Please wait a minute...
Acta Metall Sin  2026, Vol. 62 Issue (1): 29-46    DOI: 10.11900/0412.1961.2025.00238
Overview Current Issue | Archive | Adv Search |
Research Progress on High-Strength Al-Mg-Sc Alloys Fabricated by Wire Arc Additive Manufacturing: Metallurgical Defects, Microstructure, and Performance
MA Chengyong1(), HOU Xuru1,2, ZHAO Lin1(), KAN Chengling1, CAO Yang1, PENG Yun1, TIAN Zhiling1
1 Central Iron and Steel Research Institute, Beijing 100081, China
2 Institute of Machinery Manufacturing Technology, China Academy of Engineering Physics, Mianyang 621900, China
Cite this article: 

MA Chengyong, HOU Xuru, ZHAO Lin, KAN Chengling, CAO Yang, PENG Yun, TIAN Zhiling. Research Progress on High-Strength Al-Mg-Sc Alloys Fabricated by Wire Arc Additive Manufacturing: Metallurgical Defects, Microstructure, and Performance. Acta Metall Sin, 2026, 62(1): 29-46.

Download:  HTML  PDF(7369KB) 
Export:  BibTeX | EndNote (RIS)      
Abstract  

Wire arc additive manufacturing (WAAM) has emerged as one of the most promising technologies for producing large and complex components due to its low cost, high deposition efficiency, and absence of size limitations. It is particularly suitable for Al-Mg-Sc alloys, which exhibit excellent weldability. This article provides a detailed review of studies from the past five years on WAAM Al-Mg-Sc alloys, focusing on metallurgical defects, microstructural evolution, and resulting performance. Existing researches indicated that in WAAM, optimizing wire compositions, process parameters, and introducing interlayer friction stir processing (FSP) can effectively reduce porosity, improve microstructure, and enhance performance. The lowest porosity was about 0.026%. Due to the strong microalloying effect of Sc, the microstructures were all equiaxed grains with an average grain size of about 10 μm. The alloys also exhibited excellent performance, achieving a highest tensile strength of approximately 470 MPa after direct aging, along with outstanding plasticity. However, the development of WAAM-specific Al-Mg-Sc wires, the mechanisms underlying metallurgical defect formation, the control of coarse and fine Al3(Sc1 - x, Zr x ) precipitates, and the systematic evaluation of multi-property performance still need to be further addressed. Finally, considering the advantages of machine learning (ML) in the intelligent manufacturing, this review discussed its potential applications in WAAM, including forward performance prediction and reverse optimization of alloy compositions and processing parameters. Such ML-assisted approaches were expected to accelerate the development of high-strength Al-Mg-Sc filler wires, reduce manufacturing costs, and shorten alloy and process development cycles.

Key words:  wire arc additive manufacturing (WAAM)      high-strength Al-Mg-Sc alloy      metallurgical defect      microstructure and performance      machine learning     
Received:  19 August 2025     
ZTFLH:  TG146.2  
Fund: National Key Research and Development Program of China(2024YFB4609700)

URL: 

https://www.ams.org.cn/EN/10.11900/0412.1961.2025.00238     OR     https://www.ams.org.cn/EN/Y2026/V62/I1/29

Fig.1  Schematic of wire arc additive manufacturing (WAAM)
Fig.2  Schematics of three types of WAAM technologies (a-c)[5] and the characteristics of them and cold metal transfer (CMT) technologies (d)[26,27] (GMAW—gas metal arc welding, GTAW—gas tungsten arc welding, PAW—plasma arc welding)
(a) GMAW-WAAM (b) GTAW-WAAM (c) PAW-WAAM
Fig.3  Schematics of droplet transfer (a-d)[29] and waveform diagrams of welding power sources in different CMT modes (e-h) (T means a period of the welding power)
(a) arcing stage (b) short-circuit stage (c) wire retraction (d) arcing stage
(e) CMT (f) CMT + pulse (CMT + P)
(g) CMT + advance (CMT + Adv) (h) CMT + pulse + advance (CMT + Padv)
Fig.4  Phase diagram of Al rich Al-Sc alloy
Fig.5  Schematics of hydrogen supersaturation during the solidification process[47] (a) and solubility of hydrogen in aluminum versus temperature[46] (b) (C—concentration, r—radial distance, V—interface growth velocity, R—radius at the interface, Cs* and Cl*—hydrogen concentrations in the solid and liquid phases on either side of the interface, respectively, Cl—actual concentration, CsolH—solubility of hydrogen in the aluminium melt, C0—initial hydrogen content)
Fig.6  Statistical results of pores in the components of WAAW Al-Mg-Sc-Zr alloys[43]
(a-c) porosity (a), number density (b), and average diameter (c) at different welding speeds (d-g) distributions of diameter (d) and partially enlarged view (inset) in the components at different welding speeds (d, f) and spatial distributions of pores which diameter was above 50 μm (e, g) with 0.36Sc + 0.11Zr (d, e) and 0.72Sc + 0.23Zr (f, g) alloys
Fig.7  Pore distribution results of WAAM Al-Mg-Sc-Zr alloys with different printing methods[13]
(a-c) X-ray computed tomography images of pore in components with interlayer temperature 100 oC (named IW) (a) and continuous printing (named CP) (b), and the corresponding maximum pores (c)
(d) diameter distribution of pores and partially englarged view (inset)
(e) area fraction of pores layer by layer
Fig.8  Microstructure (a, b) and mechanical properties (c, d) of WAAM Al-Mg-Sc alloys[58] (HAGBs——high-angle grain boundaries, 15°; LAGBs—low-angle grain boundaries, 2°-15°; GS—average grain size;YS—yield strength, UTS—ultimate tensile strength; TD—travelling direction, BD—building direction)
(a) AlMgScZr (b) AlMgScTi (c) hardness (d) tensile properties
Fig.9  Microstructures and corrosion resistances of WAAM Al-Mg-Sc-Zr alloy[61] (ITZ—inter-layer zone, MPB—molten pool boundary, WADED—wire arc directed energy deposited, i—corrosion current density, OCP—open circuit potential)
(a, b) inverse pole figures (IPFs) (c, d) open circuit potential (c) and statistic results (d) in 3.5%NaCl solution (e-h) potentiodynamic polarization curves
Fig.10  Microstructure and mechanical properties of WAAM Al-Mg-Sc-Ti alloys with different printing modes[49] (EL—elongation, FG—fine grain, CG—coarse grain)
(a) CMT (b) CMT + PA (Padv)
(c) schematic of microstructures (d) tensile properties
Fig.11  Microstructures of WAAM Al-Mg-Sc-Zr alloys[13] (RZ—remelted zone, MZ—middle zone, TZ—top zone, FEG—fine equiaxed grain, CEG—coarse equiaxed grain)
(a) interlayer temperature 100 oC
(b) continuous printing
Fig.12  Microstructure evolution mechanisms (a-f) and strengthening mechanism (g) of WAAM Al-Mg-Sc-Zr alloy[13] (FGZ—fine equiaxed grain zone, CGZ—coarse equiaxed grain zone; σ0 is the YS of pure Al (30-50 MPa); σHP, σSS, σP, and σD are the YS induced by grain refinement, solid solution strengthening, precipitation strengthening, and dislocation strengthening, respectively)
Fig.13  Relationship between UTS and EL of WAAM Al-Mg-Sc alloys[13,49,51,53,54,58,59,61,63,64] (FSP—friction stir processing)
Fig.14  Application of machine learning (ML) algorithm in WAAM (TS—travel speed, WFS—wire feed rate, RF—random forest, ANN—artificial neural network, T—temperature, F—residual stress)
(a) path optimization[71]
(b) prediction of residual stress[74]
Fig.15  Defect monitoring process based on reinforcement learning in WAAM[77]
(a) data collection
(b) feature extraction
(c, d) support vector machines (SVM) classification results
[1] Montevecchi F, Venturini G, Grossi N, et al. Idle time selection for wire-arc additive manufacturing: A finite element-based technique [J]. Addit. Manuf., 2018, 21: 479
[2] Gordon J V, Haden C V, Nied H F, et al. Fatigue crack growth anisotropy, texture and residual stress in austenitic steel made by wire and arc additive manufacturing [J]. Mater. Sci. Eng., 2018, A724: 431
[3] Wang G Q, Zhao Y H, Hao Y F. Friction stir welding of high-strength aerospace aluminum alloy and application in rocket tank manufacturing [J]. J. Mater. Sci. Technol., 2018, 34: 73
[4] Zou Y, Cao L F, Wu X D, et al. Revealing the coarsening behavior of precipitates and its effect on the thermal stability in Tʹ and ηʹ dual-phase strengthened Al-Zn-Mg-Cu alloys [J]. J. Mater. Sci. Technol., 2025, 220: 54
[5] Wu B T, Pan Z X, Ding D H, et al. A review of the wire arc additive manufacturing of metals: Properties, defects and quality improvement [J]. J. Manuf. Process., 2018, 35: 127
[6] Dhinakaran V, Ajith J, Fahmidha A F Y, et al. Wire Arc Additive Manufacturing (WAAM) process of nickel based superalloys—A review [J]. Mater. Today: Proceed., 2020, 21: 920
[7] Derekar K S. A review of wire arc additive manufacturing and advances in wire arc additive manufacturing of aluminium [J]. Mater. Sci. Technol., 2018, 34: 895
[8] DebRoy T, Wei H L, Zuback J S, et al. Additive manufacturing of metallic components—Process, structure and properties [J]. Prog. Mater. Sci., 2018, 92: 112
[9] Li Y H, Wu S J, Wang J S, et al. Microstructure homogeneity and strength-toughness balance in submerged arc additive manufactured Mn-Ni-Mo high-strength steel by unique intrinsic heat treatment [J]. J. Mater. Process. Technol., 2022, 307: 117682
[10] Rodideal N, Machado C M, Infante V, et al. Mechanical characterization and fatigue assessment of wire and arc additively manufactured HSLA steel parts [J]. Int. J. Fatigue, 2022, 164: 107146
[11] Zhu S, Du W B. State-of-art of wire arc additive remanufacturing technology [J]. Electric Welding Machine, 2020, 50(9): 251
朱 胜, 杜文博. 电弧增材再制造技术研究进展 [J]. 电焊机, 2020, 50(9): 251
[12] Hou X R. Study on microstructure evolution mechanism and performance control of high-strength Al-Mg-Sc alloys fabricated by wire arc additive manufacturing [D]. Beijing: University of Science and Technology Beijing, 2025
侯旭儒. 电弧增材制造高强度Al-Mg-Sc系合金组织演变机理与性能调控研究 [D]. 北京: 北京科技大学, 2025
[13] Hou X R, Zhao L, Ren S B, et al. A comparative study on Al-Mg-Sc-Zr alloy fabricated by wire arc additive manufacturing with controlling interlayer temperature and continuous printing: Porosity, microstructure, and mechanical properties [J]. J. Mater. Sci. Technol., 2024, 193: 199
[14] Kazanas P, Deherkar P, Almeida P, et al. Fabrication of geometrical features using wire and arc additive manufacture [J]. Proc. Inst. Mech. Eng., 2012, 226B: 1042
[15] Bermingham M J, Thomson-Larkins J, St John D H, et al. Sensitivity of Ti-6Al-4V components to oxidation during out of chamber Wire + Arc Additive Manufacturing [J]. J. Mater. Process. Technol., 2018, 258: 29
[16] Williams S W, Martina F, Addison A C, et al. Wire + arc additive manufacturing [J]. Mater. Sci. Technol., 2016, 32: 641
[17] Hou X R, Zhao L, Ren S B, et al. Effect of heat input on microstructure and mechanical properties of marine high strength steel fabricated by wire arc additive manufacturing [J]. Acta Metall. Sin., 2023, 59: 1311
侯旭儒, 赵 琳, 任淑彬 等. 热输入对电弧增材制造船用高强钢组织与力学性能的影响 [J]. 金属学报, 2023, 59: 1311
[18] Gu J L, Gao M J, Yang S L, et al. Pore formation and evolution in wire + arc additively manufactured 2319 Al alloy [J]. Addit. Manuf., 2019, 30: 100900
[19] Su C C, Chen X Z, Gao C, et al. Effect of heat input on microstructure and mechanical properties of Al-Mg alloys fabricated by WAAM [J]. Appl. Surf. Sci., 2019, 486: 431
[20] Panchenko O, Kurushkin D, Mushnikov I, et al. A high-performance WAAM process for Al-Mg-Mn using controlled short-circuiting metal transfer at increased wire feed rate and increased travel speed [J]. Mater. Des., 2020, 195: 109040
[21] Røyset J, Ryum N. Scandium in aluminium alloys [J]. Int. Mater. Rev., 2005, 50: 19
[22] Davydov V G, Rostova T D, Zakharov V V, et al. Scientific principles of making an alloying addition of scandium to aluminium alloys [J]. Mater. Sci. Eng., 2000, A280: 30
[23] Hua Q, Wang W J, Li R D, et al. Microstructures and mechanical properties of Al-Mg-Sc-Zr alloy additively manufactured by laser direct energy deposition [J]. Chin. J. Mech. Eng.: Addit. Manuf. Front., 2022, 1: 100057
[24] Wang D, Feng Y W, Liu L Q, et al. Influence mechanism of process parameters on relative density, microstructure, and mechanical properties of low Sc-content Al-Mg-Sc-Zr alloy fabricated by selective laser melting [J]. Chin. J. Mech. Eng.: Addit. Manuf. Front., 2022, 1: 100034
[25] Shen X F, Cheng Z Y, Wang C G, et al. Effect of heat treatments on the microstructure and mechanical properties of Al-Mg-Sc-Zr alloy fabricated by selective laser melting [J]. Opt. Laser. Technol., 2021, 143: 107312
[26] Nikam P P, Arun D, Ramkumar K D, et al. Microstructure characterization and tensile properties of CMT-based wire plus arc additive manufactured ER2594 [J]. Mater. Charact., 2020, 169: 110671
[27] Kopf T, Glück T, Gruber D, et al. Process modeling and control for additive manufacturing of Ti-6Al-4V using plasma arc welding-methodology and experimental validation [J]. J. Manuf. Process., 2024, 126: 12
[28] Çam G. Prospects of producing aluminum parts by wire arc additive manufacturing (WAAM) [J]. Mater. Today: Proceed., 2022, 62: 77
[29] Lv F Y, Wang L L, Gao Z N, et al. Influence mechanism of arc characteristics on droplet transfer behavior in CMT-based additive manufacturing [J]. J. Mech. Eng., 2023, 59: 267
吕飞阅, 王磊磊, 高转妮 等. CMT电弧增材制造过程电弧特性对熔滴过渡行为的影响机理研究 [J]. 机械工程学报, 2023, 59: 267
[30] Norman A F, Prangnell P B, Mcewen R S. The solidification behaviour of dilute aluminium-scandium alloys [J]. Acta Mater., 1998, 46: 5715
[31] Deng Y, Yin Z M, Zhao K, et al. Effects of Sc and Zr microalloying additions on the microstructure and mechanical properties of new Al-Zn-Mg alloys [J]. J. Alloy. Compd., 2012, 530: 71
[32] Huang X, Pan Q L, Li B, et al. Effect of minor Sc on microstructure and mechanical properties of Al-Zn-Mg-Zr alloy metal-inert gas welds [J]. J. Alloy. Compd., 2015, 629: 197
[33] Dev S, Stuart A A, Kumaar R C R D, et al. Effect of scandium additions on microstructure and mechanical properties of Al-Zn-Mg alloy welds [J]. Mater. Sci. Eng., 2007, A467: 132
[34] Argade G R, Kumar N, Mishra R S. Stress corrosion cracking susceptibility of ultrafine grained Al-Mg-Sc alloy [J]. Mater. Sci. Eng., 2013, A565: 80
[35] Filatov Y A, Yelagin V I, Zakharov V V. New Al-Mg-Sc alloys [J]. Mater. Sci. Eng., 2000, A280: 97
[36] Ryen Ø, Holmedal B, Nijs O, et al. Strengthening mechanisms in solid solution aluminum alloys [J]. Metall. Mater. Trans., 2006, 37A: 1999
[37] Li R D, Wang M B, Li Z M, et al. Developing a high-strength Al-Mg-Si-Sc-Zr alloy for selective laser melting: Crack-inhibiting and multiple strengthening mechanisms [J]. Acta Mater., 2020, 193: 83
[38] Shi Y J, Yang K, Kairy S K, et al. Effect of platform temperature on the porosity, microstructure and mechanical properties of an Al-Mg-Sc-Zr alloy fabricated by selective laser melting [J]. Mater. Sci. Eng., 2018, A732: 41
[39] Wang Z H, Lin X, Kang N, et al. Making selective-laser-melted high-strength Al-Mg-Sc-Zr alloy tough via ultrafine and heterogeneous microstructure [J]. Scr. Mater., 2021, 203: 114052
[40] Marquis E A, Seidman D N. Coarsening kinetics of nanoscale Al3Sc precipitates in an Al-Mg-Sc alloy [J]. Acta Mater., 2005, 53: 4259
[41] Schmidtke K, Palm F, Hawkins A, et al. Process and mechanical properties: Applicability of a scandium modified Al-alloy for laser additive manufacturing [J]. Phys. Proc., 2011, 12: 369
[42] Harada Y, Dunand D C. Microstructure of Al3Sc with ternary transition-metal additions [J]. Mater. Sci. Eng., 2002, A329-331: 686
[43] Hou X R, Zhao L, Ren S B, et al. Study on the effects of alloying elements on porosity in Al-Mg-Sc-Zr alloy fabricated by wire arc directed energy deposition [J]. Addit. Manuf., 2024, 88: 104260
[44] Anyalebechi P N. Hydrogen-induced gas porosity formation in Al-4.5 wt% Cu-1.4 wt% Mg alloy [J]. J. Mater. Sci., 2013, 48: 5342
[45] Da Silva C L M, Scotti A. The influence of double pulse on porosity formation in aluminum GMAW [J]. J. Mater. Process. Technol., 2006, 171: 366
[46] Trometer N, Chen B W, Moodispaw M, et al. Modeling and validation of hydrogen porosity formation in aluminum laser welding [J]. J. Manuf. Process., 2024, 124: 877
[47] Wang Z N, Lu X F, Lin X, et al. Porosity control and properties improvement of Al-Cu alloys via solidification condition optimisation in wire and arc additive manufacturing [J]. Virtual Phys. Prototy., 2024, 19: e2414408
[48] Ren S M, Cong F G, Wang J G, et al. Comparative study of additive manufacturing thin-walled component with Al-Mg-Sc-Zr alloy using different arc modes [J]. J. Mater. Res. Technol., 2025, 35: 5665
[49] Li K, Fang X W, Yang J N, et al. Wire-arc directed energy deposition of high performance heat treatment free Al-6Mg-0.3Sc alloy [J]. J. Manuf. Process., 2024, 125: 589
[50] Derekar K S, Addison A, Joshi S S, et al. Effect of pulsed metal inert gas (pulsed-MIG) and cold metal transfer (CMT) techniques on hydrogen dissolution in wire arc additive manufacturing (WAAM) of aluminium [J]. Inter. J. Adv. Manuf. Technol., 2020, 107: 311
[51] Hou X R, Zhao L, Ren S B, et al. Synergistically improving the strength and anisotropy of wire arc additively manufactured Al-Mg-Sc-Zr alloy by regulating heat input [J]. Addit. Manuf. Front., 2025, 4: 200215
[52] Yan H T, Xiao G. Study on hydrogen in aluminum melt [J]. Alum. Fabri., 2006: 9
闫红涛, 肖 刚. 铝熔体中的氢的研究 [J]. 铝加工, 2006: 9
[53] Xu H F, Yang L J, Huang Y M, et al. Study on the microstructure and properties of additive manufacturing Al-Mg-Sc alloy with CMT-PADV + arc weaving process [J/OL]. J. Mater. Eng. Perform., (2025-07-07).
[54] Cui Y P, Guo X P, Xu R Z, et al. Enhanced strength and ductility in wire-arc directed energy deposited Al-Mg-Sc alloy assisted by interlayer friction stir processing [J]. Mater. Sci. Eng., 2025, A944: 148856
[55] He C S, Wei J X, Li Y, et al. Improvement of microstructure and fatigue performance of wire-arc additive manufactured 4043 aluminum alloy assisted by interlayer friction stir processing [J]. J. Mater. Sci. Technol., 2023, 133: 183
[56] Qie M F, Wei J X, He C S. Microstructure evolution and mechanical properties of wire-arc additive manufactured Al-Zn-Mg-Cu alloy assisted by interlayer friction stir processing [J]. J. Mater. Res. Technol., 2023, 24: 2891
[57] Wei J X, He C S, Zhao Y, et al. Evolution of microstructure and properties in 2219 aluminum alloy produced by wire arc additive manufacturing assisted by interlayer friction stir processing [J]. Mater. Sci. Eng., 2023, A868: 144794
[58] Wang Z B, Li B C, Chen X, et al. Comparative study on microstructure and mechanical properties of Ti and Zr micro-alloyed AlMgSc alloy deposits fabricated via wire-arc directed energy deposition [J]. J. Alloys Compd., 2025, 1034: 181420
[59] Ren L L, Gu H M, Wang W, et al. Effect of Sc content on the microstructure and properties of Al-Mg-Sc alloys deposited by wire arc additive manufacturing [J]. Met. Mater. Int., 2020, 27: 68
[60] Gao C Y, Xie H, Huang H F, et al. Effect of trace Sc addition on microstructure, mechanical and stress corrosion cracking properties of Al-Mg alloys fabricated by Wire Arc Additive Manufacturing (WAAM) [J]. J. Alloys Compd., 2025, 1021: 179575
[61] Zhou Y B, Qi Z W, Cong B Q, et al. Influence of in-situ precipitation on corrosion behaviors of wire arc directed energy deposited Al-Mg(-Sc-Zr) [J]. J. Mater. Sci. Technol. 2025, 228: 172
[62] Cui Y P, Guo X P, Xue P, et al. A composite structure of Al-Mg-Sc alloy prepared by wire arc‑directed energy deposition with interlayer friction stir processing [J]. Acta Metall. Sin. (Eng. Lett.), 2025, 38: 1794
[63] Zhou Y B, Qi Z W, Cong B Q, et al. Sc/Zr microalloying on strength-corrosion performance synergy of wire-arc directed energy deposited Al-Mg [J]. Virtual Phys. Prototy., 2024, 19: e2358981
[64] Cui J Y, Guo X P, Hao S, et al. Achieving high strength-ductility properties of wire-arc additive manufactured Al-Mg-Sc aluminum alloy via friction stir processing post-treatment and high temperature aging treatment [J]. Mater. Lett., 2023, 350: 134913
[65] Kang H S, Lee J Y, Choi S, et al. Smart manufacturing: Past research, present findings, and future directions [J]. Int. J. Precis. Eng. Manuf.-Green Technol., 2016, 3: 111
[66] Chigilipalli B K, Veeramani A. A machine learning approach for the prediction of tensile deformation behavior in wire arc additive manufacturing [J]. Int. J. Interact. Des. Manuf., 2025, 19: 185
[67] Hinton G E, Osindero S, Teh Y W. A fast learning algorithm for deep belief nets [J]. Neural Comput., 2006, 18: 1527
[68] Yang Q, Gu Y D, Wu D S. Survey of incremental learning [A]. Proceedings of the 2019 Chinese Control and Decision Conference (CCDC) [C]. Nanchang: IEEE, 2019: 399
[69] Wang H, Gao S L, Wang B T, et al. Recent advances in machine learning-assisted fatigue life prediction of additive manufactured metallic materials: A review [J]. J. Mater. Sci. Technol., 2024, 198: 111
[70] Li Y Z, Sun Y F, Han Q L, et al. Enhanced beads overlapping model for wire and arc additive manufacturing of multi-layer multi-bead metallic parts [J]. J. Mater. Process. Technol., 2018, 252: 838
[71] Ding D H, Yuan L, Huang R, et al. Corner path optimization strategy for wire arc additive manufacturing of gap-free shapes [J]. J. Manuf. Process., 2023, 85: 683
[72] Nguyen L, Buhl J, Bambach M. Continuous Eulerian tool path strategies for wire-arc additive manufacturing of rib-web structures with machine-learning-based adaptive void filling [J]. Addit. Manuf., 2020, 35: 101265
[73] Barrionuevo G O, Sequeira-Almeida P M, Ríos S, et al. A machine learning approach for the prediction of melting efficiency in wire arc additive manufacturing [J]. Int. J. Adv. Manuf. Technol., 2022, 120: 3123
[74] Wu Q, Mukherjee T, De A, et al. Residual stresses in wire-arc additive manufacturing—Hierarchy of influential variables [J]. Addit. Manuf., 2020, 35: 101355
[75] Farias F W C, Payao J D C P, Oliveira V H P M E. Prediction of the interpass temperature of a wire arc additive manufactured wall: FEM simulations and artificial neural network [J]. Addit. Manuf., 2021, 48: 102387
[76] Le V T, Nguyen H D, Bui M C, et al. Rapid and accurate prediction of temperature evolution in wire plus arc additive manufacturing using feedforward neural network [J]. Manuf. Lett., 2022, 32: 28
[77] Li Y X, Polden J, Pan Z X, et al. A defect detection system for wire arc additive manufacturing using incremental learning [J]. J. Ind. Inf. Integr., 2022, 27: 100291
[78] Liu Y, Liu Z Z, Zhou G S, et al. Microstructures and properties of Al-Mg alloys manufactured by WAAM-CMT [J]. Materials, 2022, 15: 5460
[79] Fan S L, Yang F, Zhu X N, et al. Numerical analysis on the effect of process parameters on deposition geometry in wire arc additive manufacturing [J]. Plasma Sci. Technol., 2022, 24: 044001
[80] Oh W J, Lee C M, Kim D H. Prediction of deposition bead geometry in wire arc additive manufacturing using machine learning [J]. J. Mater. Res. Technol., 2022, 20: 4283
[81] Yun P W, Fu H D, Zhang H T, et al. Rapid design of high-end copper alloy processes combining orthogonal experiments, machine learning, and Pareto analysis [J]. J. Mater. Res. Technol., 2025, 36: 1005
[82] Zhao S, Li J S, Wang J, et al. Closed-loop inverse design of high entropy alloys using symbolic regression-oriented optimization [J]. Mater. Today, 2025, 88: 263
[83] Su J L, Chen L Q, Van Petegem S, et al. Additive manufacturing metallurgy guided machine learning design of versatile alloys [J]. Mater. Today, 2025, 88: 240
[1] HUANG Ke, LI Xinzhi, FANG Xuewei, LU Bingheng. State-of-the-Art Progress and Outlook in Wire Arc Additive Manufacturing of Magnesium Alloys[J]. 金属学报, 2025, 61(3): 397-419.
[2] LIU Zhuangzhuang, DING Minglu, XIE Jianxin. Advancements in Digital Manufacturing for Metal 3D Printing[J]. 金属学报, 2024, 60(5): 569-584.
[3] WEN Tongqi, LIU Huaiyi, GONG Xiaoguo, YE Beilin, LIU Siyu, LI Zhuoyuan. Deep Potentials for Materials Science[J]. 金属学报, 2024, 60(10): 1299-1311.
[4] LIU Shi, HUANG Jiawei, WU Jing. Application of Machine Learning Force Fields for Modeling Ferroelectric Materials[J]. 金属学报, 2024, 60(10): 1312-1328.
[5] CHEN Mingyi, HU Junwei, YU Yaochen, NIU Haiyang. Advances in Machine Learning Molecular Dynamics to Assist Materials Nucleation and Solidification Research[J]. 金属学报, 2024, 60(10): 1329-1344.
[6] WANG Guanjie, LIU Shengxian, ZHOU Jian, SUN Zhimei. Explainable Machine Learning in the Research of Materials Science[J]. 金属学报, 2024, 60(10): 1345-1361.
[7] LI Zhishang, ZHAO Long, ZONG Hongxiang, DING Xiangdong. Machine-Learning Force Fields for Metallic Materials: Phase Transformations and Deformations[J]. 金属学报, 2024, 60(10): 1388-1404.
[8] ZHAO Jinbin, WANG Jiantao, HE Dongchang, LI Junlin, SUN Yan, CHEN Xing-Qiu, LIU Peitao. Machine Learning Model for Predicting the Critical Transition Temperature of Hydride Superconductors[J]. 金属学报, 2024, 60(10): 1418-1428.
[9] MU Yahang, ZHANG Xue, CHEN Ziming, SUN Xiaofeng, LIANG Jingjing, LI Jinguo, ZHOU Yizhou. Modeling of Crack Susceptibility of Ni-Based Superalloy for Additive Manufacturing via Thermodynamic Calculation and Machine Learning[J]. 金属学报, 2023, 59(8): 1075-1086.
[10] JI Xiumei, HOU Meiling, WANG Long, LIU Jie, GAO Kewei. Modeling and Application of Deformation Resistance Model for Medium and Heavy Plate Based on Machine Learning[J]. 金属学报, 2023, 59(3): 435-446.
[11] YANG Lei, ZHAO Fan, JIANG Lei, XIE Jianxin. Development of Composition and Heat Treatment Process of 2000 MPa Grade Spring Steels Assisted by Machine Learning[J]. 金属学报, 2023, 59(11): 1499-1512.
[12] PENG Liming, DENG Qingchen, WU Yujuan, FU Penghuai, LIU Ziyi, WU Qianye, CHEN Kai, DING Wenjiang. Additive Manufacturing of Magnesium Alloys by Selective Laser Melting Technology: A Review[J]. 金属学报, 2023, 59(1): 31-54.
[13] GAO Jianbao, LI Zhicheng, LIU Jia, ZHANG Jinliang, SONG Bo, ZHANG Lijun. Current Situation and Prospect of Computationally Assisted Design in High-Performance Additive Manufactured Aluminum Alloys: A Review[J]. 金属学报, 2023, 59(1): 87-105.
[14] HE Xingqun, FU Huadong, ZHANG Hongtao, FANG Jiheng, XIE Ming, XIE Jianxin. Machine Learning Aided Rapid Discovery of High Perfor-mance Silver Alloy Electrical Contact Materials[J]. 金属学报, 2022, 58(6): 816-826.
[15] ZHAO Wanchen, ZHENG Chen, XIAO Bin, LIU Xing, LIU Lu, YU Tongxin, LIU Yanjie, DONG Ziqiang, LIU Yi, ZHOU Ce, WU Hongsheng, LU Baokun. Composition Refinement of 6061 Aluminum Alloy Using Active Machine Learning Model Based on Bayesian Optimization Sampling[J]. 金属学报, 2021, 57(6): 797-810.
No Suggested Reading articles found!