薄规格取向硅钢二次再结晶过程中Goss织构演变的Monte Carlo模拟

doi:10.11896/j.issn.1005-023X.2018.02.030

《材料导报》期刊社

2018, Vol. 32

Issue (2): 313-315 https://doi.org/10.11896/j.issn.1005-023X.2018.02.030

物理计算模拟｜材料

薄规格取向硅钢二次再结晶过程中Goss织构演变的Monte Carlo模拟

马光¹,陈新¹,卢理成²,信冬群³,孟利⁴,王浩³,程灵¹,杨富尧¹

1 全球能源互联网研究院电工新材料研究所,北京102211
2 国家电网公司,北京100031
3 北京科技大学材料科学与工程学院,北京100083
4 钢铁研究总院,北京100081

Monte Carlo Simulation of the Evolution of Goss Texture in Secondary Recrystallization of Thin Gauge Grain Oriented Silicon Steel

Guang MA¹,Xin CHEN¹,Licheng LU²,Dongqun XIN³,Li MENG⁴,Hao WANG³,Ling CHENG¹,Fuyao YANG¹

1 Department of Electrical Engineering New Materials, Global Energy Interconnection Research Institute, Beijing 102211
2 State Grid Corporation of China, Beijing 100031
3 School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing 100083
4 Central Iron and Steel Research Institute, Beijing 100081

摘要
图/表
参考文献
相关文章
推荐阅读
Metrics

下载:

全文 ( PDF ) ( 2170KB )
输出: BibTeX | EndNote (RIS)

摘要

通过EBSD实验获取了薄规格取向硅钢(0.18 mm厚)初次再结晶样品表面晶粒组织的取向数据,并以此构建模拟的初始组织。采用Potts模型Monte Carlo方法对薄规格取向硅钢初次再结晶样品的二次再结晶过程进行了模拟仿真,研究了表面能对Goss织构演变的影响。模拟结果表明:Goss取向晶粒与相邻晶粒的表面能差是Goss取向晶粒异常长大的重要驱动力;表面能差存在一个临界值(约12%),只有当表面能差大于此临界值时才会发生表面能驱动Goss取向晶粒的异常长大。

	服务
	把本文推荐给朋友
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	马光
	陈新
	卢理成
	信冬群
	孟利
	王浩
	程灵
	杨富尧

关键词: 薄规格取向硅钢 Monte Carlo模拟 Goss织构

Abstract:

The orientation data of surface grains of the primary recrystallized samples of thin gauge grain oriented silicon steel (0.18 mm thick) were obtained by EBSD experiment and the initial microstructure were generated from the orientation data. The Potts model Monte Carlo method was used to simulate the secondary recrystallization of thin gauge graded grain oriented silicon steel, and the effect of surface energy on the evolution of Goss texture was studied. The simulation results show that the surface energy difference between Goss grain and its adjacent grains is an important driving force for Goss grain growth. The surface energy diffe-rence has a critical value (≈12%), only when the surface energy difference is larger than the critical value, can the surface energy-driven abnormal Goss grain growth occur.

Key words: thin gauge grain oriented silicon steel Monte Carlo simulation Goss texture

出版日期: 2018-01-25 发布日期: 2018-01-25

ZTFLH:

TG142.77

基金资助: 国家电网公司科技项目(SGRI-WD-71-14-002);国家自然科学基金(51571020;51371030);国家重点研发计划(2016YFB0700501)

引用本文:

马光,陈新,卢理成,信冬群,孟利,王浩,程灵,杨富尧. 薄规格取向硅钢二次再结晶过程中Goss织构演变的Monte Carlo模拟[J]. 《材料导报》期刊社, 2018, 32(2): 313-315.
Guang MA,Xin CHEN,Licheng LU,Dongqun XIN,Li MENG,Hao WANG,Ling CHENG,Fuyao YANG. Monte Carlo Simulation of the Evolution of Goss Texture in Secondary Recrystallization of Thin Gauge Grain Oriented Silicon Steel. Materials Reports, 2018, 32(2): 313-315.

链接本文:

https://www.mater-rep.com/CN/10.11896/j.issn.1005-023X.2018.02.030 或 https://www.mater-rep.com/CN/Y2018/V32/I2/313

表1 实验钢化学成分(质量分数,%)

图1 Fe-3%Si试样初次再结晶EBSD取向成像图

图2 显微组织离散化示意图(数字对应格点的取向属性)

图3 不同Λ值显微组织演变的模拟结果

图4 表面能对Goss织构演变的影响

1	1 毛卫民, 杨平 . 电工钢的材料学原理[M]. 北京: 高等教育出版社, 2013.
2	Harase J, Shimizu R, Dingley D J . Texture evolution in the presence of precipitates in Fe-3% Si alloy[J]. Acta Metallurgica Et Materialia, 1991,39:763.
3	Lin P, Palumbo G, Harase J , et al. Coincidence site lattice (CSL) grain boundaries and Goss texture development in Fe-3% Si alloy[J]. Acta Metallurgica Et Materialia, 1996,44(12):4677.
4	Harase J, Shimizu R, Kim J K , et al. The role of high energy boundaries and coincidence boundaries in the secondary recrystallization of grain-oriented silicon steel[J]. Metals and Materials International, 1999,5(5):429.
5	Hayakawa Y, Szpunar J A, Palumbo G , et al. The role of grain boundary character distribution in Goss texture development in electrical steels[J]. Journal of Magnetism and Magnetic Materials, 1996,160(4):143.
6	Hayakawa Y, Szpunar J A . A new model of Goss texture development during secondary recrystallization of electrical steel[J]. Acta Materialia, 1997,45(11):4713.
7	Zhang L Z, Rollett A D, Bartel T , et al. A calibrated Monte Carlo approach to quantify the impacts of misorientation and different driving forces on texture development[J]. Acta Materialia, 2012,60(3):1201.
8	Maazi N . Introduction of preferential interaction particle-grain boundary in grain growth simulation—Application to the abnormal Goss grain growth in the Fe-3%Si magnetic alloys[J]. Computatio-nal Materials Science, 2013,79:303.
9	Liu Y, Baudin T, Penelle R . Simulation of normal grain growth by cellular automata[J]. Scripta Materialia, 1996,34(11):1679.
10	Plimpton S . Fast parallel algorithms for short-range molecular dynamics[J]. Journal of Computational Physics, 1995,117(1):1.
11	CEK Iii, Chen L Q . Computer simulation of 3-D grain growth using a phase-field model[J]. Acta Materialia, 2002,50(12):3059.
12	Anderson M P, Srolovitz D J, Grest G S , et al. Computer simulation of grain growth-Ⅰ. Kinetics[J]. Acta Metallurgica, 1984,32(5):783.
13	Srolovitz D J, Anderson M P, Sahni P S , et al. Computer simulation of grain growth-Ⅱ. Grain size distribution, topology, and local dynamics[J]. Acta Metallurgica, 1984,32(5):793.
14	Radhakrishnan B, Zacharia T . Simulation of curvature-driven grain growth by using a modified monte carlo algorithm[J]. Metallurgical and Materials Transactions A, 1995,26(1):167.
15	Song X, Liu G, He Y . Modified Monte Carlo method for grain growth simulation[J]. Progress in Natural Science, 1998,8(1):92.
16	Wang Hao, Liu Guoquan, Qin Xiangge . Simulation of 3D grain growth from different initial states and their quasi-stationary state distributions[J]. Rare Metal Materials and Engineering, 2009,38(1):126(in Chinese).
17	王浩, 刘国权, 秦湘阁 . 不同初始组织的3D晶粒长大仿真及其准稳态分布研究[J]. 稀有金属材料与工程. 2009,38(1):126.
18	Meng L, Wang H, Liu G Q, Chen Y . Study on topological properties in two-dimensional grain networks via large-scale Monte Carlo simulation[J]. Computational Materials Science, 2015,103:165.

[1]	李娜, 丁西安, 王永强, 陆勤阳, 郑成思. Cu对含Ce高强高效无取向硅钢磁性能的影响[J]. 材料导报, 2024, 38(6): 22100266-7.
[2]	王海军, 牛宇豪, 凌海涛, 乔家龙, 何飞, 仇圣桃. 无取向硅钢中微细夹杂物控制研究进展[J]. 材料导报, 2024, 38(3): 22040407-9.
[3]	褚绍阳, 干勇, 仇圣桃, 项利, 田玉石, 石超. 高牌号无取向硅钢生产流程中织构控制研究现状[J]. 材料导报, 2024, 38(13): 23020235-9.
[4]	何承绪, 马光, 毛航银, 祝志祥, 韩钰, 高洁, 张一航, 胡卓超. 耐热型取向硅钢涂层特性与磁性能[J]. 材料导报, 2024, 38(1): 22030301-5.
[5]	何承绪, 高洁, 毛航银, 马光, 陈新, 祝志祥, 张一航, 胡卓超. 退火温度对耐热型取向硅钢组织与磁性能的影响[J]. 材料导报, 2023, 37(8): 21090231-5.
[6]	付兵, 项利, 乔家龙, 刘静, 仇圣桃. 薄板坯连铸连轧流程制备低温Hi-B钢织构的演变及Goss晶粒的发展[J]. 材料导报, 2022, 36(9): 20120130-8.
[7]	汪勇, 李光强, 刘玉龙, 高洋, 郭小龙, 朱诚意. Nb微合金化对取向硅钢常化板中析出物特征及组织和织构的影响[J]. 材料导报, 2022, 36(7): 20110126-6.
[8]	李慧姝, 卢豪, 顾宇红. 聚合物刷在溶剂中的自组装行为及弹性响应[J]. 材料导报, 2022, 36(15): 21030320-5.
[9]	朱诚意, 鲍远凯, 汪勇, 马江华, 李光强. 新能源汽车驱动电机用无取向硅钢应用现状和性能调控研究进展[J]. 材料导报, 2021, 35(23): 23089-23096.
[10]	杨浩, 王成, 肖小波, 王晨, 陈俊锋, 汪炳叔, 张维林, 崔熙贵. 添加硼酸和钨酸铵对取向硅钢无铬绝缘涂层的影响[J]. 材料导报, 2021, 35(22): 22141-22145.
[11]	乔家龙, 郭飞虎, 付兵, 胡金文, 项利, 仇圣桃. 无取向硅钢中硫化物的析出机理[J]. 材料导报, 2021, 35(20): 20106-20112.
[12]	王丽娜, 何承绪, 孟利, 杨佳欣, 张宁, 郭小龙, 胡卓超, 李国保, 王福明. 升温速率对冷轧超薄取向硅钢再结晶行为的影响[J]. 材料导报, 2021, 35(18): 18170-18175.
[13]	樊立峰, 秦美美, 岳尔斌, 肖丽俊, 何建中. 新能源汽车对无取向硅钢的技术挑战[J]. 材料导报, 2021, 35(15): 15183-15188.
[14]	何承绪, 马光, 陈新, 杨富尧, 程灵, 杨勇杰, 胡卓超, 孟利. 低温薄规格取向硅钢初次再结晶组织对二次再结晶行为的影响[J]. 材料导报, 2020, 34(Z1): 457-461.
[15]	程灵, 韩钰, 马光, 孟利, 杨富尧, 陈新, 董瀚. 特高压直流换流阀饱和电抗器用超薄取向硅钢涂层制备与性能评估[J]. 材料导报, 2020, 34(18): 18139-18144.

[1]	Wei ZHOU, Xixi WANG, Yinlong ZHU, Jie DAI, Yanping ZHU, Zongping SHAO. A Complete Review of Cobalt-based Electrocatalysts Applying to Metal-Air Batteries and Intermediate-Low Temperature Solid Oxide Fuel Cells[J]. Materials Reports, 2018, 32(3): 337 -356 .
[2]	Dongyong SI, Guangxu HUANG, Chuanxiang ZHANG, Baolin XING, Zehua CHEN, Liwei CHEN, Haoran ZHANG. Preparation and Electrochemical Performance of Humic Acid-based Graphitized Materials[J]. Materials Reports, 2018, 32(3): 368 -372 .
[3]	Yunzi LIU,Wei ZHANG,Zhanyong SONG. Technological Advances in Preparation and Posterior Treatment of Metal Nanoparticles-based Conductive Inks[J]. Materials Reports, 2018, 32(3): 391 -397 .
[4]	Bingwei LUO,Dabo LIU,Fei LUO,Ye TIAN,Dongsheng CHEN,Haitao ZHOU. Research on the Two Typical Infrared Detection Materials Serving at Low Temperatures: a Review[J]. Materials Reports, 2018, 32(3): 398 -404 .
[5]	Yingke WU,Jianzhong MA,Yan BAO. Advances in Interfacial Interaction Within Polymer Matrix Nanocomposites[J]. Materials Reports, 2018, 32(3): 434 -442 .
[6]	Zhengrong FU,Xiuchang WANG,Qinglin JIN,Jun TAN. A Review of the Preparation Techniques for Porous Amorphous Alloys and Their Composites[J]. Materials Reports, 2018, 32(3): 473 -482 .
[7]	Fangyuan DONG,Shansuo ZHENG,Mingchen SONG,Yixin ZHANG,Jie ZHENG,Qing QIN. Research Progress of High Performance ConcreteⅡ: Durability and Life Prediction Model[J]. Materials Reports, 2018, 32(3): 496 -502 .
[8]	Lixiong GAO,Ruqian DING,Yan YAO,Hui RONG,Hailiang WANG,Lei ZHANG. Microbial-induced Corrosion of Concrete: Mechanism, Influencing Factors,Evaluation Indices, and Proventive Techniques[J]. Materials Reports, 2018, 32(3): 503 -509 .
[9]	Ningning HE,Chenxi HOU,Xiaoyan SHU,Dengsheng MA,Xirui LU. Application of SHS Technique for the High-level Radioactive Waste Disposal[J]. Materials Reports, 2018, 32(3): 510 -514 .
[10]	Haoran CHEN, Yingdong XIA, Yonghua CHEN, Wei HUANG. Low-dimensional Perovskites: a Novel Candidate Light-harvesting Material for Solar Cells that Combines High Efficiency and Stability[J]. Materials Reports, 2018, 32(1): 1 -11 .

Viewed

Full text

Abstract

Cited

Shared

Discussed