Please wait a minute...
金属学报  2026, Vol. 62 Issue (1): 191-202    DOI: 10.11900/0412.1961.2025.00065
  研究论文 本期目录 | 过刊浏览 |
第一性原理分子动力学研究MnO对埋弧焊剂导电机制的影响
袁航1,2, 张燕云1,2, 王聪1,2()
1 东北大学 冶金学院 沈阳 110819
2 东北大学 辽宁省厚板焊接冶金工程研究中心 沈阳 110819
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
引用本文:

袁航, 张燕云, 王聪. 第一性原理分子动力学研究MnO对埋弧焊剂导电机制的影响[J]. 金属学报, 2026, 62(1): 191-202.
Hang YUAN, Yanyun ZHANG, Cong WANG. Influence of MnO upon Electrical Conductive Mechanisms of Submerged Arc Welding Fluxes: Insights from Ab Initio Molecular Dynamics Simulations[J]. Acta Metall Sin, 2026, 62(1): 191-202.

全文: PDF(2864 KB)   HTML
摘要: 

为了研究焊剂中离子导电和电子导电的具体机制,本工作采用四电极法测量了CaF2-SiO2-Al2O3-MgO(MnO)焊剂的电导率,并结合第一性原理分子动力学模拟,探究了离子导电和电子导电对总电导率的贡献机制。结果表明,在无MnO体系中,Mg2+、Ca2+和F-为主要载流子进行离子导电,其扩散行为受网络结构聚合度的限制。引入MnO后,硅铝酸盐网络结构聚合度先升后降,促使离子导电能力呈现先降后升的波动趋势;电子导电能力则持续增强,其原因在于MnO降低了O和F周围的电子局域化程度,提升了Mn原子的电荷转移能力并拓宽了电子跃迁通道。在离子和电子复合导电机制下,MnO对电子导电的促进作用远强于对离子导电的影响。合理调控MnO含量是有效提升焊剂导电性能的重要策略。

关键词 焊剂电导率第一性原理分子动力学结构聚合度电子结构    
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 wordswelding flux    electrical conductivity    ab initio molecular dynamics simulation    structural polymerization    electronic structure
收稿日期: 2025-03-12     
ZTFLH:  TG445  
基金资助:国家重点研发计划项目(2023YFB3709900);国家自然科学基金项目(W2411047);国家自然科学基金项目(52404393);中央高校基本科研业务费项目(N2402016)
通讯作者: 王 聪,wangc@smm.neu.edu.cn,主要从事焊接冶金研究
作者简介: 袁 航,男,1995年生,博士生
SampleSiO2Al2O3MgOMnOCaF2

Tlq

K

PrePostPrePostPrePostPrePostPrePost
F136.0036.2935.4336.108.578.50--20.0019.111731
F236.0036.0835.4335.56--8.578.9320.0019.431716
F336.0035.9225.4325.73--18.5719.0420.0019.311524
表1  焊剂熔融前后的化学成分及开始熔化温度 (mass fraction / %)
图1  目标体系XRD谱及电导率
图2  目标体系中原子对的径向分布函数曲线及F3样品中原子对的配位数
图3  目标体系中不同类型O和F以及Si多面体(QSi)和Al多面体(QAl)单元的占比
图4  目标体系中离子的均方根位移(MSD)和数据拟合结果及扩散系数
图5  第一性原理分子动力学(AIMD)模拟目标体系中最后10 ps的原子轨迹(2000 K)
图6  目标体系中不同元素的分波态密度和总态密度
图7  不同原子构型下的电子局域化函数(ELF)分布图及Mn—O/F和Mg—O/F的ELF分布
图8  目标体系中的Bader电荷
[1] Wang C, Zhang J. Fine-tuning weld metal compositions via flux optimization in submerged arc welding: An overview [J]. Acta Metall. Sin., 2021, 57: 1126
[1] 王 聪, 张 进. 埋弧焊中焊剂对焊缝金属成分调控的研究进展 [J]. 金属学报, 2021, 57: 1126
[2] Sengupta V, Havrylov D, Mendez P F. Physical phenomena in the weld zone of submerged arc welding—A review [J]. Weld. J., 2019, 98: 283S
[3] Liu H Y, Zhang Y Y, Zhao Y Q, et al. Unveiling the amphoteric behavior of TiO2 in fused CaF2-TiO2-MgO-SiO2 submerged arc welding fluxes [J]. Metall. Mater. Trans., 2025, 56B: 699
[4] Bai H Y, Zhang Y Y, Zhao Y Q, et al. Numerical analysis of slag viscosity effects mechanism in submerged arc welding pool [J]. Metall. Mater. Trans., 2025, 56B: 1659
[5] Xie X, Han S, Zhong M, et al. In situ observation of acicular ferrite growth behavior differences in weld metals subjected to varied CaF2-TiO2 flux-cored wires [J]. Metall. Mater. Trans., 2025, 56A: 7
[6] Xie X, Wan Y B, Zhong M, et al. Optimizing microstructures and properties of electro-gas welded metals for EH36 shipbuilding steel treated by CaF2-TiO2 fluxes [J]. Acta Metall. Sin., 2025, DOI: 10.11900/0412.1961.2025.00028
[6] 谢 旭, 万一博, 钟 明 等. CaF2-TiO2焊剂作用下EH36船板钢气电立焊焊缝金属组织优化及性能调控 [J]. 金属学报, 2025, DOI: 10.11900/0412.1961.2025.00028
[7] Hou Y, Zhang S, Dang J, et al. Electrical conductivity and structure of CaO-MgO-SiO2-Al2O3-BaO slag with different BaO/Al2O3 molar ratios [J]. Metall. Mater. Trans., 2024, 55B: 3201
[8] Zhang Y Y, Yuan H, Tian H Y, et al. Elucidating electrical conductive mechanisms for CaF2-SiO2-CaO-TiO2 welding fluxes [J]. Metall. Mater. Trans., 2023, 54B: 3023
[9] Schwemmer D D, Olson D L, Williamson D L. The relationship of weld penetration to the welding flux [J]. Weld. J., 1979, 58: 153
[10] Barati M, Coley K S. Electrical and electronic conductivity of CaO-SiO2-FeO x slags at various oxygen potentials: Part II. Mechanism and a model of electronic conduction [J]. Metall. Mater. Trans., 2006, 37B: 51
[11] Yuan H, Wang Z J, Zhang Y Y, et al. Elucidating electrical conductive mechanisms for CaF2-SiO2-Al2O3-MgO welding fluxes in liquid and crystalline states [J]. Metall. Mater. Trans., 2024, 55B: 5068
[12] Hou Y, Zhang G H, Lv X W. Electrical conductivity of CaO-Al2O3-SiO2 slags containing SiC particles [J]. J. Sustain. Metall., 2023, 9: 1344
[13] Zhou L J, Wu H F, Wang W L, et al. Electrical conductivity and melt structure of the CaO-SiO2-based mold fluxes with different basicity [J]. Metall. Mater. Trans., 2022, 53B: 466
[14] Komen H, Shigeta M, Tanaka M, et al. Numerical investigation of heat transfer during submerged arc welding phenomena by coupled DEM-ISPH simulation [J]. Int. J. Heat Mass Transfer, 2021, 171: 121062
[15] Hu K, Lv X W, Yu W Z, et al. Electric conductivity of TiO2-Ti2O3-FeO-CaO-SiO2-MgO-Al2O3 for high-titania slag smelting process [J]. Metall. Mater. Trans., 2019, 50B: 2982
[16] Wang C, Wang Z J, Yang J K. Revealing the viscosity-structure relationship of SiO2-MnO-CaO fluxes geared toward high heat input submerged arc welding [J]. Metall. Mater. Trans., 2022, 53B: 693
[17] Nath S K, Randhawa N S, Kumar S. A review on characteristics of silico-manganese slag and its utilization into construction materials [J]. Resour. Conserv. Recycl., 2022, 176: 105946
[18] Mori K. The electrical conductivity of molten slags containing titanium-oxide (I) Na2O-SiO2-TiO2 system [J]. Tetsu-to-Hagané, 1956, 42: 633
[18] 森一美. 酸化チタンを含む溶融スラッグの電気伝導度(I) Na2O-SiO2-TiO2系 [J]. 鉄と鋼1956, 42: 633
[19] Ge X, Lai P S, Shi C J, et al. Immiscibility in binary silicate liquids: Insight from ab initio molecular dynamics simulations [J]. Phys. Rev., 2024, 109B: 174215
[20] Liu S Y, Wang L J, He X B, et al. Insight into the oxidation mechanisms of vanadium slag and its application in the separation of V and Cr [J]. J. Cleaner Prod., 2023, 405: 136981
[21] Chen M H. Progress of the ABACUS software for density functional theory and its integration and applications with deep learning algorithms [J]. Acta Metall. Sin., 2024, 60: 1405
[21] 陈默涵. 密度泛函理论软件ABACUS进展及其与深度学习算法的融合及应用 [J]. 金属学报, 2024, 60: 1405
[22] Cheng K, Chen S M, Cao S, et al. Precipitation strengthening in titanium alloys from first principles investigation [J]. Acta Metall. Sin., 2024, 60: 537
[22] 程 坤, 陈树明, 曹 烁 等. 第一性原理研究钛合金中的沉淀强化 [J]. 金属学报, 2024, 60: 537
[23] Shen X Y, Chu R X, Jiang Y H, et al. Progress on materials design and multiscale simulations for phase-change memory [J]. Acta Metall. Sin., 2024, 60: 1362
[23] 沈雪阳, 褚瑞轩, 蒋宜辉 等. 相变存储器材料设计与多尺度模拟的研究进展 [J]. 金属学报, 2024, 60: 1362
[24] Sun Y W, Qian G Y, Pang S, et al. Element partitioning and stabilization for impurities removal between liquid silicon and silicate melts: Ab initio insights into electronic structure [J]. J. Mol. Liq., 2024, 400: 124566
[25] Gao L F, Liu X C, Bai J, et al. Unveiling charge compensation effects in Na2O-Al2O3-SiO2 melts: Atomic-scale mechanisms and implications for fluidity from AIMD simulations [J]. J. Phys. Chem., 2024, 128C: 17756
[26] Zhang C, Wu T, Xia W Z, et al. Effect of alkaline oxides on aluminate slag structure by first principles calculation [J]. J. Mol. Liq., 2023, 390: 123088
[27] Jiang C H, Li K J, Barati M, et al. The interaction mechanism between molten SiO2-Al2O3-CaO slag and graphite with different crystal orientations: Experiment and ab initio molecular dynamics simulation [J]. Ceram. Int., 2023, 49: 8295
[28] Pang Z D, Lv X W, Yan Z M, et al. Transition of blast furnace slag from silicate based to aluminate based: Electrical conductivity [J]. Metall. Mater. Trans., 2019, 50B: 385
[29] Boeykens P J, Bellemans I, Scheunis L, et al. Parameter investigation of the experimental methodology of electrical conductivity measurements for PbO containing slags [J]. Electrochim. Acta, 2023, 464: 142846
[30] Kühne T D, Iannuzzi M, Del Ben M, et al. CP2K: An electronic structure and molecular dynamics software package—Quickstep: Efficient and accurate electronic structure calculations [J]. J. Chem. Phys., 2020, 152: 194103
[31] VandeVondele J, Krack M, Mohamed F, et al. QUICKSTEP: Fast and accurate density functional calculations using a mixed Gaussian and plane waves approach [J]. Comput. Phys. Commun., 2005, 167: 103
[32] Grimme S, Antony J, Ehrlich S, et al. A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu [J]. J. Chem. Phys., 2010, 132: 154104
[33] Plimpton S. Fast parallel algorithms for short-range molecular dynamics [J]. J. Comput. Phys., 1995, 117: 1
[34] Yuan H, Wang Z J, Zhang Y Y, et al. Roles of MnO and MgO on structural and thermophysical properties of SiO2-MnO-MgO-B2O3 welding fluxes: A molecular dynamics study [J]. J. Mol. Liq., 2023, 386: 122501
[35] Yuan H, Zhang Y Y, Liu H Y, et al. Bond characteristic-dependent viscosity variations in CaF2-SiO2-Al2O3-MgO welding fluxes [J]. Weld. J., 2025, 104: 107-s
[36] Momma K, Izumi F. VESTA 3 for three-dimensional visualization of crystal, volumetric and morphology data [J]. J. Appl. Crystallogr., 2011, 44: 1272
[37] Lu T, Chen F W. Multiwfn: A multifunctional wavefunction analyzer [J]. J. Comput. Chem., 2012, 33: 580
[38] He X B, Ma S D, Wang L J, et al. Comparison of desulfurization mechanism in liquid CaO-SiO2 and MnO-SiO2: An ab initio molecular dynamics simulation [J]. J. Alloys Compd., 2022, 896: 163008
[39] Wang Z, Huang S H, Yu Y, et al. Comprehensive understanding of the microstructure and volatilization mechanism of fluorine in silicate melt [J]. Chem. Eng. Sci., 2021, 243: 116773
[40] Gong K, Özçelik V O, Yang K R, et al. Density functional modeling and total scattering analysis of the atomic structure of a quaternary CaO-MgO-Al2O3-SiO2 (CMAS) glass: Uncovering the local environment of calcium and magnesium [J]. Phys. Rev. Mater., 2021, 5: 015603
[41] Christie J K. Clustering of fluoride and phosphate ions in bioactive glass from computer simulation [J]. Philos. Trans. Roy. Soc., 2023, 381A: 20220345
[42] Zhang X B, Liu C J, Jiang M F. Effect of fluorine on melt structure for CaO-SiO2-CaF2 and CaO-Al2O3-CaF2 by molecular dynamics simulations [J]. ISIJ Int., 2020, 60: 2176
[43] Yuan H, Zhang Y Y, Zhao Y Q, et al. Structural role of CaF2 upon welding flux viscosity [J]. Weld. J., 2025, 104: 164-S
[44] Zhang C, Kong Y Q, Wu T, et al. First-principles study on microstructure of CaO-Al2O3-B2O3 slag [J]. J. Mol. Liq., 2022, 368: 120738
[1] 谢旭, 万一博, 钟明, 邹晓东, 王聪. CaF2-TiO2 焊剂作用下EH36船板钢气电立焊焊缝金属组织优化及力学性能调控[J]. 金属学报, 2025, 61(7): 998-1010.
[2] 王京京, 姚志浩, 张鹏, 赵杰, 张迈, 王蕾, 董建新, 陈迎. 镍基高温合金中S元素对基体与热障涂层界面稳定性的影响[J]. 金属学报, 2024, 60(9): 1250-1264.
[3] 李斗, 徐长江, 李旭光, 李双明, 钟宏. La掺杂PCeyFe3CoSb12 热电材料及涂层的热电性能[J]. 金属学报, 2023, 59(2): 237-247.
[4] 皇甫顥, 王子龙, 刘永利, 孟凡顺, 宋久鹏, 祁阳. W1 - x Ir x 固溶合金几何结构、电子结构、力学和热力学性能的第一性原理计算[J]. 金属学报, 2022, 58(2): 231-240.
[5] 王硕, 王俊升. Al-Li合金中 δ′/θ′/δ复合沉淀相结构演化及稳定性的第一性原理探究[J]. 金属学报, 2022, 58(10): 1325-1333.
[6] 王聪, 张进. 埋弧焊中焊剂对焊缝金属成分调控的研究进展[J]. 金属学报, 2021, 57(9): 1126-1140.
[7] 崔洋, 李寿航, 应韬, 鲍华, 曾小勤. 基于第一性原理的金属导热性能研究[J]. 金属学报, 2021, 57(3): 375-384.
[8] 陈丽群, 邱正琛, 于涛. Ru对NiAl[100](010)刃型位错电子结构的影响[J]. 金属学报, 2019, 55(2): 223-228.
[9] 宋贵宏,李贵鹏,刘倩男,杜昊,胡方. 溅射沉积Mg2(Sn, Si)薄膜组织结构与导电性能[J]. 金属学报, 2019, 55(11): 1469-1476.
[10] 毛萍莉,于波,刘正,王峰,鞠阳. Mg-Zn-Ca合金中AB2型金属间化合物电子结构和弹性性质的第一性原理计算[J]. 金属学报, 2013, 49(10): 1227-1233.
[11] 厉英,丁玉石,崔绍刚,王常珍. 掺杂Sc的CaZrO3的制备及电学性能[J]. 金属学报, 2012, 48(5): 575-578.
[12] 黄炼,高坤元,文胜平,黄晖,王为,聂祚仁. Al3M(M=Ti, Zr, Hf)亚稳相和平衡相的价电子结构分析[J]. 金属学报, 2012, 48(4): 492-501.
[13] 宋鲁男 刘嘉斌 黄六一 曾跃武 孟亮. 强变形对Cu-Cr合金组织性能的影响[J]. 金属学报, 2012, 48(12): 1459-1466.
[14] 周惦武 刘金水 徐少华 彭平. Al2Sr和Mg2Sr相结构稳定性与弹性性能的第一原理计算[J]. 金属学报, 2011, 47(10): 1315-1320.
[15] 李贵茂 王恩刚 张林 左小伟 赫冀成. 强磁场对Cu-25%Ag合金析出相及性能的影响[J]. 金属学报, 2010, 46(9): 1128-1132.