Metals and Materials International最新文献_第9页

Microstructure, Mechanical Properties and Strengthening Mechanism of Mg-8Gd-2 Nd-xEr-0.5Zr Alloy Mg-8Gd-2 Nd-xEr-0.5Zr合金的组织、力学性能及强化机理

IF 4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Metals and Materials International

Pub Date : 2025-05-23 DOI: 10.1007/s12540-025-01964-1

Yidan Ma, Quanan Li, Xiaoya Chen, Zhuolin Li, Nana Zhang

The microstructure and mechanical properties of Mg-8Gd-2Nd-xEr-0.5Zr alloy were systematically studied. The effect of Er addition on the microstructure of as-cast alloy was discussed by calculating the mismatch degree, and the strengthening mechanism of aged alloy was expounded from the aspects of fine grain strengthening and precipitation strengthening. The mismatches between (100), (110), and (111) planes of Mg₅Gd and (0001) plane of α-Mg were 0.95, 2.33, and 1.65%, respectively. Calculations demonstrate that Mg₅Gd can serve as an effective core for α-Mg nucleation. The addition of the Er element can replace Gd atom to form Mg₅ (Gd, Er) phase, which increases the effective heterogeneous nucleation core, thus refining the grains. In addition, the number of β′ precipitates increases after aging treatment, which better hinders the dislocation movement and improves the performance. The ultimate tensile strength (UTS) of Mg-8Gd-2Nd-3Er-0.5Zr alloy can reach 313, 319, 307 and 287 MPa at 25, 200, 250 and 300 °C, respectively. The fracture morphology has a large number of dissociation surfaces and tearing edges, showing brittle fracture.

Graphical abstract

系统地研究了Mg-8Gd-2Nd-xEr-0.5Zr合金的显微组织和力学性能。通过计算错配度，讨论了添加Er对铸态合金组织的影响，并从细晶强化和析出强化两方面阐述了时效合金的强化机理。Mg5Gd的（100）、（110）、（111）面与α-Mg的（0001）面不匹配度分别为0.95、2.33、1.65%。计算表明，Mg5Gd可以作为α-Mg成核的有效核。Er元素的加入可以取代Gd原子形成Mg5 （Gd, Er）相，增加了有效的非均相形核芯，使晶粒细化。此外，时效处理后β′析出相数量增加，更好地阻碍了位错的运动，提高了性能。Mg-8Gd-2Nd-3Er-0.5Zr合金在25、200、250和300℃时的极限抗拉强度分别达到313、319、307和287 MPa。断口形貌具有大量的解离面和撕裂边，呈脆性断裂。图形抽象

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引用次数: 0

Laser Powder Bed Fusion Inconel 718 Lattice Structures: From Process Simulation to Microstructural and Mechanical Characterizations 激光粉末床熔合Inconel 718晶格结构：从过程模拟到微观组织和力学表征

IF 4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Metals and Materials International

Pub Date : 2025-05-23 DOI: 10.1007/s12540-025-01963-2

Alberto Santoni, Marcello Cabibbo, Marco Mandolini, Marco Palladino, Stefano Spigarelli, Eleonora Santecchia

Lattice are porous structures obtained by a controlled repetition in the space of a designed unit cell, resulting in reduced weight and unique functional characteristics such as high specific strength and stiffness, mechanical energy absorption, and heat transfer control. This work aims to tailor geometrical variables and process parameters to fabricate L-PBF Inconel 718 beam-based lattice structures, focusing on their novel use as support structures during the printing process of metallic components, enhancing structural integrity and heat dissipation. 3D models of different porous structures (cell type: FCC-Z) were developed varying geometrical parameters. Finite Element Method simulations were conducted by Ansys, validating its ability to meet quality standards for directional deformations and residual stresses. The simulation’s correlation with the coordinate measuring machine (CMM) analysis confirmed the accuracy of the model. Scanning electron microscopy (SEM) characterization was employed to analyze the deformation and failure characteristics of the lattices, excluding those with geometric parameters unsuitable for optimal support performance. Microstructural analysis revealed partial recrystallization in the heat-treated samples. The remaining dendritic structures indicate incomplete homogenization, particularly near the lattice. Precipitated strengthening phases such as γ′ and δ were identified, alongside minor quantities of η phases and MC carbides, which could influence ductility and strength. Vickers microhardness tests showed higher hardness in the heat-treated samples, particularly at nodes and struts, with a more uniform hardness distribution in heat-treated samples due to the precipitation of strengthening phases. This highlights the role of heat treatment in enhancing the material’s mechanical properties.

Graphical Abstract

晶格是通过在设计的单元格空间中控制重复而获得的多孔结构，从而减少了重量和独特的功能特征，如高比强度和刚度，机械能吸收和传热控制。这项工作旨在定制几何变量和工艺参数来制造L-PBF Inconel 718梁基晶格结构，重点关注它们在金属部件打印过程中作为支撑结构的新用途，提高结构完整性和散热性。建立了不同几何参数的不同多孔结构（细胞类型：FCC-Z）的三维模型。利用Ansys进行了有限元模拟，验证了其能够满足定向变形和残余应力的质量标准。仿真与三坐标测量机（CMM）分析的对比验证了模型的准确性。采用扫描电子显微镜（SEM）表征分析了网格的变形和破坏特征，排除了几何参数不适合最佳支护性能的网格。显微组织分析表明，热处理后的样品存在部分再结晶现象。剩余的枝晶结构表明不完全均匀化，特别是在晶格附近。析出的强化相如γ′和δ，以及少量的η相和MC碳化物会影响塑性和强度。显微硬度测试表明，热处理后的试样硬度较高，特别是在节点和支杆处，由于强化相的析出，热处理后的试样硬度分布更加均匀。这突出了热处理在提高材料机械性能方面的作用。图形抽象

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引用次数: 0

Three Constitutive Equations and a Three-Dimensional Hot Processing Map of AA3003 Alloy at Elevated Temperatures for Process Design and Performance Prediction 用于工艺设计和性能预测的AA3003合金高温三维热加工图及三个本构方程

IF 4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Metals and Materials International

Pub Date : 2025-05-20 DOI: 10.1007/s12540-025-01955-2

Xiaohui Fang, Fuguo Li, Miaomiao Wan, Qian Zhao, Xinru Jia

As the demand for high-performance lightweight materials in electric vehicle manufacturing increased, AA3003 alloy, due to its excellent hot deformation properties, became a key research subject for improving product quality and optimizing process performance, but few current material models can be used to simulate the synergistic evolution of deformation and performance. The hot deformation behavior of a homogenized annealed extruded AA3003 alloy was investigated through isothermal hot compression tests conducted at temperatures between 250 and 550 ℃ and at strain rates ranging from 1 to 10 s⁻¹. The experimental results revealed that the true stress-true strain behavior of the AA3003 alloy exhibited the characteristics of dynamic recovery (DRV) and dynamic recrystallization (DRX). Subsequently, three constitutive models with different mechanisms were established: a strain-compensated Arrhenius model for deformation simulation, an internal state variable (ISV) model considering multiple internal variables for performance prediction, and a particle swarm optimization-artificial neural network (PSO-ANN) model for rapid design. The findings indicated that the PSO-ANN model exhibited superior prediction accuracy and more robust generalization ability in comparison to the modified Arrhenius and ISV models, with evaluation parameters (R),(AARE), and (RMSE) being 0.9998, 1.5%, and 1.48 MPa. A three-dimensional hot processing map was developed based on the PSO-ANN model, and the microstructural analysis revealed the presence of large undeformed grains and fine DRX grains in regions with low power dissipation coefficients. The optimal processing window for the deformation process was identified through the application of the developed 3D hot processing map (350–450 ℃, 1–10 s⁻¹). The ISV model was integrated into the ABAQUS software for the simulation of material deformation and the associated properties, and the resulting predictions of microstructure and performance were validated.

Graphic Abstract

随着电动汽车制造对高性能轻量化材料需求的增加，AA3003合金因其优异的热变形性能成为提高产品质量和优化工艺性能的重点研究对象，但目前很少有材料模型能够模拟变形与性能的协同演化。通过等温热压缩试验，研究了均匀退火挤压AA3003合金在250 ～ 550℃、1 ～ 10 s毒化速率下的热变形行为。实验结果表明，AA3003合金的真应力-真应变行为表现为动态恢复（DRV）和动态再结晶（DRX）特征。在此基础上，建立了形变模拟的应变补偿Arrhenius模型、性能预测的考虑多内变量的内状态变量（ISV）模型和快速设计的粒子群优化-人工神经网络（PSO-ANN）模型。结果表明，与改进的Arrhenius和ISV模型相比，PSO-ANN模型的预测精度更高，泛化能力更强，评价参数(R)、(AARE)和(RMSE)分别为0.9998、1.5%, and 1.48 MPa. A three-dimensional hot processing map was developed based on the PSO-ANN model, and the microstructural analysis revealed the presence of large undeformed grains and fine DRX grains in regions with low power dissipation coefficients. The optimal processing window for the deformation process was identified through the application of the developed 3D hot processing map (350–450 ℃, 1–10 s⁻1). The ISV model was integrated into the ABAQUS software for the simulation of material deformation and the associated properties, and the resulting predictions of microstructure and performance were validated.Graphic Abstract

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引用次数: 0

Advanced Modeling and Microstructural Insights into the Hot Deformation Behavior of Fe–11Al–5Mn–1Nb–1C Low-Density Steel Fe-11Al-5Mn-1Nb-1C低密度钢热变形行为的高级建模和显微组织研究

IF 4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Metals and Materials International

Pub Date : 2025-05-18 DOI: 10.1007/s12540-025-01950-7

Bashista Kumar Mahanta, Pankaj Rawat, Sumit Bhan, Swagata Roy

The hot deformation behavior of Fe–11Al–5Mn–1Nb–1C low-density steel was investigated using a GLEEBLE 3800R thermomechanical simulator across a temperature range of 900–1200 ℃ and strain rates of 1–0.001 s⁻¹. An Arrhenius-type constitutive model was developed to predict flow stress during deformation, alongside a bilayer evolutionary neural network (EvoNN) model based on an artificial neural network (ANN) approach. The EvoNN model demonstrated higher prediction accuracy than the constitutive model. Microstructural analysis revealed a ferritic matrix with kappa carbide as a secondary phase at 900 and 1000 ℃, while at 1100 and 1200 ℃, a dual-phase structure (ferrite + austenite) with fine kappa carbides at the phase interface was observed. NbC particles were consistently present in all hot compressed samples. Partial dynamic recrystallization (DRX) occurred at 900 and 1000 ℃, whereas more extensive DRX was observed at 1100 and 1200 ℃. Grain coarsening was evident at lower strain rates, increasing as the strain rate decreased. Fine NbC particles and kappa carbides pinned grain boundaries, potentially delaying DRX onset, while coarse NbC particles appeared to enhance particle-stimulated nucleation (PSN), introducing complexity to DRX dynamics and contributing to model discrepancies in the constitutive and EvoNN model.

Graphical Abstract

采用GLEEBLE 3800R热模拟装置，研究了Fe-11Al-5Mn-1Nb-1C低密度钢在900 ~ 1200℃、应变速率1 ~ 0.001 s−1范围内的热变形行为。建立了arrhenius型本构模型和基于人工神经网络（ANN）方法的双层进化神经网络（EvoNN）模型，用于预测变形过程中的流动应力。EvoNN模型的预测精度高于本构模型。显微组织分析表明，在900℃和1000℃时，合金为铁素体基体，次生相为碳化物kappa；在1100℃和1200℃时，合金为铁素体+奥氏体的双相结构，相界面处有细小的kappa碳化物。在所有的热压缩样品中均一致存在NbC颗粒。900℃和1000℃时发生部分动态再结晶（DRX）， 1100℃和1200℃时发生更广泛的动态再结晶。在较低应变速率下晶粒粗化明显，随着应变速率的降低晶粒粗化程度增大。细小的NbC颗粒和碳化物固定了晶界，可能会延迟DRX的发生，而粗的NbC颗粒似乎会增强粒子刺激成核（PSN），给DRX动力学带来复杂性，并导致本构模型和EvoNN模型的差异。图形抽象

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引用次数: 0

Effects of Sc Additions on Annealing Behavior of Heavily Cold-Rolled Al-Cu-Mn Alloys Sc添加对Al-Cu-Mn重冷轧合金退火行为的影响

IF 4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Metals and Materials International

Pub Date : 2025-05-17 DOI: 10.1007/s12540-025-01949-0

Xiaoyu Huang, Tianlin Huang, Yueyue Zhu, Guilin Wu, Yongzhong Zhang, Xiaoxu Huang, Oleg V. Mishin

Effects of minor additions of Sc on the microstructure evolution during long-term heat treatments at 200–300 °C have been studied for heavily rolled Al-Cu-Mn alloys, where Sc content varies in the range 0‒0.2 wt%. It is found that cold rolling to 90% thickness reduction results in deformation structures with boundary spacing of 58–68 nm measured along the normal direction. This cold-rolled sample is characterized by high hardness (145‒147 HV). Precipitation of θ′ particles along deformation-induced boundaries and coarsening of deformation structures via triple junction motion and boundary migration take place during annealing for 100 h at 200 °C or 250 °C. The extent of structural coarsening is greater in the Sc-free alloy than in the Sc-containing alloys, where the presence of Sc enhances precipitation and stability of θ′ particles. The coarsening of deformation structures leads to reduced hardness in each alloy, with greater reductions seen for the Sc-free alloy. Interestingly, an increase in Sc content from 0.1 wt% to 0.2 wt% does not lead to greater improvement in thermal stability of deformation structures. It is shown that the addition of 0.2 wt% Sc stimulates precipitation of Al₃Sc particles during homogenization. As these particles consume Sc, the amount of Sc available for enhanced precipitation and stability of θ′ particles does not increase despite the higher concentration of this element in the chemical composition. Therefore, the number density of θ′ particles in samples heat treated at 200–250 °C also does not increase with increasing Sc content from 0.1 wt% to 0.2 wt%. Annealing at 300 °C for 100 h leads to fully recrystallized microstructures in each alloy. During recrystallization, finer grains develop in the Sc-containing alloys compared with those in the recrystallized Sc-free alloy. The recrystallized Sc-containing alloys are harder (51‒55 HV) than the Sc-free alloy (47 HV).

Graphical Abstract

在200-300°C长期热处理过程中，研究了少量添加Sc对Al-Cu-Mn合金组织演变的影响，其中Sc含量在0-0.2 wt%范围内变化。结果表明，当冷轧厚度减小到90%时，在法向方向产生了边界间距为58 ~ 68 nm的变形组织。这种冷轧样品的特点是硬度高（145-147 HV）。在200℃或250℃退火100 h时，θ′粒子沿变形边界析出，并通过三结运动和边界迁移使变形结构粗化。无Sc合金的组织粗化程度大于含Sc合金，其中Sc的存在增强了θ′颗粒的析出和稳定性。变形组织的粗化导致每种合金的硬度降低，无sc合金的硬度降低幅度更大。有趣的是，Sc含量从0.1 wt%增加到0.2 wt%并没有导致变形结构热稳定性的更大改善。结果表明，在均匀化过程中，添加0.2 wt%的Sc刺激了Al3Sc颗粒的析出。由于这些粒子消耗Sc，尽管化学成分中Sc的浓度较高，但用于增强沉淀和θ′粒子稳定性的Sc量并未增加。因此，在200-250℃热处理的样品中，θ′粒子的数量密度也不随Sc含量从0.1 wt%增加到0.2 wt%而增加。在300°C下退火100小时，导致每种合金的显微组织完全再结晶。在再结晶过程中，含sc合金的晶粒比无sc合金的晶粒细。含sc合金的再结晶硬度（51 ~ 55 HV）高于无sc合金（47 HV）。图形抽象

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引用次数: 0

Dynamic Globularization and Dynamic Phase Transformation Behaviors in a Lamellar Metastable-β Ti Alloy Under Subtransus Processing 亚稳-β钛合金在亚横向加工下的动态球化和动态相变行为

IF 4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Metals and Materials International

Pub Date : 2025-05-16 DOI: 10.1007/s12540-025-01960-5

Gui-Cheng Wu, Y. C. Lin, Shu-Xin Li, Hong-Bin Li, Xiao-Dong Zhan, Guo-Dong Pang, Hui-Jie Zhang, Miao Wan, Ning-Fu Zeng, Ming-Song Chen

Dynamic globularization (DG) and dynamic phase transformation (DPT) are significant concurrent phenomena observed during thermal processing in lamellar Ti alloys. The experimental findings elucidate the occurrence of DG and DPT, as well as their underlying mechanisms, during hot deformation. The proportion of globularized α lamellae increases with higher deformation degrees, lower strain rates, or elevated deformation temperatures. Two distinct clusters associated with the lamellar and globular α phases are observed. The changing trend in Schmid factor, in conjunction with the inverse pole figure (IPF), indicates basal and prismatic glide mechanisms facilitating DG process. The DPT is featured by displacive nucleation and diffusion-controlled growth mechanisms. The transformed substructures in α and β phases provide rapid pathways for solute elemental diffusion, causing their sequential distribution from the β phase to α phase. This redistribution of elements, combined with stress concentration at phase boundaries, triggers the occurrence of DPT. As strain is applied, the accumulation of high-density dislocations progressively forms dislocation walls and low-angle grain boundaries, which subsequently evolve into grooves with the aid of the DPT. Ultimately, the infiltration of new β phases into the α plates results in their disintegration.

Graphical Abstract

动态球化（DG）和动态相变（DPT）是层状钛合金在热加工过程中同时发生的重要现象。实验结果阐明了热变形过程中DG和DPT的发生及其潜在机制。变形程度越高、应变速率越低、变形温度越高，球状α片的比例越高。观察到两种不同的与片层α相和球状α相相关的团簇。Schmid因子的变化趋势与逆极图（IPF）相结合，表明基底和棱柱滑动机制促进了DG过程。DPT具有驱替成核和扩散控制生长机制。α和β相中转变的亚结构为溶质元素的快速扩散提供了通道，导致溶质元素从β相到α相的顺序分布。这种元素的重新分布，加上相界处的应力集中，触发了DPT的发生。随着应变的施加，高密度位错的积累逐渐形成位错壁和低角度晶界，随后在DPT的帮助下演变成凹槽。最终，新的β相渗透到α板中，导致其解体。图形抽象

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引用次数: 0

Simultaneously Reducing Porosity and Strengthening the Additively Manufactured 18Ni300 Steel Through Cyclic Electropulsing Treatment 循环电脉冲处理增材18Ni300钢同时降低孔隙率和强化性能

IF 4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Metals and Materials International

Pub Date : 2025-05-16 DOI: 10.1007/s12540-025-01952-5

Jingyu Wang, Shengwei Zhang, Zhijie Liu, Hao Chen, Dongni Liu

This study investigates the effect of cyclic electropulsing treatment (EPT) on rapid pore healing and the enhancement of mechanical strength in 18Ni300 maraging steel fabricated using laser powder bed fusion (LPBF) technique. During EPT, high-density electric pulses with an electric current density of 103 A/mm² and a short duration of 500 ms are circularly applied to the LPBF 18Ni300 samples. In-situ computed tomography scan and mechanical testing demonstrate that EPT significantly increases the maximum tensile strength of LPBF 18Ni300 from 1200 to 1600 MPa after 10 cycle applications of EPT, while porosity decreases from an initial value of 0.087‰ to 0.023‰. Multi-physics simulation indicates that the width-to-length (WL) ratio of pores dramatically influences healing efficiency by modulating the distribution of electric current flow. Pores with a smaller WL ratio exhibit more pronounced electric current concentration at the pore edge, resulting in an inhomogeneous distribution of electric current density. This inhomogeneity initiates the development of a temperature gradient and causes the formation of significant thermal stress and plastic deformation, which facilitate the closure process for pores with a smaller WL ratio. Microstructural analysis reveal that the enhancement of tensile strength after a single EPT is attributed to increased dislocation density (dislocation-induced strengthening), while the strengthening observed after 10 EPT cycles is primarily governed by the rapid formation of Ni₃ (Ti, Al) precipitates (precipitation hardening). These findings provide valuable insights into the application of EPT for rapid pore healing and mechanical properties enhancement in LPBF-fabricated precipitation hardening metallic materials.

研究了循环电脉冲处理（EPT）对激光粉末床熔合（LPBF）法制备的18Ni300马氏体时效钢孔隙快速愈合和机械强度提高的影响。在EPT期间，对LPBF 18Ni300样品循环施加电流密度为103 A/mm2、持续时间为500 ms的高密度电脉冲。现场ct扫描和力学试验结果表明，经10次EPT循环作用后，LPBF 18Ni300的最大抗拉强度由1200 MPa显著提高至1600 MPa，孔隙率由0.087‰降低至0.023‰。多物理场模拟表明，孔隙的宽长比通过调节电流的分布而显著影响愈合效率。WL比越小的孔隙在孔隙边缘的电流集中越明显，导致电流密度分布不均匀。这种不均匀性引发了温度梯度的发展，导致显著的热应力和塑性变形的形成，有利于较小WL比孔隙的闭合过程。显微组织分析表明，单次EPT后拉伸强度的提高主要是位错密度的增加（位错强化），而10次EPT后的强化主要是由Ni3 （Ti, Al）析出相的快速形成（沉淀硬化）决定的。这些发现为EPT在lpbf制备的沉淀硬化金属材料中快速孔隙愈合和力学性能增强的应用提供了有价值的见解。

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引用次数: 0

Feasibility of Direct Learning in Predicting Complex Flow Behavior of Metastable TiAl Intermetallics: Constitutive Analysis, Modelling and Numerical Implementation 直接学习预测亚稳TiAl金属间化合物复杂流动行为的可行性：本构分析、建模和数值实现

IF 4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Metals and Materials International

Pub Date : 2025-05-14 DOI: 10.1007/s12540-025-01947-2

Huashan Fan, Liang Cheng, Lingyan Sun, Zhihao Bai, Jiangtao Wang, Jinshan Li

The deformation behavior of a TiAl alloy with a (β_o + γ) structure was studied in the temperature range of 1000 ~ 1150 °C and strain rates of 10⁰ ~ 10^–3 s⁻¹, which was characterized by intricate and irregular flow hardening/softening primarily due to the initial metastable microstructure and the onset of phase transition during deformation. As a consequence, the flow behavior was quite difficult to be modelled by the conventional constitutive relations even utilizing the highly flexible strain-compensated hyperbolic-sine law. Therefore, in this study we tried to develop an accurate constitutive model based on the multilayer feed-forward neural networks (FFNN). To this end, the FFNNs with various widths (nodes-per-layer) and depths (number of hidden layers) were constructed and evaluated. A dual-cycle training strategy was proposed to achieve the best performance for each FFNN, whereby an optimal architecture with four hidden layers and four nodes-per-layer was selected to balance the overfitting and underfitting. After systematic verification, it was demonstrated that the optimized FFNN showed superior predictivities in terms of excellent reproducibility of existing flow data, powerful interpolation and reasonable extrapolation, which notably outperformed those of the classical constitutive models. To further test the applicability of the FFNN-based model in numerical simulations, it was implemented into the finite-element (FE) code together with an efficient automatic differentiation programme. The reasonable prediction of the heterogeneous metal flow during the benchmark compression test manifested the feasibility of the multilayer FFNNs as advanced constitutive models, which were trained directly from the experimental flow data.

Graphical Abstract

短句来源研究了（βo + γ） TiAl合金在1000 ~ 1150℃、应变速率100 ~ 10-3 s−1范围内的变形行为，变形过程中出现了复杂而不规则的流动硬化/软化，主要是由于初始亚稳组织和相变的发生。因此，即使采用高柔性应变补偿双曲正弦律，也很难用传统的本构关系来模拟流体的流动特性。因此，在本研究中，我们试图建立一个基于多层前馈神经网络（FFNN）的精确本构模型。为此，构建并评估了具有不同宽度（每层节点数）和深度（隐藏层数）的ffnn。为了使每个FFNN达到最佳性能，提出了一种双循环训练策略，其中选择了一个包含4个隐藏层和每层4个节点的最优架构来平衡过拟合和欠拟合。经过系统验证，优化后的FFNN在对现有流动数据的再现性好、插值功能强、外推合理等方面具有优越的预测能力，明显优于经典本构模型。为了进一步测试基于ffnn的模型在数值模拟中的适用性，将其与有效的自动微分程序一起实现到有限元（FE）代码中。对基准压缩试验中非均质金属流动的合理预测，证明了多层ffnn作为直接从实验流动数据中训练的高级本构模型的可行性。图形抽象

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引用次数: 0

Dislocation Network and Microstructural Characterization of Directionally Solidified GTD-111 Nickel-Based Superalloy after Long-Term Service Exposure 长期使用后定向凝固GTD-111镍基高温合金的位错网络及显微组织表征

IF 4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Metals and Materials International

Pub Date : 2025-05-13 DOI: 10.1007/s12540-025-01951-6

Hassan Ghorbani, Hassan Farhangi, Mehdi Malekan, Zishu Sun, Xiangwei Jiang

This study focuses on investigating the effects of long-term service exposure on the microstructure and creep properties of directionally solidified GTD-111 Nickel base superalloy as a land-based gas turbine blade. After a duration of 76,000 h, the examination of the airfoil microstructure through optical microscopy, scanning electron microscopy, and transmission electron microscopy (TEM) demonstrated significant changes. These changes included the coarsening of primary γ′ particles, the decomposition of MC carbides, the emergence of needle-like phases, and the formation of dislocation patterns. TEM observations verified that within the critical zone of the airfoil, there was a notable presence of extensive dislocation networks observed in both the γ channels and at the γ/γ′ interfaces. Furthermore, the examination of the creep-tested samples using TEM unveiled the existence of tightly-packed dislocations within the γ channels, accompanied by the occurrence of shearing dislocations in the γ′ phases. Upon analyzing the TEM observations, it has been concluded that the primary mechanism of creep occurring during the service exposure of the examined alloy is a composite process involving the movement of dislocations through gliding, climbing, and cross-slipping.

Graphic Abstract

本研究主要研究了长期使用暴露对定向凝固GTD-111镍基高温合金陆基燃气轮机叶片组织和蠕变性能的影响。在持续76,000小时后，通过光学显微镜，扫描电子显微镜和透射电子显微镜（TEM）对翼型微观结构进行了检查，证明了显著的变化。这些变化包括初生γ′颗粒的粗化，MC碳化物的分解，针状相的出现以及位错图案的形成。TEM观察证实，在翼型的临界区域内，在γ通道和γ/γ′界面处观察到明显存在广泛的位错网络。此外，使用TEM对蠕变测试样品的检查揭示了γ通道内紧密堆积的位错的存在，并伴随着γ′相中剪切位错的发生。通过对透射电镜观察结果的分析，可以得出结论，在所检测合金的使用暴露期间发生蠕变的主要机制是一个复合过程，包括滑移、爬升和交叉滑移等位错运动。图形抽象

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引用次数: 0

Data–Driven Stress Prediction and Microstructure Characterization During Hot Deformation of Al–Zn–Mg–Cu Alloys Al-Zn-Mg-Cu合金热变形过程应力预测及显微组织表征

IF 4 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Metals and Materials International

Pub Date : 2025-05-12 DOI: 10.1007/s12540-025-01946-3

Min Bai, Xiaodong Wu, Lingfei Cao, Songbai Tang, Youcai Qiu, Ying Zhou, Xiaomin Lin, Zhenghao Zhang

A data-driven model for stress prediction of hot-deformed Al–Zn–Mg–Cu alloys was developed. The model utilized 9397 datasets, encompassing 22 features including alloy composition, homogenization treatment parameters and hot deformation parameters. Machine learning methods, including Linear Regression, Random Forest Regression, Decision Tree (DT), Artificial Neural Network, Support Vector Machine, and Gaussian Process Regression, are used to develop models to predict flow stress. Through data preprocessing and feature selection, 19 key features were identified, and a data partition ratio of 8:2 for training-to-test sets was found to yield optimal model performance, with an adjusted coefficient of determination (R²) of 0.93329 and an outlier-bias-bias error ratio of 0.00851. The developed models were used to predict the flow stress of the Al–6.3Zn–2.5Mg–2.6 Cu–0.11Zr alloy upon hot compression with interpolation and extrapolation strategies. The results indicated that the RF and DT models demonstrated excellent stability and generalization capability in predicting the alloy’s flow behavior. Microstructure changes at various deformation temperatures and strain rates were characterized, and the correlation among flow stresses, deformation parameters and microstructure was analyzed, providing deeper insights into the hot deformation behavior of Al–Zn–Mg–Cu alloys and potentially guiding the process optimization for industrial applications.

Graphical Abstract

建立了热变形Al-Zn-Mg-Cu合金应力预测数据驱动模型。该模型利用9397个数据集，包含合金成分、均匀化处理参数和热变形参数等22个特征。机器学习方法，包括线性回归、随机森林回归、决策树（DT）、人工神经网络、支持向量机和高斯过程回归，用于开发预测流动应力的模型。通过数据预处理和特征选择，识别出19个关键特征，发现训练集与测试集的数据分割比为8:2时，模型性能最优，调整后的决定系数（R2）为0.93329，离群-偏倚-偏倚误差率为0.00851。采用插值和外推的方法对Al-6.3Zn-2.5Mg-2.6 Cu-0.11Zr合金的热压缩流动应力进行了预测。结果表明，RF和DT模型在预测合金流动行为方面具有良好的稳定性和通用性。表征了不同变形温度和应变速率下的微观组织变化，分析了流变应力、变形参数和微观组织之间的相关性，为进一步了解Al-Zn-Mg-Cu合金的热变形行为提供了依据，并有可能指导工业应用的工艺优化。图形抽象

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