# Influence of Laser-Based Powder Bed Fusion of Metals Process Parameters on the Formation of Defects in Al-Zn-Mg-Cu Alloy Using Path Analysis

^{1}

^{2}

^{3}

^{4}

^{*}

## Abstract

**:**

## 1. Introduction

_{2}phases to improve the strength of the allow [32]; on the other hand, a higher Zn content can cause a wider solidification zone, leading to higher hot cracking sensitivity and increasing the difficulty of forming [33]. Therefore, in this paper, to address the problem of the low forming quality of 7050, on the basis of an analysis of the formation mechanism of defects through a combination of numerical simulation and experiments, based on path analysis, we propose a method to quantify the relationship between the influence of process parameters, numerical simulation, and defects, which can help to improve the forming quality of 7050 aluminium alloy and optimise the process parameters.

## 2. Experiments and Numerical Simulations

#### 2.1. Powder Feedstock

#### 2.2. Sample Preparation

^{3}were fabricated. The energy density E is calculated using Equation (2) [35]:

#### 2.3. Microstructural Characterisation

#### 2.4. Numerical Simulation Process

#### 2.4.1. Finite Element Modelling

^{3}and its mesh size is 0.05 × 0.05 × 0.05 mm

^{3}. The size of the powder layer is 1 × 0.35 × 0.02 mm

^{3}and its mesh size is 0.01 × 0.01 × 0.01 mm

^{3}. The substrate under the powder layer was encrypted with a mesh size of 0.02 × 0.02 × 0.02 mm

^{3}. The 3D simulation model was meshed into 31570 hexahedral cells.

#### 2.4.2. Boundary and Initial Conditions

_{x}, k

_{y}and k

_{z}are the thermal conductivity in the x, y and z directions, respectively; T and t are the temperature and time, respectively; and Q is the amount of heat generated, which is the amount of heat per unit volume obtained by laser radiation.

_{t=0}= T

_{0}

_{0}is the initial temperature, which is 25 °C.

_{c}= h

_{c}(T

_{0}− T

_{1})

_{r}= ωφ(T

_{0}

^{4}− T

_{1}

^{4})

_{c}and q

_{r}denote the convective and radiative heat fluxes; ω is the radiation coefficient; φ is the Stefan–Boltzmann constant (5.67 × 10

^{−8}W/(m

^{2}·K

^{4})); h

_{c}is the convection coefficient; and T

_{1}is the material temperature.

#### 2.4.3. Heat Source Modelling

^{2}·s); r is the radius of the laser spot in m; R is the distance from any point to the centre of the heat source in m; and k is the laser absorption rate.

#### 2.4.4. Material Parameters

#### 2.5. Path Analysis

## 3. Results and Discussion

#### 3.1. Experimental Results

_{2}O = Al

_{2}O

_{3}+ 3H

_{2}, and under the high cooling rate of PBF-LB/M, the hydrogen generated fails to spill out of the molten pool during the solidification stage of the molten pool, which in turn forms these types of rounded pores in the solidified samples [45].

^{3}and 100.67 J/mm

^{3}). According to Figure 10(a1,b1), it can be seen that most of the grains grow along the build direction during PBF-LB/M, and coarse columnar grains grow around the cracks. From Figure 10(a2,b2), it can be seen that the average grain size at an energy density of 100.67 J/mm

^{3}is 24.29 μm, and the maximum grain size is 75.9 μm, while the average grain size at an energy density of 47.7 J/mm

^{3}is 18.31 μm, and the maximum grain size is 73.80 μm. This indicates that with an increase in energy density, the grain size is also increased, as is the size of the columnar grains growing in the vertical direction, and the trend of the vertical growth of columnar grains is more and more obvious.

#### 3.2. Numerical Simulation Results

#### 3.3. Path Analysis Results

^{2}), ANOVA test. the R

^{2}values ranged from 0.499 to 0.998, which indicated that the independent variables of the obtained regression models could explain the variations of the dependent variables well. In addition, according to the ANOVA results, the p-values of all predictive equations were <0.001, indicating that the regression equations were significant and these equations were statistically significant (Table 5).

^{7}–3.711 × 10

^{7}), and due to the characteristics of the extremely fast cooling rate under the PBF-LB/M process, this makes the change in the energy gained under different scanning speeds not as large as the change in the laser power that directly changes the laser power, which therefore results in the laser power having a greater effect on the porosity compared to the scanning speed. Similarly, due to the extremely fast cooling rate characteristic of PBF-LB/M, it is difficult to achieve rapid temperature conduction in very short time changes, resulting in a greater degree of influence of power on the temperature gradient than scanning speed. Therefore, the mitigation of defects by optimising laser power has a higher priority than controlling scanning speed.

## 4. Conclusions

^{7}°C/s) during PBF-LB/M, the liquid metal is not able to adequately fill the elongated voids formed by the longer crystalline channels. Together with the thermal stress caused by the temperature gradient, cracks are eventually formed by expansion during the solidification stage.

## Author Contributions

## Funding

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

- Saadi, M.; Maguire, A.; Pottackal, N.T.; Thakur, M.S.H.; Ikram, M.M.; Hart, A.J.; Ajayan, P.M.; Rahman, M.M. Direct Ink Writing: A 3D Printing Technology for Diverse Materials. Adv. Mater.
**2022**, 34, 2108855. [Google Scholar] [CrossRef] [PubMed] - Peng, J.; Li, J.; Liu, B.; Wang, J.; Chen, H.T.; Feng, H.; Zeng, X.; Duan, H.; Cao, Y.; He, J.; et al. Formation process and mechanical properties in selective laser melted multi-principal-element alloys. J. Mater. Sci. Technol.
**2023**, 133, 12–22. [Google Scholar] [CrossRef] - Shin, W.S.; Son, B.; Song, W.S.; Sohn, H.; Jang, H.; Kim, Y.J.; Park, C. Heat treatment effect on the microstructure, mechanical properties, and wear behaviors of stainless steel 316L prepared via selective laser melting. Mater. Sci. Eng. A Struct. Mater. Prop. Microstruct. Process.
**2021**, 806, 140805. [Google Scholar] [CrossRef] - Chen, F.; Wang, Q.; Zhang, C.; Huang, Z.F.; Jia, M.Y.; Shen, Q. Microstructures and mechanical behaviors of additive manufactured Inconel 625 alloys via selective laser melting and laser engineered net shaping. J. Alloys Compd.
**2022**, 917, 165572. [Google Scholar] [CrossRef] - Moghadas, S.M.J.; Yeganeh, M.; Zaree, S.R.A.; Eskandari, M. Influence of low temperature heat treatment on microstructure, corrosion resistance and biological performance of 316L stainless steel manufactured by selective laser melting. CIRP J. Manuf. Sci. Technol.
**2023**, 40, 68–74. [Google Scholar] [CrossRef] - Shi, J.L.; Hu, Q.; Zhao, X.M.; Liu, J.H.; Zhou, J.C.; Xu, W.C.; Chen, Y. Densification, Microstructure and Anisotropic Corrosion Behavior of Al-Mg-Mn-Sc-Er-Zr Alloy Processed by Selective Laser Melting. Coatings
**2023**, 13, 337. [Google Scholar] [CrossRef] - Yang, H.R.; Sha, J.W.; Zhao, D.D.; He, F.; Ma, Z.Q.; He, C.N.; Shi, C.; Zhao, N. Defects control of aluminum alloys and their composites fabricated via laser powder bed fusion: A review. J. Mater. Process. Technol.
**2023**, 319, 118064. [Google Scholar] [CrossRef] - Zhang, S.H.; Zhang, S.M.; Li, F.D.; Li, Z.H.; Wang, Y.; Liu, B. Selective Laser Melting of Al-Cu-Mn-Mg Alloys: Processing and Mechanical Properties. Metals
**2023**, 13, 1520. [Google Scholar] [CrossRef] - Lai, Y.; Deng, Y.; Zhu, X.W.; Guo, Y.F.; Xu, G.F.; Huang, J.W.; Yin, Z.M. Tensile property and microstructure of Al-4.77Mn-1.37Mg-0.67Sc-0.25Zr alloy under different selective laser melting processing parameters. Trans. Nonferrous Met. Soc. China
**2023**, 33, 357–370. [Google Scholar] [CrossRef] - Zhu, Z.G.; Hu, Z.H.; Li Seet, H.; Liu, T.T.; Liao, W.H.; Ramamurty, U.; Nai, S.M.L. Recent progress on the additive manufacturing of aluminum alloys and aluminum matrix composites: Microstructure, properties, and applications. Int. J. Mach. Tools Manuf.
**2023**, 190, 104047. [Google Scholar] [CrossRef] - Tan, Q.Y.; Liu, Y.G.; Fan, Z.Q.; Zhang, J.Q.; Yin, Y.; Zhang, M.X. Effect of processing parameters on the densification of an additively manufactured 2024 Al alloy. J. Mater. Sci. Technol.
**2020**, 58, 34–45. [Google Scholar] [CrossRef] - Pekok, M.A.; Setchi, R.; Ryan, M.; Han, Q.Q.; Gu, D.D. Effect of process parameters on the microstructure and mechanical properties of AA2024 fabricated using selective laser melting. Int. J. Adv. Manuf. Technol.
**2021**, 112, 175–192. [Google Scholar] [CrossRef] - Nie, X.J.; Zhang, H.; Zhu, H.H.; Hu, Z.H.; Ke, L.D.; Zeng, X.Y. Analysis of processing parameters and characteristics of selective laser melted high strength Al-Cu-Mg alloys: From single tracks to cubic samples. J. Mater. Process. Technol.
**2018**, 256, 69–77. [Google Scholar] [CrossRef] - Li, L.; Gou, Y.Q.; Zhang, W.; Meng, X.K.; Zhang, H.M.; Li, P.F.; Huang, S.; Zhou, J. Effect of hatch spacing on the characteristics of LPBF 2195 Al-Li alloy. J. Alloys Compd.
**2024**, 972, 172804. [Google Scholar] [CrossRef] - Li, N.; Wang, T.; Zhang, L.; Zhang, L.X. Crack initiation mechanism of laser powder bed fusion additive manufactured Al-Zn-Mg-Cu alloy. Mater. Charact.
**2023**, 195, 112415. [Google Scholar] [CrossRef] - Oko, O.E.; Mbakaan, C.; Barki, E. Experimental investigation of the effect of processing parameters on densification, microstructure and hardness of selective laser melted 7075 aluminium alloy. Mater. Res. Express
**2020**, 7, 036512. [Google Scholar] - Kaufmann, N.; Imran, M.; Wischeropp, T.M.; Emmelmann, C.; Siddique, S.; Walther, F. Influence of process parameters on the quality of aluminium alloy EN AW 7075 using selective laser melting (SLM). Phys. Procedia
**2016**, 83, 918–926. [Google Scholar] [CrossRef] - Tan, Q.Y.; Fan, Z.Q.; Tang, X.Q.; Yin, Y.; Li, G.; Huang, D.N.; Zhang, J.; Liu, Y.; Wang, F.; Wu, T.; et al. A novel strategy to additively manufacture 7075 aluminium alloy with selective laser melting. Mater. Sci. Eng. A Struct. Mater. Prop. Microstruct. Process.
**2021**, 821, 141638. [Google Scholar] [CrossRef] - DebRoy, T.; Wei, H.L.; Zuback, J.S.; Mukherjee, T.; Elmer, J.W.; Milewski, J.O.; Beese, A.M.; Wilson-Heid, A.; De, A.; Zhang, W. Additive manufacturing of metallic components—Process, structure and properties. Prog. Mater. Sci.
**2018**, 92, 112–224. [Google Scholar] [CrossRef] - Li, D.M.; Zhang, X.; Qin, R.X.; Xu, J.X.; Yue, D.Y.; Chen, B.Z. Influence of processing parameters on AlSi10Mg lattice structure during selective laser melting: Manufacturing defects, thermal behavior and compression properties. Opt. Laser Technol.
**2023**, 161, 109182. [Google Scholar] [CrossRef] - Wang, W.L.; Wang, D.; He, L.; Liu, W.Q.; Yang, X. Thermal behavior and densification during selective laser melting of Mg-Y-Sm-Zn-Zr alloy: Simulation and experiments. Mater. Res. Express
**2020**, 7, 116519. [Google Scholar] [CrossRef] - Li, Y.L.; Gu, D.D. Parametric analysis of thermal behavior during selective laser melting additive manufacturing of aluminum alloy powder. Mater. Des.
**2014**, 63, 856–867. [Google Scholar] [CrossRef] - Wei, P.; Wei, Z.Y.; Chen, Z.; Li, J.F.; Zhang, S.Z.; Du, J. Numerical simulation and parametric analysis of selective laser melting process of AlSi10Mg powder. Appl. Phys. A Mater. Sci. Process.
**2017**, 123, 540. [Google Scholar] - Khan, H.M.; Dirikolu, M.H.; Koç, E. Parameters optimization for horizontally built circular profiles: Numerical and experimental investigation. Optik
**2018**, 174, 521–529. [Google Scholar] [CrossRef] - Zhou, J.T.; Han, X.; Li, H.; Liu, S.; Yi, J.C. Investigation of layer-by-layer laser remelting to improve surface quality, microstructure, and mechanical properties of laser powder bed fused AlSi10Mg alloy. Mater. Des.
**2021**, 210, 110092. [Google Scholar] [CrossRef] - Yang, J.; Li, X.; Mao, L.; Dong, J.; Fan, R.; Zhang, L. Path Analysis of Influencing Factors of Depression in Middle-Aged and Elderly Patients with Diabetes. Patient Prefer. Adherence
**2023**, 17, 273–280. [Google Scholar] [CrossRef] [PubMed] - Li, Z.X.; Liu, J.L.; You, J.; Li, X.; Liang, Z.S.; Du, J.L. Proanthocyanidin Structure-Activity Relationship Analysis by Path Analysis Model. Int. J. Mol. Sci.
**2023**, 24, 6379. [Google Scholar] [CrossRef] - Mandana, A.; Mohsen, S.; Ale Agha, A.B.; Danial, K. Interaction of iron and zinc fortification and late-season water deficit on yield and fatty acid composition of Dragon’s Head (Lallemantia iberica L.). Plant Physiol. Biochem.
**2023**, 201, 107882. [Google Scholar] - Parsamanesh, S.; Sadeghi, H. Modeling the interactions between inter-correlated variables of plant and soil micro-ecology responses under simultaneous cadmium stress and drought. J. Clean. Prod.
**2023**, 418, 138163. [Google Scholar] [CrossRef] - Li, Q.; Xue, Q.C.; Hu, Q.S.; Song, T.; Wang, Y.H.; Li, S.Y. Cold Expansion Strengthening of 7050 Aluminum Alloy Hole: Structure, Residual Stress, and Fatigue Life. Int. J. Aerosp. Eng.
**2022**, 2022, 4057898. [Google Scholar] [CrossRef] - Meng, Q.J.; Frankel, G.S. Effect of Cu content on corrosion behavior of 7xxx series aluminum alloys. J. Electrochem. Soc.
**2004**, 151, B271–B283. [Google Scholar] [CrossRef] - Liu, Q.; Liu, Z.; Zhao, J.; Guo, W.; Wang, M.; Liu, Z. Effect of Zn content and retrogression and re-aging treatment on properties of 7075 aluminum alloy. Heat Treat. Met.
**2016**, 41, 11–15. [Google Scholar] - Zhang, X.; Mao, W.; Zhu, W. Influence of Zn, Mg and Cu Contents on Hot Cracking Behavior and Microstructure of 7075 Aluminum Alloys. Spec. Cast. Nonferrous Alloys
**2014**, 34, 1336–1339. [Google Scholar] - Sun, Y.Y.; Gulizia, S.; Oh, C.H.; Doblin, C.; Yang, Y.F.; Qian, M. Manipulation and Characterization of a Novel Titanium Powder Precursor for Additive Manufacturing Applications. JOM
**2015**, 67, 564–572. [Google Scholar] [CrossRef] - Boschetto, A.; Bottini, L.; Pilone, D. Effect of laser remelting on surface roughness and microstructure of AlSi10Mg selective laser melting manufactured parts. Int. J. Adv. Manuf. Technol.
**2021**, 113, 2739–2759. [Google Scholar] [CrossRef] - Ma, R.-l.; Peng, C.-q.; Cai, Z.-y.; Wang, R.-c.; Zhou, Z.-h.; Li, X.-g.; Cao, X. Finite element analysis of temperature and stress fields during selective laser melting process of Al-Mg-Sc-Zr alloy. Trans. Nonferrous Met. Soc. China
**2021**, 31, 2922–2938. [Google Scholar] [CrossRef] - Li, Z.H.; Yang, S.; Liu, B.; Liu, W.P.; Kuai, Z.Z.; Nie, Y.F. Simulation of temperature field and stress field of selective laser melting of multi-layer metal powder. Opt. Laser Technol.
**2021**, 140, 106782. [Google Scholar] [CrossRef] - Nie, S.J.; Li, L.; Wang, Q.; Zhao, R.X.; Lin, X.; Liu, F.R. Effects of Thermal Stress on the Formation and Cracking Behavior of Nickel-Based Superalloys by Selective Laser Melting Based on a Coupled Thermo-Mechanical Model. Materials
**2022**, 15, 8968. [Google Scholar] [CrossRef] - Yin, J.; Zhu, H.; Ke, L.; Lei, W.; Dai, C.; Zuo, D. Simulation of temperature distribution in single metallic powder layer for laser micro-sintering. Comput. Mater. Sci.
**2012**, 53, 333–339. [Google Scholar] [CrossRef] - Liu, H.W.; Zheng, J.X.; Guo, Y.L.; Zhu, L.X. Residual stresses in high-speed two-dimensional ultrasonic rolling 7050 aluminum alloy with thermal-mechanical coupling. Int. J. Mech. Sci.
**2020**, 186, 105824. [Google Scholar] [CrossRef] - Romano, J.; Ladani, L.; Razmi, J.; Sadowski, M. Temperature distribution and melt geometry in laser and electron-beam melting processes—A comparison among common materials. Addit. Manuf.
**2015**, 8, 1–11. [Google Scholar] [CrossRef] - Yang, X.; Li, Y.Z.; Li, B. Formation mechanisms of lack of fusion and keyhole-induced pore defects in laser powder bed fusion process: A numerical study. Int. J. Therm. Sci.
**2023**, 188, 108221. [Google Scholar] [CrossRef] - Bayat, M.; Thanki, A.; Mohanty, S.; Witvrouw, A.; Yang, S.F.; Thorborg, J.; Tiedje, N.S.; Hattel, J.H. Keyhole-induced porosities in Laser-based Powder Bed Fusion (L-PBF) of Ti6Al4V: High-fidelity modelling and experimental validation. Addit. Manuf.
**2019**, 30, 100835. [Google Scholar] [CrossRef] - Liu, B.Q.; Fang, G.; Lei, L.P.; Yan, X.C. Predicting the porosity defects in selective laser melting (SLM) by molten pool geometry. Int. J. Mech. Sci.
**2022**, 228, 107478. [Google Scholar] [CrossRef] - Weingarten, C.; Buchbinder, D.; Pirch, N.; Meiners, W.; Wissenbach, K.; Poprawe, R. Formation and reduction of hydrogen porosity during selective laser melting of AlSi10Mg. J. Mater. Process. Technol.
**2015**, 221, 112–120. [Google Scholar] [CrossRef] - Yao, S.; Wang, J.J.; Li, M.; Chen, Z.; Lu, B.H.; Shen, S.; Li, Y. LPBF-Formed 2024Al Alloys: Process, Microstructure, Properties, and Thermal Cracking Behavior. Metals
**2023**, 13, 268. [Google Scholar] [CrossRef] - Wang, T.; Wang, Y.; Yang, X.; Chen, B.; Zhu, H. Cracks and process control in laser powder bed fusion of Al-Zn-Mg alloy. J. Manuf. Process.
**2022**, 81, 571–579. [Google Scholar] [CrossRef] - Huang, X.Q.; Chen, H.T.; Liu, B.; Mohammadzadeh, R.; Li, J.; Fang, Q.H. Thermal behavior and microstructural evolution of additively manufactured Ni-based superalloys via multi-scale simulation. Optik
**2021**, 243, 167456. [Google Scholar] [CrossRef] - Zhang, C.; Liao, Q.H.; Zhang, X.X.; Ma, F.; Wu, M.H.; Xu, Q. Characterization of porosity in lack of fusion pores in selective laser melting using the wavefunction. Mater. Res. Express
**2023**, 10, 016501. [Google Scholar] [CrossRef]

**Figure 1.**(

**a**) SEM morphology of 7050 aluminium alloy powder at low magnification. (

**b**) SEM morphology of 7050 aluminium alloy powder at high magnification.

**Figure 3.**Schematic diagram of the forming principle of the experimental metal powder PBF-LB/M forming machine.

**Figure 6.**(

**a1**) Scatter plot of energy density vs. defect rate; (

**a2**) 3D histogram of laser power vs. scanning speed and defect rate. (

**b1**) Scatter plot of energy density vs. porosity; (

**b2**) 3D histogram of laser power vs. scanning speed and porosity. (

**c1**) Scatter plot of energy density versus crack rate; (

**c2**) 3D histogram of laser power versus scanning speed and crack rate.

**Figure 7.**(

**a1**) SEM image of irregular large pores; (

**a2**) schematic diagram of the formation of irregular large pores during the printing process. (

**b1**) SEM image of irregular small pores; (

**b2**) schematic diagram of the formation of irregular small pores during the printing process. (

**c1**) SEM image of a rounded small pore; (

**c2**) schematic diagram of the formation of a rounded small pore during the printing process.

**Figure 8.**(

**a1**) Scatter plot of energy density versus crack maximum length; (

**a2**) 3D histogram of laser power versus scanning speed and crack maximum length. (

**b1**) Scatter plot of energy density versus crack minimum length; (

**b2**) 3D histogram of laser power versus scanning speed and crack minimum length. (

**c1**) Scatter plot of energy density versus average crack length; (

**c2**) 3D histogram of laser power versus scanning speed and average crack length.

**Figure 10.**IPF map (

**a1**) and grain size distribution (

**a2**) for the sample with E = 47.7 J/mm

^{3}. IPF map (

**b1**) and grain size distribution (

**b2**) for the sample with E = 100.7 J/mm

^{3}.

**Figure 12.**Model validation: (

**a**) temperature field simulation results; (

**b**) experimental OM image of the melt pool.

**Figure 13.**(

**a**) Temperature distribution on the upper surface of the melt pool; (

**b**) temperature distribution at the centre of the spot at different times.

**Figure 17.**(

**a**) Solidification curves of 7050 alloy and AlSi10Mg; (

**b**) liquid reflux channel of 7050 aluminium alloy; (

**c**) liquid reflux channel of AlSi10Mg.

**Figure 18.**Path diagram showing the effect of process parameters on temperature field results and of temperature field results on defects. Numerical values indicate path coefficients between variables. Solid arrows indicate impact. ** and * are significant at the 0.001 and 0.01 levels of probability, respectively.

Alloy | Al | Zn | Mg | Cu | Zr | Si | Fe | Ti |
---|---|---|---|---|---|---|---|---|

7050 | Bal. | 5.87 | 1.21 | 1.98 | 0.084 | 0.033 | 0.023 | 0.022 |

Form Factor (Sphericity) | 0–0.4 | 0.4–0.5 | 0.5–0.6 | 0.6–0.7 | 0.7–0.8 | 0.8–0.9 | 0.9–1 |
---|---|---|---|---|---|---|---|

Number fraction (%) | 0 | 1 | 2 | 9 | 15 | 24 | 49 |

Process Parameters | Numerical Value | Unit |
---|---|---|

Laser power (P) | 210, 260, 310, 360, 410 | W |

Scan speed (V) | 800, 1100, 1400, 1700, 2000 | mm/s |

Hatch space (h) | 110 | μm |

Layer thickness (L) | 20 | μm |

Properties | Values |
---|---|

Density (kg/m^{3}) | 2830 |

Specific heat J/(kg·K) | 860 |

Conductivity W/(m·K) | 157 |

Convective heat transfer coefficient W/(m^{2}·°C) | 80 |

Laser absorption rate | 0.15 |

**Table 5.**Predictive model equations and R

^{2}and p-values for temperature, cooling rate, temperature gradient, porosity and cracking.

Prediction Model Equation | R^{2} | p-Value |
---|---|---|

Temperature = 246.433 + 6.61 P − 0.215 V | 0.998 | <0.001 |

Cooling rate = −10,576,413.1 + 47,602.848 P + 13,586.573 V | 0.960 | <0.001 |

Temperature gradient = 5.214 + 0.059 P − 0.001 V | 0.987 | <0.001 |

Porosity = 13.672 − 0.007 Temperature + 2.403 × 10^{−7} Cooling rate | 0.679 | <0.001 |

Crack = −0.702 + 0.117 Temperature gradient | 0.499 | <0.001 |

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |

© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Huang, B.; Tang, H.; Huang, J.; Jia, Y.; Liao, L.; Pang, S.; Zheng, X.; Chen, Z.
Influence of Laser-Based Powder Bed Fusion of Metals Process Parameters on the Formation of Defects in Al-Zn-Mg-Cu Alloy Using Path Analysis. *Micromachines* **2024**, *15*, 1121.
https://doi.org/10.3390/mi15091121

**AMA Style**

Huang B, Tang H, Huang J, Jia Y, Liao L, Pang S, Zheng X, Chen Z.
Influence of Laser-Based Powder Bed Fusion of Metals Process Parameters on the Formation of Defects in Al-Zn-Mg-Cu Alloy Using Path Analysis. *Micromachines*. 2024; 15(9):1121.
https://doi.org/10.3390/mi15091121

**Chicago/Turabian Style**

Huang, Biao, Hongqun Tang, Jincheng Huang, Yuanxiang Jia, Liuhui Liao, Shuhuan Pang, Xu Zheng, and Zhendong Chen.
2024. "Influence of Laser-Based Powder Bed Fusion of Metals Process Parameters on the Formation of Defects in Al-Zn-Mg-Cu Alloy Using Path Analysis" *Micromachines* 15, no. 9: 1121.
https://doi.org/10.3390/mi15091121