新型钴基与<strong>Nb-Si</strong>基高温合金扩散动力学研究进展

doi:10.11900/0412.1961.2023.00128

金属学报

2023, Vol. 59

Issue (8): 969-985 DOI: 10.11900/0412.1961.2023.00128

综述

本期目录 | 过刊浏览

新型钴基与Nb-Si基高温合金扩散动力学研究进展

刘兴军¹^,²^,³(

), 魏振帮³^,⁴, 卢勇³^,⁴, 韩佳甲³^,⁴, 施荣沛¹^,², 王翠萍³^,⁴(

)

¹哈尔滨工业大学(深圳) 材料基因与大数据研究院深圳 518055
²哈尔滨工业大学(深圳) 材料科学与工程学院深圳 518055
³厦门大学材料学院福建省表界面工程与高性能材料重点实验室厦门 361005
⁴厦门大学厦门市高性能金属材料重点实验室厦门 361005

Progress on the Diffusion Kinetics of Novel Co-based and Nb-Si-based Superalloys

LIU Xingjun¹^,²^,³(

), WEI Zhenbang³^,⁴, LU Yong³^,⁴, HAN Jiajia³^,⁴, SHI Rongpei¹^,², WANG Cuiping³^,⁴(

)

¹Institute of Materials Genome and Big Data, Harbin Institute of Technology, Shenzhen, Shenzhen 518055, China
²School of Materials Science and Engineering, Harbin Institute of Technology, Shenzhen, Shenzhen 518055, China
³College of Materials and Fujian Key Laboratory of Surface and Interface Engineering for High Performance Materials, Xiamen University, Xiamen 361005, China
⁴Xiamen Key Laboratory of High Performance Metals and Materials, Xiamen University, Xiamen 361005, China

引用本文:

刘兴军, 魏振帮, 卢勇, 韩佳甲, 施荣沛, 王翠萍. 新型钴基与Nb-Si基高温合金扩散动力学研究进展[J]. 金属学报, 2023, 59(8): 969-985.
Xingjun LIU, Zhenbang WEI, Yong LU, Jiajia HAN, Rongpei SHI, Cuiping WANG. Progress on the Diffusion Kinetics of Novel Co-based and Nb-Si-based Superalloys[J]. Acta Metall Sin, 2023, 59(8): 969-985.

全文: PDF(3650 KB) HTML

摘要:

扩散动力学信息是深入理解合金的相变机制、微观组织形成和演化机理的关键参数，也是实现新型钴基与Nb-Si基高温合金设计与研发必要的基础物性数据。首先，本文系统地归纳了高温合金中常见的合金化元素及其作用。随后，详细介绍了合金体系中自扩散系数与杂质扩散系数的机器学习计算方法、互扩散系数的实验测定方法以及示踪扩散系数的分子动力学计算方法，并介绍了本课题组在新型钴基与Nb-Si基高温合金多元扩散动力学数据库建立与完善方面的工作。最后，介绍了扩散动力学数据库在微观组织模拟、合金设计等领域的应用，并对扩散动力学数据库的完善及应用方面的发展进行了展望。

关键词 ：钴基高温合金, Nb-Si基高温合金, 动力学数据库, 微观组织

Abstract：

Data on diffusion kinetics of superalloys is crucial for gaining a thorough understanding of the mechanisms underlying the phase transition and microstructural evolution of superalloys. Further, it is the basis for the design and development of novel Co and Nb-Si-based superalloys. Herein, the common elements used in preparing superalloys and their corresponding functions are systematically summarized. In addition, the contribution of our research group in the establishment and improvement of databases on multicomponent diffusion kinetics of novel Co and Nb-Si-based superalloys is presented in detail. Furthermore, the machine learning method for self-diffusion coefficient and impurity diffusion coefficient, the experimental method for mutual diffusion coefficients, and the molecular dynamics method for tracer diffusion coefficients in the alloy systems are briefly discussed. In addition to providing a brief introduction of the applications of the databases in the simulation of microstructural evolution and alloy design, an outlook on the development of the databases on diffusion kinetics and related applications is presented.

Key words： Co-based superalloy Nb-Si-based superalloy kinetics database microstructure

收稿日期: 2023-03-27

ZTFLH:

TG146.1

基金资助:国家自然科学基金项目(51831007);广东省基础与应用基础研究基金项目(2021B1515120071);深圳市科技计划项目(SGDX20210823104002016)

通讯作者: 刘兴军，xjliu@hit.edu.cn，主要从事相图与相变、计算材料学、金属材料及功能材料等相关研究;王翠萍，wangcp@xmu.edu.cn，主要从事相图与相变、材料热力学与动力学、计算材料学、材料设计及新材料研发等研究

Corresponding author: LIU Xingjun, professor, Tel:(0592)2187888, E-mail: xjliu@hit.edu.cn;WANG Cuiping, professor, Tel:(0592)2180606, E-mail: wangcp@xmu.edu.cn

作者简介: 刘兴军，男，1962年生，教授，博士

	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
	刘兴军
	魏振帮
	卢勇
	韩佳甲
	施荣沛
	王翠萍
44.8K

链接本文:

https://www.ams.org.cn/CN/10.11900/0412.1961.2023.00128 或 https://www.ams.org.cn/CN/Y2023/V59/I8/969

表1 钴基高温合金中合金化元素的作用[16~26]

Element	Microstructure and mechanical property	Oxidation resistance property
Si	Alloy's strength increases, but its ductility and toughness decrease, due to the formation of Nb₃Si and Nb₅Si₃	With increasing temperature over 1000^oC, the resistance to oxidations decreases because of the reduction in the density of oxide films caused by a phase transformation in SiO₂
Al	Inhibiting the formation of Nb₃Si phase and promoting the formation of β-Nb₅Si₃. Toughness decreases, due to the formation of Nb₃Al with a content of Al more than 6% (atomic fraction)	Resistance to the oxidation increases with formation of a dense layer of Al₂O₃
Cr	Inhibiting the formation of Nb₃Si phase and promoting the formation of β-Nb₅Si₃. Formation of Nb₉Si₂Cr₃ is be-neficial to creep resistance of the alloy, while the formation of NbCr₂ phase has negative effects	Enhancing the oxidation resistance of the alloy above 1000^oC by forming Nb₉Si₂Cr₃, NbCr₂ with high oxidation resistance and NbCrO₄ which beneficial to improving adhesion of the oxide layer
Hf	Inhibiting the formation of Nb₃Si phase and promoting the formation of β-Nb₅Si₃. High temperature creep properties decrease, due to the formation of Hf₅Si₃ intermetallic compound with a high content of Hf in alloys	Resistance to oxidations decreases because of embrittlement and cracking of the HfO₂ layer with a high content of Hf
Ti	Stabilizing the Nb₃Si phase. Toughness increases due to the increase in the diffusion rates of the atom and the growth of the phase Nb_ss caused by the addition of Ti	Enhancing the oxidation resistance of the alloy at a temperature below 800^oC by forming dense TiO₂ layers, and decreasing at a temperature above 800^oC due to a phase transformation in TiO₂
V	Stabilizing the α-Nb₅Si₃ phase and inducing the microstr-ucture transformation from dispersion to eutectic-like structure. Alloy's fracture toughness decreases, but its high temperature strength decrease, due to the softening of solid solution caused by thermal activation diffusion process	Resistance to oxidations decreases because of cracking of oxidation layers caused by the formation of V₂O₅ with a high content of V in alloys

表2 Nb-Si基高温合金中合金化元素的作用[29~36]

表3 3种自扩散系数与杂质扩散系数获取方法的对比

图1 基于实验方法获取扩散系数的流程图[37~39]

图2 基于机器学习算法构建固溶体相扩散数据预测模型的流程图[67]

图3 杂质扩散激活能(QI)预测模型中自变量的重要性排序，以及最优机器学习模型计算的自扩散激活能(Qs)、QI与实验结果的对比[67,84]

表4 新型钴基高温合金中fcc相与Nb-Si基高温合金中bcc相的自扩散迁移率参数与杂质扩散迁移率参数的部分优化结果[85~91]

图4 Ni-Co-Al合金中扩散偶在1373 K保温259200 s[92]，Co-Cr-Mo合金中扩散偶在1473 K保温259200 s[93]，Ni-Mo-Ta合金中扩散偶在1473 K保温259200 s[94]，以及Ni-Mo-Ta合金中扩散偶在1573 K保温172800 s后[94]的扩散路径计算结果和实验数据的对比

图5 Co、Ti与Ni原子在不同合金中的均方位移(MSD)随时间的变化曲线，以及不同温度下Co-Ti-Ni三元系fcc相中示踪扩散系数的计算结果与分子动力学计算结果的对比图，随成分变化的示踪扩散系数DNi*[85]

图6 不同冷却速率下Co-Ti-Al和Ni-Si-Hf三元系合金热裂敏感性系数随成分变化的分布[85]

图7 相场法模拟的Co-9Al-9W合金在900℃经过不同时效时间后Al与W的浓度分布[107]

1	Sims C T, Stoloff N S, Hagel W C. Superalloys II [M]. New York: Wiley, 1987: 1
2	Roskill Information Services. Superalloys: An Introduction [M]. Lasne, Belgium: Tantalum-Niobium International Study Center, 2016: 10
3	Shi C X, Zhong Z Z. Fifty Years of High Temperature Alloys in China [M]. Beijing: Metallurgical Industry Press, 2006: 1
3	师昌绪, 仲增墉. 中国高温合金五十年 [M]. 北京: 冶金工业出版社, 2006: 1
4	Huang W, Chang Y A. A thermodynamic analysis of the Ni-Al system [J]. Intermetallics, 1998, 6: 487 doi: 10.1016/S0966-9795(97)00099-X
5	Yokokawa T, Harada H, Kawagishi K, et al. Advanced alloy design program and improvement of sixth-generation Ni-base single crystal superalloy TMS-238 [A]. Superalloys 2020 [C]. Cham: Springer, 2020: 122
6	Bhadeshia H K D H. Nickel based superalloys [M]. Cambridge: University of Cambridge, 2003: 1
7	Kawagishi K, Yeh A C, Yokokawa T, et al. Development of an oxidation-resistant high-strength sixth-generation single-crystal superalloy TMS-238 [A]. Superalloys 2012 [C]. Hoboken: John Wiley & Sons, Inc., 2012: 189
8	Liu L, Zhang J, Ai C. Nickel-based superalloys [A]. Reference Module in Materials Science and Materials Engineering [M]. Amsterdam: Elsevier, 2020: 1
9	Senkov O N, Miracle D B, Chaput K J, et al. Development and exploration of refractory high entropy alloys—A review [J]. J. Mater. Res., 2018, 33: 3092 doi: 10.1557/jmr.2018.153
10	Perepezko J H. The hotter the engine, the better [J]. Science, 2009, 326: 1068 doi: 10.1126/science.1179327 pmid: 19965415
11	Sato J, Omori T, Oikawa K, et al. Cobalt-base high-temperature alloys [J]. Science, 2006, 312: 90 pmid: 16601187
12	Lass E A, Grist R D, Williams M E. Phase equilibria and microstructural evolution in ternary Co-Al-W between 750 and 1100^oC [J]. J. Phase Equilib. Diffus., 2016, 37: 387 doi: 10.1007/s11669-016-0461-3
13	Pollock T M, Dibbern J, Tsunekane M, et al. New Co-based γ-γ′ high-temperature alloys [J]. JOM, 2010, 62(1): 58
14	Klein L, Bauer A, Neumeier S, et al. High temperature oxidation of γ/γ′-strengthened Co-base superalloys [J]. Corros. Sci., 2011, 53: 2027 doi: 10.1016/j.corsci.2011.02.033
15	Liu X J, Chen Z F, Chen Y C, et al. Multicomponent Co-Ti-based superalloy with high solvus temperature and low lattice misfit [J]. Mater. Lett., 2021, 284: 128910 doi: 10.1016/j.matlet.2020.128910
16	Ishida K. Intermetallic compounds in Co-base alloys—Phase stability and application to superalloys [J]. MRS Online Proc. Libr., 2008, 1128: 606
17	Epishin A, Petrushin N, Nolze G, et al. Investigation of the γ′- strengthened quaternary Co-based alloys Co-Al-W-Ta [J]. Metall. Mater. Trans., 2018, 49A: 4042
18	Zhou P J, Zhai D R, Guo Y H, et al. The role of Ti on reducing the misfit of a Co-Al-W alloy [A]. TMS 2014: 143rd Annual Meeting & Exhibition [C]. Cham: Springer, 2016: 667
19	Povstugar I, Zenk C H, Li R, et al. Elemental partitioning, lattice misfit and creep behaviour of Cr containing γ′ strengthened Co base superalloys [J]. Mater. Sci. Technol., 2016, 32: 220 doi: 10.1179/1743284715Y.0000000112
20	Yoo B, Im H J, Seol J B, et al. On the microstructural evolution and partitioning behavior of L1₂-structured γ′-based Co-Ti-W alloys upon Cr and Al alloying [J]. Intermetallics, 2019, 104: 97 doi: 10.1016/j.intermet.2018.10.027
21	Weiser M, Virtanen S. Influence of W content on the oxidation behaviour of ternary γ'-strengthened Co-based model alloys between 800 and 900^oC [J]. Oxid. Met., 2019, 92: 541 doi: 10.1007/s11085-019-09934-w
22	Xu Y T, Xia T D, Yan J Q, et al. Research on oxidation behavior of novel Co-Al-W alloy at high temperature [J]. Rare Met. Mater. Eng., 2011, 40: 1742
22	徐仰涛, 夏天东, 闫健强等. 新型Co-Al-W合金高温氧化行为研究 [J]. 稀有金属材料与工程, 2011, 40: 1742
23	Ma C M, Yang S T, Zhang Y H, et al. Effects of temperature and Ti addition on high-temperature oxidation behaviors of Co-Al-W based superalloys [J]. Anti-Corros. Methods Mater., 2020, 67: 445 doi: 10.1108/ACMM-04-2020-2298
24	Yu J X, Wang C L, Chen Y C, et al. Accelerated design of L1₂-strengthened Co-base superalloys based on machine learning of experimental data [J]. Mater. Des., 2020, 195: 108996 doi: 10.1016/j.matdes.2020.108996
25	Ruan J J, Xu W W, Yang T, et al. Accelerated design of novel W-free high-strength Co-base superalloys with extremely wide γ/γʹ region by machine learning and CALPHAD methods [J]. Acta Mater., 2020, 186: 425 doi: 10.1016/j.actamat.2020.01.004
26	Yu J X, Guo S, Chen Y C, et al. A two-stage predicting model for γ′ solvus temperature of L1₂-strengthened Co-base superalloys based on machine learning [J]. Intermetallics, 2019, 110: 106466 doi: 10.1016/j.intermet.2019.04.009
27	Tsakiropoulos P. Refractory metal (Nb) intermetallic composites, high entropy alloys, complex concentrated alloys and the alloy design methodology NICE—Mise-en-scène patterns of thought and progress [J]. Materials, 2021, 14: 989 doi: 10.3390/ma14040989
28	Mo T T, Song N, Xie G, et al. The study of crystallization process of high-purity silica at high temperature [J]. Light Met., 2015, (4): 49
28	莫腾腾, 宋宁, 谢刚等. 高温下高纯二氧化硅的结晶过程研究 [J]. 轻金属, 2015, (4): 49
29	Esparza N, Rangel V, Gutierrez A, et al. A comparison of the effect of Cr and Al additions on the oxidation behaviour of alloys from the Nb-Cr-Si system [J]. Mater. High Temp., 2016, 33: 105 doi: 10.1179/1878641315Y.0000000012
30	Vazquez A, Varma S K. High-temperature oxidation behavior of Nb-Si-Cr alloys with Hf additions [J]. J. Alloys Compd., 2011, 509: 7027 doi: 10.1016/j.jallcom.2011.02.174
31	Li Y, Zhu W F, Li Q, et al. Phase equilibria in the Nb-Ti side of the Nb-Si-Ti system at 1200^oC and its oxidation behavior [J]. J. Alloys Compd., 2017, 704: 311 doi: 10.1016/j.jallcom.2017.02.007
32	Li N, Zhang B D, Hang H, et al. Discussion of effects of Hf on the high temperature oxidation of Nb-based alloy [J]. New Technol. New Process, 2015, (4): 103
32	李宁, 张宝东, 黄辉等. 铪提高铌硅基合金高温抗氧化性能的机理探讨 [J]. 新技术新工艺, 2015, (4): 103
33	Han G M, Li F, Sun B D. Research progress in ultrahigh temperature Nb-Si based alloys [J]. Spec. Cast. Nonferrous Alloys, 2018, 38: 1071
33	韩国明, 李飞, 孙宝德. Nb-Si基超高温合金研究进展 [J]. 特种铸造及有色合金, 2018, 38: 1071 doi: 10.15980/j.tzzz.2018.10.008
34	Kim W Y, Yeo I D, Ra T Y, et al. Effect of V addition on microstructure and mechanical property in the Nb-Si alloy system [J]. J. Alloys Compd., 2004, 364: 186 doi: 10.1016/S0925-8388(03)00495-X
35	Kim W Y, Kim H S, Kim S K, et al. Effect of ternary alloying elements on microstructure and mechanical property of Nb-Si based refractory intermetallic alloy [J]. Mater. Sci. Forum, 2005, 486-487: 342 doi: 10.4028/www.scientific.net/MSF.486-487
36	Bewlay B P, Whiting P W, Davis A W, et al. Creep mechanisms in niobium-silicide based in-situ composites [J]. MRS Online Proc. Libr., 1998, 552: 6111
37	Neumann G, Tuijn C. Self-Diffusion and Impurity Diffusion in Pure Metals: Handbook of Experimental Data [M]. London: Pergamon, 2011: 1
38	Chen J, Liu Y J, Sheng G, et al. Atomic mobilities, interdiffusivities and their related diffusional behaviors in fcc Co-Cr-Ni alloys [J]. J. Alloys Compd., 2015, 621: 428 doi: 10.1016/j.jallcom.2014.09.139
39	Liu B S, Ren Y P, Li H X, et al. Interdiffusion and impurity diffusion behavior in polycrystalline Mg-Y binary system [J]. J. Alloys Compd., 2021, 867: 159070 doi: 10.1016/j.jallcom.2021.159070
40	Hirano K, Fujikawa S. Impurity diffusion in aluminum [J]. J. Nucl. Mater., 1978, 69-70: 564 doi: 10.1016/0022-3115(78)90275-1
41	Mehrer H. Diffusion in Solids: Fundamentals, Methods, Materials, Diffusion-Controlled Processes [M]. Berlin, Heidelberg: Springer, 2007: 1
42	Zhang Q F, Chen Z Q, Zhong W, et al. Accurate and efficient measurement of impurity (dilute) diffusion coefficients without isotope tracer experiments [J]. Scr. Mater., 2017, 128: 32 doi: 10.1016/j.scriptamat.2016.09.040
43	Askill J. Tracer Diffusion Data for Metals, Alloys, and Simple Oxides [M]. Boston: Springer, 1970: 1
44	Askill J. Correlation of self diffusion data in metals as a function of thermal expansion coefficient [J]. Phys. Stat. Solidi, 1965, 11B: K49
45	Dushman S, Langmuir I. The diffusion coefficient in solids and its temperature coefficient [J]. Phys. Rev., 1922, 20: 113 doi: 10.1103/PhysRevA.20.113
46	Leclaire A D. Diffusion in Body-Centered Cubic Metals [M]. Metals Park, Ohio: American Society for Metals, 1965: 1
47	Neumann G, Tuijn C. Application of the thermodynamic model to the diffusion of substitutionally dissolved impurities in lead [J]. Physica, 2002, 319B: 343
48	Koerner R M, Lord Jr A E, Hsuan Y H. Arrhenius modeling to predict geosynthetic degradation [J]. Geotext. Geomembr., 1992, 11: 151 doi: 10.1016/0266-1144(92)90042-9
49	Han J J, Wang C P, Liu X J. A modified model to predict self-diffusion coefficients in metastable FCC, BCC and HCP structures [J]. J. Phase Equilib. Diffus., 2013, 34: 17 doi: 10.1007/s11669-012-0185-y
50	Leclaire A D, Lidiard A B. LIII. Correlation effects in diffusion in crystals [J]. Philos. Mag., 1956, 1A: 518
51	Neumann G, Hirschwald W. Impurity diffusion in F.C.C. metals [J]. Phys. Stat. Solidi, 1973, 55B: 99
52	Le Claire A D. On the theory of impurity diffusion in metals [J]. Philos. Mag., 1962, 7A: 141
53	Neumann G. A model for the calculation of monovacancy and divacancy contributions to the impurity diffusion in noble metals [J]. Phys. Stat. Solidi, 1987, 144B: 329
54	Neumann G, Tölle V, Tuijn C, et al. A modified thermodynamic model for the impurity diffusion via nearest- and next-nearest neighbour jumps in body-centred cubic metals of the groups V and VI [J]. Physica, 1997, 233B: 161
55	Lazarus D. Effect of screening on solute diffusion in metals [J]. Phys. Rev., 1954, 93: 973 doi: 10.1103/PhysRev.93.973
56	Rabinovitch A, Pelleg J. A simple model for impurity diffusion [J]. J. Phys., 1977, 7F: 1853
57	Shang S L, Zhou B C, Wang W Y, et al. A comprehensive first-principles study of pure elements: Vacancy formation and migration energies and self-diffusion coefficients [J]. Acta Mater., 2016, 109: 128 doi: 10.1016/j.actamat.2016.02.031
58	Mantina M, Wang Y, Chen L Q, et al. First principles impurity diffusion coefficients [J]. Acta Mater., 2009, 57: 4102 doi: 10.1016/j.actamat.2009.05.006
59	Andersson D A, Simak S I. Monovacancy and divacancy formation and migration in copper: A first-principles theory [J]. Phys. Rev., 2004, 70B: 115108
60	Hargather C Z, Shang S L, Liu Z K. A comprehensive first-principles study of solute elements in dilute Ni alloys: Diffusion coefficients and their implications to tailor creep rate [J]. Acta Mater., 2018, 157: 126 doi: 10.1016/j.actamat.2018.07.020
61	Ganeshan S, Hector L G, Liu Z K. First-principles calculations of impurity diffusion coefficients in dilute Mg alloys using the 8-frequency model [J]. Acta Mater., 2011, 59: 3214 doi: 10.1016/j.actamat.2011.01.062
62	Lu H J, Wu H, Zou N, et al. First-principles investigation on diffusion mechanism of alloying elements in dilute Zr alloys [J]. Acta Mater., 2018, 154: 161 doi: 10.1016/j.actamat.2018.05.015
63	Zou N, Lu H J, Lu X G. Impurity diffusion coefficients in BCC Nb from first-principles calculations [J]. J. Alloys Compd., 2019, 803: 684 doi: 10.1016/j.jallcom.2019.06.293
64	Zeng Y Z, Bai K W. High-throughput prediction of activation energy for impurity diffusion in fcc metals of Group I and VIII [J]. J. Alloys Compd., 2015, 624: 201 doi: 10.1016/j.jallcom.2014.11.091
65	Wu H, Lorenson A, Anderson B, et al. Robust FCC solute diffusion predictions from ab-initio machine learning methods [J]. Comput. Mater. Sci., 2017, 134: 160 doi: 10.1016/j.commatsci.2017.03.052
66	Lu H J, Zou N, Jacobs R, et al. Error assessment and optimal cross-validation approaches in machine learning applied to impurity diffusion [J]. Comput. Mater. Sci., 2019, 169: 109075 doi: 10.1016/j.commatsci.2019.06.010
67	Wei Z B, Yu J X, Lu Y, et al. Prediction of diffusion coefficients in fcc, bcc and hcp phases remained stable or metastable by the machine-learning methods [J]. Mater. Des., 2021, 198: 109287 doi: 10.1016/j.matdes.2020.109287
68	Smith W F, Hashemi J. Foundations of Materials Science and Engineering [M]. 4th Ed., New York: McGraw-Hill Publishing, 2006: 1
69	Matano C. On the relation between diffusion-coefficients and concentrations of solid metals [J]. Jpn. J. Appl. Phys., 1933, 8: 109
70	den Broeder F J A. A general simplification and improvement of the matano-boltzmann method in the determination of the interdiffusion coefficients in binary systems [J]. Scr. Metall., 1969, 3: 321 doi: 10.1016/0036-9748(69)90296-8
71	Kirkaldy J S. Diffusion in multicomponent metallic systems [J]. Can. J. Phys., 1957, 35: 435 doi: 10.1139/p57-047
72	Whittle D P, Green A. The measurement of diffusion coefficients in ternary systems [J]. Scr. Metall., 1974, 8: 883 doi: 10.1016/0036-9748(74)90311-1
73	Chen W M, Zhang L J, Du Y, et al. A pragmatic method to determine the composition-dependent interdiffusivities in ternary systems by using a single diffusion couple [J]. Scr. Mater., 2014, 90-91: 53 doi: 10.1016/j.scriptamat.2014.07.016
74	Zhong J, Chen W M, Zhang L J. HitDIC: A free-accessible code for high-throughput determination of interdiffusion coefficients in single solution phase [J]. Calphad, 2018, 60: 177 doi: 10.1016/j.calphad.2017.12.004
75	Zhong J, Li Q, Deng C M, et al. Automated development of an accurate diffusion database in FCC AlCoCrFeNi high-entropy alloys from a big dataset of composition profiles [J]. Materials, 2022, 15: 3240 doi: 10.3390/ma15093240
76	Liu F, Wang Z X, Wang Z, et al. High‐throughput method—Accelerated design of Ni-based superalloys [J]. Adv. Funct. Mater., 2022, 32: 2109367 doi: 10.1002/adfm.v32.28
77	Heumann T. Zur berechnung von diffusionskoeffizienten bei ein- und mehrphasiger diffusion in festen legierungen [J]. Z. Phys. Chem., 1952, 201: 168 doi: 10.1515/zpch-1952-20114
78	Fitzer E, Schmidt F K. Die diffusion von silizium in Nb₅Si₃: The diffusion of silicon in Nb₅Si₃ [J]. Monatsh. Chem./Chem. Mon., 1971, 102: 1608
79	Darken L S. Diffusion, mobility and their interrelation through free energy in binary metallic system [J]. Trans. AIME, 1948, 175: 184
80	Marian J, Wirth B D, Odette G R, et al. Cu diffusion in α-Fe: Determination of solute diffusivities using atomic-scale simulations [J]. Comput. Mater. Sci., 2004, 31: 347 doi: 10.1016/j.commatsci.2004.03.023
81	Pan L. Atomic simulations of the diffusion process of Cr in Fe-Cr alloy [D]. Nanjing: Nanjing University of Science and Technology, 2015
81	潘龙. Cr在FeCr合金中扩散过程的原子尺度模拟研究 [D]. 南京: 南京理工大学, 2015
82	Maksimenko V N, Lipnitskii A G, Saveliev V N, et al. Prediction of the diffusion characteristics of the V-Cr system by molecular dynamics based on N-body interatomic potentials [J]. Comput. Mater. Sci., 2021, 198: 110648 doi: 10.1016/j.commatsci.2021.110648
83	Huang X S, Liu L H, Duan X B, et al. Atomistic simulation of chemical short-range order in HfNbTaZr high entropy alloy based on a newly-developed interatomic potential [J]. Mater. Des., 2021, 202: 109560 doi: 10.1016/j.matdes.2021.109560
84	Wei Z B, Wang C P, Xu W W, et al. A predictive model of impurity diffusion coefficients in face-centered-cubic metallic systems based on machine-learning [J]. Calphad, 2021, 72: 102251 doi: 10.1016/j.calphad.2021.102251
85	Wei Z B. Establishment and application of kinetic databases for the novel Co-based and Nb-Si-based high-temperature alloys [D]. Xiamen: Xiamen University, 2022
85	魏振帮. 新型Co基和Nb-Si基高温合金扩散动力学数据库的建立及应用 [D]. 厦门. 厦门大学, 2022
86	Zhang L, Du Y, Ouyang Y, et al. Atomic mobilities, diffusivities and simulation of diffusion growth in the Co-Si system [J]. Acta Mater., 2008, 56: 3940 doi: 10.1016/j.actamat.2008.04.017
87	Cui Y W, Jiang M, Ohnuma I, et al. Computational study of atomic mobility for fcc phase of Co-Fe and Co-Ni binaries [J]. J. Phase Equilib. Diffus., 2008, 29: 2 doi: 10.1007/s11669-007-9238-z
88	Cui Y W, Tang B, Kato R, et al. Interdiffusion and atomic mobility for face-centered-cubic Co-Al alloys [J]. Metall. Mater. Trans., 2011, 42A: 2542
89	Liu Y J, Zhang L J, Pan T Y, et al. Study of diffusion mobilities of Nb and Zr in bcc Nb-Zr alloys [J]. Calphad, 2008, 32: 455 doi: 10.1016/j.calphad.2008.06.008
90	Liu Y J, Pan T Y, Zhang L J, et al. Kinetic modeling of diffusion mobilities in bcc Ti-Nb alloys [J]. J. Alloys Compd., 2009, 476: 429 doi: 10.1016/j.jallcom.2008.09.019
91	Liu Y J, Yu D, Zhang L J, et al. Atomic mobilities and diffusional growth in solid phases of the V-Nb and V-Zr systems [J]. Calphad, 2009, 33: 425 doi: 10.1016/j.calphad.2008.12.008
92	Yang Y L, Shi Z, Luo Y S, et al. Interdiffusion and atomic mobility studies in Ni-rich fcc Ni-Co-Al alloys [J]. J. Phase Equilib. Diffus., 2016, 37: 269 doi: 10.1007/s11669-016-0453-3
93	Wang C P, Qin S Y, Lu Y, et al. Interdiffusion and atomic mobilities in fcc Co-Cr-Mo Alloys [J]. J. Phase Equilib. Diffus., 2018, 39: 437 doi: 10.1007/s11669-018-0657-9
94	Wang C P, Yu X, Qin S Y, et al. Interdiffusion and atomic mobilities in fcc Ni-Mo-Ta alloys [J]. J. Phase Equilib. Diffus., 2019, 40: 432 doi: 10.1007/s11669-019-00739-7
95	Liu X J, Yu Y, Lu Y, et al. Interdiffusion and atomic mobilities in Co-rich fcc Co-Cr-V alloys [J]. Rare Met. Mater. Eng., 2018, 47: 3251 doi: 10.1016/S1875-5372(18)30228-5
96	Wang C P, Qin S Y, Lu Y, et al. Interdiffusion and atomic mobilities in Ni-rich fcc Ni-Cr-W Alloys [J]. Rare Met. Mater. Eng., 2020, 49: 441
97	Wei Z B, Wang C P, Qin S Y, et al. Assessment of atomic mobilities for bcc phase in the Ti-Nb-V system [J]. J. Phase Equilib. Diffus., 2020, 41: 191 doi: 10.1007/s11669-020-00801-9
98	Chen Q, Jou H J, Sterner G. TC-PRISMA User's Guide and Examples [M]. Stockholm: Thermo-Calc Software AB, 2011: 1
99	Wang Y. Study on the thermodynamics of the Ni-Co-Al-Mo-W system and the diffusion kinetics of its fcc phase [D]. Shanghai: Shanghai University, 2018
99	王杨. Ni-Co-Al-Mo-W体系热力学及其fcc相扩散动力学研究 [D]. 上海: 上海大学, 2018
100	Azzam A, Philippe T, Hauet A, et al. Kinetics pathway of precipitation in model Co-Al-W superalloy [J]. Acta Mater., 2018, 145: 377 doi: 10.1016/j.actamat.2017.12.032
101	Wang W, Hou Z Y, Lizárraga R, et al. An experimental and theoretical study of duplex fcc + hcp cobalt based entropic alloys [J]. Acta Mater., 2019, 176: 11 doi: 10.1016/j.actamat.2019.06.041
102	Eiken J, Böttger B, Steinbach I. Multiphase-field approach for multicomponent alloys with extrapolation scheme for numerical application [J]. Phys. Rev., 2006, 73E: 066122
103	Rabbe D, translated by Xiang J Z, Wu X H. Computational Materials Science [M]. Beijing: Chemical Industry Press, 2002: 1
103	Rabbe D著, 项金钟, 吴兴惠译. 计算材料学 [M]. 北京: 化学工业出版社, 2002: 1
104	Yang Y F, Xie M, Cheng Y, et al. Research status of numerical simulation of solidification microstructure [J]. Mater. Rep., 2014, 28(21): 24
104	杨云峰, 谢明, 程勇等. 金属凝固微观组织数值模拟研究现状 [J]. 材料导报, 2014, 28(21): 24
105	Shi S J, Yan Z W, Li Y S, et al. Phase-field simulation of early-stage kinetics evolution of γ' phase in medium supersaturation Co-Al-W alloy [J]. J. Mater. Sci. Technol., 2020, 53: 1 doi: 10.1016/j.jmst.2020.02.038
106	Chen J, Guo M, Yang M, et al. Phase-field simulation of γ' coarsening behavior in cobalt-based superalloy [J]. Comput. Mater. Sci., 2021, 191: 110358 doi: 10.1016/j.commatsci.2021.110358
107	Liu X J, Kong H F, Lu Y, et al. Phase-field simulation on microstructure evolution of D0₁₉ phase in γ/γ′ structure of Co-Al-W superalloys [J]. Prog. Nat. Sci.: Mater. Int., 2020, 30: 382 doi: 10.1016/j.pnsc.2020.05.004
108	Wang C, Ali M A, Gao S W, et al. Combined phase-field crystal plasticity simulation of P- and N-type rafting in Co-based superalloys [J]. Acta Mater., 2019, 175: 21 doi: 10.1016/j.actamat.2019.05.063

[1]	冯强, 路松, 李文道, 张晓瑞, 李龙飞, 邹敏, 庄晓黎. γ' 相强化钴基高温合金成分设计与蠕变机理研究进展[J]. 金属学报, 2023, 59(9): 1125-1143.
[2]	陈佳, 郭敏, 杨敏, 刘林, 张军. 新型钴基高温合金中W元素对蠕变组织和性能的影响[J]. 金属学报, 2023, 59(9): 1209-1220.
[3]	陈礼清, 李兴, 赵阳, 王帅, 冯阳. 结构功能一体化高锰减振钢研究发展概况[J]. 金属学报, 2023, 59(8): 1015-1026.
[4]	冯艾寒, 陈强, 王剑, 王皞, 曲寿江, 陈道伦. 低密度Ti₂AlNb基合金热轧板微观组织的热稳定性[J]. 金属学报, 2023, 59(6): 777-786.
[5]	王长胜, 付华栋, 张洪涛, 谢建新. 冷轧变形对高性能Cu-Ni-Si合金组织性能与析出行为的影响[J]. 金属学报, 2023, 59(5): 585-598.
[6]	李民, 王继杰, 李昊泽, 邢炜伟, 刘德壮, 李奥迪, 马颖澈. Y对无取向6.5%Si钢凝固组织、中温压缩变形和软化机制的影响[J]. 金属学报, 2023, 59(3): 399-412.
[7]	唐伟能, 莫宁, 侯娟. 增材制造镁合金技术现状与研究进展[J]. 金属学报, 2023, 59(2): 205-225.
[8]	王虎, 赵琳, 彭云, 蔡啸涛, 田志凌. 激光熔化沉积TiB₂ 增强TiAl基合金涂层的组织及力学性能[J]. 金属学报, 2023, 59(2): 226-236.
[9]	李会朝, 王彩妹, 张华, 张建军, 何鹏, 邵明皓, 朱晓腾, 傅一钦. 搅拌摩擦增材制造技术研究进展[J]. 金属学报, 2023, 59(1): 106-124.
[10]	卢海飞, 吕继铭, 罗开玉, 鲁金忠. 激光热力交互增材制造Ti6Al4V合金的组织及力学性能[J]. 金属学报, 2023, 59(1): 125-135.
[11]	高栋, 周宇, 于泽, 桑宝光. 液氮温度下纯Ti动态塑性变形中的孪晶变体选择[J]. 金属学报, 2022, 58(9): 1141-1149.
[12]	马志民, 邓运来, 刘佳, 刘胜胆, 刘洪雷. 淬火速率对7136铝合金应力腐蚀开裂敏感性的影响[J]. 金属学报, 2022, 58(9): 1118-1128.
[13]	沈岗, 张文泰, 周超, 纪焕中, 罗恩, 张海军, 万国江. 热挤压Zn-2Cu-0.5Zr合金的力学性能与降解行为[J]. 金属学报, 2022, 58(6): 781-791.
[14]	余春, 徐济进, 魏啸, 陆皓. 核级镍基合金焊接材料失塑裂纹研究现状[J]. 金属学报, 2022, 58(4): 529-540.
[15]	何焕生, 余黎明, 刘晨曦, 李会军, 高秋志, 刘永长. 新一代马氏体耐热钢G115的研究进展[J]. 金属学报, 2022, 58(3): 311-323.

Viewed

Full text

Abstract

Cited

Shared

Discussed