Influence of MnO upon Electrical Conductive Mechanisms of Submerged Arc Welding Fluxes: Insights from Ab Initio Molecular Dynamics Simulations

doi:10.11900/0412.1961.2025.00065

Acta Metall Sin

2026, Vol. 62

Issue (1): 191-202 DOI: 10.11900/0412.1961.2025.00065

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Influence of MnO upon Electrical Conductive Mechanisms of Submerged Arc Welding Fluxes: Insights from Ab Initio Molecular Dynamics Simulations

YUAN Hang¹^,², ZHANG Yanyun¹^,², WANG Cong¹^,²(

)

1 School of Metallurgy, Northeastern University, Shenyang 110819, China
2 Liaoning Engineering Research Centre for Thick Plate Welding Metallurgy, Northeastern University, Shenyang 110819, China

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YUAN Hang, ZHANG Yanyun, WANG Cong. Influence of MnO upon Electrical Conductive Mechanisms of Submerged Arc Welding Fluxes: Insights from Ab Initio Molecular Dynamics Simulations. Acta Metall Sin, 2026, 62(1): 191-202.

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Abstract

Submerged arc welding (SAW) is a widely used technique for joining oil and gas pipelines and shipbuilding steels. During SAW, fluxes are critical for atmospheric shielding, weld metal refinement, and heat loss prevention. Their electrical conductivity—a key temperature- and composition-dependent property—dictates arc stability and weld pool heat distribution. However, the mechanisms governing ionic and electronic conduction remain inadequately understood. This study explores the conductivity of CaF₂-SiO₂-Al₂O₃-MgO(MnO) fluxes using a combination of four-electrode experimental measurements and ab initio molecular dynamics simulations, systematically analyzing contributions from ionic and electronic conduction. The results demonstrate that substituting MgO with MnO induces fluctuations in ionic conductivity, primarily owing to competing effects of structural polymerization and ion diffusion. Specifically, the degree of polymerization in Si and Al polyhedral structures and the proportion of bridging oxygens initially increase but later decrease with MnO addition. A general trend is observed in ionic diffusion coefficients, reflecting a balance between structural rigidity and ion mobility. However, MnO consistently enhances electronical conductivity. As MnO content increases, the partial density of states of Mn near the Fermi level rises considerably, indicating improved electron mobility. MnO facilitates electron migration by reducing electron localization around O and F atoms. Furthermore, the increased Bader charge on Mn atoms suggests enhanced charge transfer between Mn and O, thereby creating additional pathways for electron hopping. Consequently, the overall conductivity increases markedly with elevated MnO content, enabled by a consistent rise in electronical conductivity that outweighs fluctuating ionic contributions. These findings underscore the dominant role of electronic conduction in enhancing slag conductivity and the need for future efforts toward optimizing electronic transport through the rational design of transition metal oxides.

Key words: welding flux electrical conductivity ab initio molecular dynamics simulation structural polymerization electronic structure

Received: 12 March 2025

ZTFLH:

TG445

Fund: National Key Research and Development Program of China(2023YFB3709900);National Natural Science Foundation of China(W2411047);Fundamental Research Funds for the Central Universities(N2402016)

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https://www.ams.org.cn/EN/10.11900/0412.1961.2025.00065 OR https://www.ams.org.cn/EN/Y2026/V62/I1/191

Table 1 Chemical compositions of the flux before and after melting and onset melting temperatures (T_lq)

Fig.1 XRD patterns (a) and electrical conductivities (Blue area represents error band) (b) of target systems (i.e., F1, F2, and F3 samples)

Fig.2 Structural radial distribution function (RDF) curves of Si-O (a), Al-O (b), and Ca-F (c) atomic pairs in target systems; and coordination numbers (CNs) for various atomic pairs in F3 sample (d) (R_i represents bond length for specific bond i; g(r) and CN(r) represent RDF and CN functions, respectively; r—distance)

Fig.3 Distributions of O (a) and F (b) with different types, and Si polyhedron (Q_Si) (c) and Al polyhedron (Q_Al) (d) units in target systems (Q ⁿ —polyhedron with n BOs, TO—tricluster oxygen, BO—bridging oxygen, NBO—non-bridging oxygen, FO—free oxygen, BF—bonded fluorine, FF—free fluorine)

Fig.4 Mean square displacement (MSD) curves and fitting lines of F1 (a), F2 (b), and F3 (c) samples and diffusion coefficients of ions in target systems (d) (Solid lines and the dashed lines represent fitted data and original data, respectively; t—time)

Fig.5 Atomic trajectories in F1 (a-c), F2 (d-f), and F3 (g-i) samples during the last 10 ps of the ab initio molecular dynamics (AIMD) simulation at 2000 K (The color intensity reflects the depth along the viewing axis, where darker trajectories denote atoms situated closer to the observer, and lighter trajectories correspond to atoms located farther away)
(a) Ca, Mg (d, g) Ca, Mg (b, e, h) F, O (c, f, i) Si, Al

Fig.6 Partial density of states (PDOS) of different atoms in F1 (a), F2 (b), and F3 (c) samples and total density of states (DOS) (d) (E_f—Fermi level)

Fig.7 Electron localization function (ELF) maps of O—Mg—F (a), Al—O—Mg (b), F—Mn—F (c), Al—O—Mn (d), Al—O—Al/Ca (e), and Si-O-Ca (f) regions and ELF distribution line profiles of Mn—O/F and Mg—O/F (The lines are averages of all the distributions and the shadows are standard deviations) (g)

Fig.8 Bader charges of atoms in F1 (a), F2 (b), and F3 (c) samples

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