosphere, Mater. Chem. Phys., 288(2022), art. No. 126409.

[12] T.Y. Zhang, X.X. Xu, Y. Li, and X.W. Lv, The function of Cr on the rust formed on weathering steel performed in a simulated tropical marine atmosphere environment, Constr. Build. Mater., 277(2021), art. No. 122298.

[13] YamashitaM, MiyukiH, MatsudaY, NaganoH, MisawaT. The long term growth of the protective rust layer formed on weathering steel by atmospheric corrosion during a quarter of a century. Corros. Sci., 1994, 362283

[14] YangXJ, YangY, SunMH, et al.. A new understanding of the effect of Cr on the corrosion resistance evolution of weathering steel based on big data technology. J. Mater. Sci. Technol., 2022, 10467

[15] H.Y. Zhang, J.Q. Wang, L. Hao, S. Zhang, and C.H. Zhang, The formation and mechanism of oxides film on GCr15 bearing steel under indoor atmospheric exposure, Inorg. Chem. Commun., 141(2022), art. No. 109538.

[16] B.Z. Sun, X.M. Zuo, X.Q. Cheng, and X.G. Li, The role of chromium content in the long-term atmospheric corrosion process, NPJ Mater. Degrad., 4(2020), art. No. 37.

[17] QianYH, MaCH, NiuD, XuJJ, LiMS. Influence of alloyed chromium on the atmospheric corrosion resistance of weathering steels. Corros. Sci., 2013, 74424

[18] R.N. Chen, Z.D. Li, Y.G. Cao, B. Gao, Q.F. Zhang, and X.G. Li, Enhanced corrosion resistance of 9Cr alloy steel via Al alloying in simulated harsh marine atmosphere, Mater. Chem. Phys., 320(2024), art. No. 129459.

[19] FanYM, LiuW, LiSM, et al.. Evolution of rust layers on carbon steel and weathering steel in high humidity and heat marine atmospheric corrosion. J. Mater. Sci. Technol., 2020, 39190

[20] HaoL, ZhangSX, DongJH, KeW. Evolution of atmospheric corrosion of MnCuP weathering steel in a simulated coastal-industrial atmosphere. Corros. Sci., 2012, 59270

[21] MaSZ, SunLJ, SunHY, et al.. Stabilization technology and corrosion mechanism of rust layer on Q370 weathering steel surface. J. Iron Steel Res. Int., 2022, 29101694

[22] XuD, YangXJ, LiQ, ChengXQ, LiXG. Review on corrosion test methods and evaluation techniques for materials in atmospheric environment. J. Chin. Soc. Corros. Prot., 2022, 42: 447-457

[23] D. Xu, Z.B. Pei, X.J. Yang, et al., A review of trends in corrosion-resistant structural steels research: From theoretical simulation to data-driven directions, Materials, 16(2023), No. 9, art. No. 3396.

[24] LiXG, ZhangDW, LiuZY, LiZ, DuCW, DongCF. Materials science: Share corrosion data. Nature, 2015, 5277579441

[25] YangXJ, JiaJH, LiQ, et al.. Stress-assisted corrosion mechanism of 3Ni steel by using gradient boosting decision tree machining learning method. Int. J. Miner. Metall. Mater., 2024, 3161311

[26] YangXJ, YangJK, YangY, et al.. Data-mining and atmospheric corrosion resistance evaluation of Sn- and Sb-additional low alloy steel based on big data technology. Int. J. Miner. Metall. Mater., 2022, 294825

[27] X. Guo, X.L. Ding, Y.X. Wang, et al., High-throughput screening of green amino acid and surfactant mixtures with high corrosion inhibition efficiency: Experimental and modelling perspectives, Corros. Sci., 240(2024), art. No. 112460.

[28] C.H. Ren, L.W. Ma, D.W. Zhang, X.G. Li, and A. Mol, High-throughput experimental techniques for corrosion research: A review, Mater. Genome Eng. Adv., 1(2023), No. 2, art. No. e20.

[29] B.Q. Wang, Y.R. Li, X.Q. Cheng, et al., Data-driven optimization model customization for atmospheric corrosion on low-alloy steel: Incorporating the dynamic evolution of the surface rust layer, Corros. Sci., 221(2023), art. No. 111349.

[30] Q. Li, X.J. Xia, Z.B. Pei, et al., Long-term corrosion monitoring of carbon steels and environmental correlation analysis via the random forest method, NPJ Mater. Degrad., 6(2022), art. No. 1.

[31] L. Yang, X.J. Yang, F.F. Xu, et al., Investigation of rust layer on low alloy steel with 0.40wt% Sn in a rural atmospheric environment, Constr. Build. Mater., 402(2023), art. No. 133029.

[32] QinYM, LiXG, AnJF, FanZB, WuJ, WangXM. Mining methods for material corrosion data. Corros. Prot., 2023, 44472

[33] V. Vangrunderbeek, L.B. Coelho, D.W. Zhang, Y.R. Li, Y.V. Ingelgem, and H. Terryn, Exploring the potential of transfer learning in extrapolating accelerated corrosion test data for long-term atmospheric corrosion forecasting, Corros. Sci., 225(2023), art. No. 111619.

[34] P.X. Wang, P.J. Wang, Q. Li, et al., Study of rust layer evolution in Q345 weathering steel utilizing electric resistance probes, Corros. Sci., 225(2023), art. No. 111595.

[35] B.Q. Wang, Y.Q. Mu, F.M. Shen, et al., Identification of corrosion factors in blast furnace gas pipe network with corrosion big data online monitoring technology, Corros. Sci., 230(2024), art. No. 111906.

[36] YangL, ChengXQ, LiXG. Beneficial role of Sn in rapid rust stabilization of weathering steel in marine environments. Int. J. Miner. Metall. Mater., 2025, 3251141

[37] KuangJG, LongZL. Prediction model for corrosion rate of low-alloy steels under atmospheric conditions using machine learning algorithms. Int. J. Miner. Metall. Mater., 2024, 312337

[38] LiYR, FuZH, YuXY, et al.. Developing an atmospheric aging evaluation model of acrylic coatings: A semi-supervised machine learning algorithm. Int. J. Miner. Metall. Mater., 2024, 3171617

[39] Z.B. Pei, D.W. Zhang, Y.J. Zhi, et al., Towards understanding and prediction of atmospheric corrosion of an Fe/Cu corrosion sensor via machine learning, Corros. Sci., 170(2020), art. No. 108697.

[40] PeiZB, ChengXQ, YangXJ, et al.. Understanding environmental impacts on initial atmospheric corrosion based on corrosion monitoring sensors. J. Mater. Sci. Technol., 2021, 64214

[41] P. Karl, “Das fehlergesetz und seine verallgemeinerungen durch Fechner und Pearson.” A rejoinder, Biometrika, 4(1905), No. 1/2, art. No. 169.

[42] Y. Zhang, K.F. Zheng, J. Zhu, M. Lei, and X.Y. Feng, Research on corrosion and fatigue performance of weathering steel and high-performance steel for bridges, Constr. Build. Mater., 289(2021), art. No. 123108.

[43] J.H. Jia, X.Q. Cheng, X.J. Yang, X.G. Li, and W. Li, A study for corrosion behavior of a new-type weathering steel used in harsh marine environment, Constr. Build. Mater., 259(2020), art. No. 119760.

[44] GuoLQ, LinMC, QiaoLJ, VolinskyAA. Duplex stainless steel passive film electrical properties studied by in situ current sensing atomic force microscopy. Corros. Sci., 2014, 7855

[45] P. Mills and J.L. Sullivan, A study of the core level electrons in iron and its three oxides by means of X-ray photoelectron spectroscopy, J. Phys. D Appl. Phys., 16(1983), No. 5, art. No. 723.

[46] GrohmannI, KemnitzE, LippitzA, UngerWES. Curve fitting of Cr 2p photoelectron spectra of Cr₂O₃ and CrF₃. Surf. Interface Anal., 1995, 2313887

[47] AllenGC, HarrisSJ, JutsonJA, DykeJM. A study of a number of mixed transition metal oxide spinels using X-ray photoelectron spectroscopy. Appl. Surf. Sci., 1989, 371111

[48] ShuttleworthD. Preparation of metal-polymer dispersions by plasma techniques. An ESCA investigation. J. Phys. Chem., 1980, 84121629

[49] W. Wu, X.Q. Cheng, J.B. Zhao, and X.G. Li, Benefit of the corrosion product film formed on a new weathering steel containing 3% nickel under marine atmosphere in Maldives, Corros. Sci., 165(2020), art. No. 108416.

[50] StratmannM, BohnenkampK, EngellHJ. An electrochemical study of phase-transitions in rust layers. Corros. Sci., 1983, 239969

[51] ZhouYL, ChenJ, XuY, LiuZY. Effects of Cr, Ni and Cu on the corrosion behavior of low carbon microalloying steel in a Cl^‒ containing environment. J. Mater. Sci. Technol., 2013, 292168

[52] KamimuraT, StratmannM. The influence of chromium on the atmospheric corrosion of steel. Corros. Sci., 2001, 433429

[53] GomesA, Paiva LuisT, FigueiraI, DiamantinoTC. Corrosion behavior of stainless steel alloys in molten solar salt. Proceedings of EuroSun2016, 20168

[54] ZengZ, NatesanK, GrimsditchM. Effect of oxide scale compositions on metal dusting corrosion of Fe-based alloys. Corrosion, 2004, 607632

[55] StratmannM, MüllerJ. The mechanism of the oxygen reduction on rust-covered metal substrates. Corros. Sci., 1994, 362327

[56] ZhangXYResearch on Metal Corrosion Mechanism of Semiconductor Material/Metal Galvanic System, 2020, Dalian. Dalian University of Technology.

[57] DillmannP, MazaudierF, HærléS. Advances in understanding atmospheric corrosion of iron. I. Rust characterisation of ancient ferrous artefacts exposed to indoor atmospheric corrosion. Corros. Sci., 2004, 4661401

[58] ZhangQ, WangJ, WuJ, ZhengW, ChenJ, LiA. Effect of ion selective property on protective ability of rust layer formed on weathering steel exposed in the marine atmosphere. Acta Metall. Sin., 2001, 372193

RIGHTS & PERMISSIONS

University of Science and Technology Beijing