Journal of Alloys and Metallurgical Systems最新文献

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Journal of Alloys and Metallurgical Systems

Pub Date : 2026-01-01

引用次数: 0

Journal of Alloys and Metallurgical Systems

Pub Date : 2026-01-01

引用次数: 0

Journal of Alloys and Metallurgical Systems

Pub Date : 2026-01-01

引用次数: 0

Journal of Alloys and Metallurgical Systems

Pub Date : 2026-01-01

引用次数: 0

Effect of process parameters on bead geometry and microstructure of the stainless steel fabricated by wire arc additive manufacturing 工艺参数对电弧增材制造不锈钢焊头几何形状和显微组织的影响

Journal of Alloys and Metallurgical Systems

Pub Date : 2025-12-19 DOI: 10.1016/j.jalmes.2025.100231

Huifeng Qin , Wensha Zhu , Huajun Zhang

The selection of appropriate wire arc additive manufacturing (WAAM) parameters is crucial for controlling bead morphology and dimensional accuracy in multi-layer metallic structures. This study investigates cold metal transfer (CMT)-based WAAM of 316 L stainless steel with a particular focus on two key process variables—deposition current and auxiliary wire feed speed—to establish their combined influence on bead geometry and microstructure. Unlike existing AWF-CMT WAAM studies, this work first determines the maximum stable arc travel speed for both T-CMT and AWF-CMT modes, providing an essential process boundary for high-efficiency manufacturing. Single-layer tracks were fabricated using S316L wire following an orthogonal experimental design, enabling a systematic evaluation of parameter interactions. The results reveal that arc travel speed, deposition current, and auxiliary wire feed speed exert strong coupled effects on bead width and height. Furthermore, microstructural characterization using optical microscopy and electron backscatter diffraction demonstrates that auxiliary-wire-assisted CMT produces significant quantitative grain refinement, the T-CMT deposits exhibit a relatively coarser grain structure, whereas the AWF-CMT process produces a more refined and more uniform microstructure in the deposited region, reducing the average grain size from 130μm (T-CMT) to 86μm(AWF-CMT). This study therefore establishes a new process–structure relationship for AWF-CMT WAAM and demonstrates that 316 L components manufactured with this technique exhibit markedly improved microstructural quality, confirming its suitability for industrial deployment.

选择合适的电弧增材制造（WAAM）工艺参数对于控制多层金属结构的焊头形貌和尺寸精度至关重要。本研究研究了基于冷金属转移（CMT）的316 L不锈钢的WAAM，特别关注两个关键工艺变量-沉积电流和辅助送丝速度-以确定它们对焊头几何形状和微观结构的综合影响。与现有的AWF-CMT WAAM研究不同，这项工作首先确定了T-CMT和AWF-CMT模式的最大稳定弧行速度，为高效制造提供了必要的工艺边界。采用正交实验设计，使用S316L线制作单层轨道，从而能够对参数相互作用进行系统评估。结果表明，电弧行程速度、沉积电流和辅助送丝速度对焊头宽度和高度有很强的耦合影响。此外，利用光学显微镜和电子背散射衍射进行的显微结构表征表明，辅助线辅助CMT工艺产生了显著的定量晶粒细化，T-CMT沉积具有相对粗糙的晶粒结构，而AWF-CMT工艺在沉积区域产生了更精细和更均匀的微观结构，将平均晶粒尺寸从130μm （T-CMT）减小到86μm（AWF-CMT）。因此，本研究建立了AWF-CMT WAAM的新工艺结构关系，并证明用该技术制造的316 L组件的显微组织质量显着提高，证实了其适合工业部署。

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引用次数: 0

An attempt toward machine learning-driven optimization of manufacturing processes for metal-supported solid oxide fuel cells using nickel and iron oxides as raw support materials 利用镍和铁氧化物作为原材料，对金属支撑固体氧化物燃料电池的制造工艺进行机器学习驱动优化的尝试

Journal of Alloys and Metallurgical Systems

Pub Date : 2025-12-08 DOI: 10.1016/j.jalmes.2025.100230

Hirofumi Sumi , Mizuki Momai , Yuki Yamaguchi

A novel fabrication method for metal-supported solid oxide fuel cells (SOFCs) is proposed using nickel and iron oxides as raw support materials. This approach enables the co-sintering of all components in their oxide states via conventional ceramic processing. To minimize cell warpage, which is a critical issue in mechanical integrity, machine learning models, including random forest and linear regression, are employed to optimize the manufacturing process parameters. The random forest regression model demonstrated superior predictive accuracy (RMSE = 0.01454 and R² = 0.7310) than the linear regression model (RMSE = 0.02253 and R² = 0.4642), effectively capturing the non-linear relationships between the manufacturing process parameters and cell warpage. The electrolyte thickness, presintering temperature, and Ni/(Fe+Ni) atomic ratio are identified as key factors influencing cell warpage. Material characterizations using X-ray diffraction and coefficient of thermal expansion measurements validate these predictions. Although the open circuit voltage remains below the theoretical electromotive force owing to residual microstructural defects in the electrolyte, the cell warpage successfully reduced from 0.07578 to 0.03825 by increasing the presintering temperature from 1150 to 1250 °C. These results demonstrate the potential of machine learning for guiding manufacturing process optimization of mechanically robust and high-performance metal-supported SOFCs.

提出了一种以镍和铁氧化物为原料制备金属支撑固体氧化物燃料电池（SOFCs）的新方法。这种方法可以通过传统的陶瓷加工使所有成分在氧化状态下共烧结。为了最大限度地减少细胞翘曲，这是机械完整性中的一个关键问题，采用机器学习模型，包括随机森林和线性回归，来优化制造工艺参数。随机森林回归模型的预测精度（RMSE = 0.01454, R2 = 0.7310）优于线性回归模型（RMSE = 0.02253, R2 = 0.4642），有效地捕捉了制造工艺参数与细胞翘曲之间的非线性关系。电解液厚度、预熔温度和Ni/(Fe+Ni)原子比是影响电池翘曲的关键因素。使用x射线衍射和热膨胀系数测量的材料特性验证了这些预测。虽然由于电解液中残留的微结构缺陷，开路电压仍然低于理论电动势，但通过将预熔温度从1150℃提高到1250 ℃，电池翘曲成功地从0.07578降低到0.03825。这些结果证明了机器学习在指导机械鲁棒性和高性能金属支撑sofc的制造工艺优化方面的潜力。

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引用次数: 0

A comprehensive comparison of dynamic strain localisation and mechanical behaviour in traditional and additively manufactured Ti6Al4V 传统和增材制造Ti6Al4V的动态应变局部化和力学行为的综合比较

Journal of Alloys and Metallurgical Systems

Pub Date : 2025-12-06 DOI: 10.1016/j.jalmes.2025.100228

Govind Gour , Antonio Pellegrino

Titanium alloys are widely used in aerospace, defence, automotive, and biomedical engineering owing to their high specific strength and excellent corrosion resistance. Additive manufacturing has emerged as a promising alternative to conventional production methods, offering the capability to fabricate complex geometries while reducing processing time and material waste. In this study, the high strain rate deformation behaviour of Ti6Al4V produced by selective laser melting is investigated using a Split Hopkinson Tension Bar system equipped with a multi-camera high-speed imaging setup. A comprehensive experimental programme is conducted on specimens manufactured in three different build orientations to assess the influence of processing direction on dynamic strain localisation and true stress–strain response. The post-necking behaviour is examined and compared with that of conventionally forged Ti6Al4V, revealing notable differences in ductility and strain localisation mechanisms. In addition, the high strain rate compressive behaviour of both material variants and their temperature dependence are investigated using a Split Hopkinson Compression Bar system equipped with thermal conditioning. The deformation and failure mechanisms of additively manufactured specimens produced in different orientations are further examined through post-mortem analysis of the fracture surfaces.

钛合金具有高比强度和优异的耐腐蚀性，广泛应用于航空航天、国防、汽车和生物医学工程等领域。增材制造已经成为传统生产方法的一种有前途的替代方法，它能够制造复杂的几何形状，同时减少加工时间和材料浪费。在本研究中，使用配备多摄像头高速成像装置的分离式霍普金森张力杆系统研究了选择性激光熔化Ti6Al4V产生的高应变速率变形行为。为了评估加工方向对动态应变局部化和真应力-应变响应的影响，在三种不同的构建方向下对试样进行了综合试验。研究了后颈缩行为，并将其与传统锻造的Ti6Al4V进行了比较，揭示了延展性和应变局部化机制的显著差异。此外，两种材料变体的高应变率压缩行为及其温度依赖性使用配备热调节的分离式霍普金森压缩棒系统进行了研究。通过对断口表面的事后分析，进一步研究了不同取向的增材试样的变形和破坏机制。

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引用次数: 0

Microstructural evolution of Mg-Nd-Zr alloy during multi-directional reverse shear processing Mg-Nd-Zr合金多向反剪切过程中的组织演变

Journal of Alloys and Metallurgical Systems

Pub Date : 2025-11-19 DOI: 10.1016/j.jalmes.2025.100226

O. Tarasov , V. Greshta , D. Pavlenko , D. Tkach , O. Altukhov

This study investigates the microstructural evolution and hardness response of a Mg–Nd–Zr alloy subjected to a novel hot multi-directional reverse shear (MDRS) process developed by the authors. The MDRS technique represents a severe plastic deformation route designed to enhance shear deformation. This method was applied to deform the magnesium alloy under near-isothermal conditions. Finite element modeling and experimental data show that MDRS provides a more uniform distribution of equivalent strain than traditional MDF/CCDF processing routes. After four consecutive cycles, the ratio of accumulated strain in the central region to that in the peripheral region (inhomogeneity coefficient) is 2.5 for MDF and 1.62 for MDRS, respectively. The as-cast microstructure consists of equiaxed α-Mg grains (∼47 μm) and grain-boundary Mg₁₂Nd-type and Zr-rich particles, as confirmed by combined XRD and SEM/EDS analysis. MDRS processing leads to a non-monotonic grain size evolution: refinement to ∼32 μm after one cycle, partial coarsening to ∼39.7 μm after three cycles, and subsequent stabilisation at ∼41 μm after five cycles. The formation of a near-normal grain size distribution and ∼120° triple junctions after five cycles indicates a thermodynamically stabilised grain boundary network. The grain size and grain boundaries are controlled by the competition between deformation-induced grain refinement, accompanied by Zener pinning of the boundaries by dispersed particles, and thermally activated grain growth driven by continuous dynamic recrystallization. Microhardness increases by 6–16 % compared with the initial state. Higher hardness values are associated with regions of higher accumulated strain and refined grains. In contrast, the slight decrease in central hardness after five cycles correlates with partial grain coarsening, which remains above the initial level. The established relationships between strain distribution, microstructure and hardness demonstrate that MDRS is an efficient route for producing Mg–Nd–Zr alloy workpieces with controlled gradient properties and improved performance, promising for Mg-based bioresorbable implants and lightweight structural applications.

研究了Mg-Nd-Zr合金在热多向反剪切（MDRS）过程中的显微组织演变和硬度响应。MDRS技术代表了一种旨在增强剪切变形的剧烈塑性变形路线。将该方法应用于镁合金在近等温条件下的变形。有限元模拟和实验数据表明，与传统的MDF/CCDF加工路线相比，MDRS提供了更均匀的等效应变分布。连续4次循环后，MDF和MDRS的中心和外围累积应变之比（非均匀性系数）分别为2.5和1.62。结合XRD和SEM/EDS分析证实，铸态组织由等轴α-Mg晶粒（~ 47 μm）和晶界Mg₁₂nd型和富锆颗粒组成。MDRS处理导致晶粒尺寸的非单调演变：一个循环后细化到~ 32 μm，三个循环后部分粗化到~ 39.7 μm，五个循环后稳定在~ 41 μm。经过5次循环后，形成了接近正常的晶粒尺寸分布和~ 120°的三重结，这表明了一个热力学稳定的晶界网络。晶粒尺寸和晶界受变形诱导晶粒细化（分散颗粒对晶界的齐纳钉住）和连续动态再结晶驱动的热激活晶粒长大（热激活晶粒长大）两种因素的竞争控制。显微硬度比初始状态提高了6-16 %。较高的硬度值与较高的累积应变和细化晶粒的区域有关。中心硬度在5次循环后略有下降，与部分晶粒粗化有关，但仍高于初始水平。建立的应变分布、显微组织和硬度之间的关系表明，MDRS是生产具有可控梯度性能和改进性能的Mg-Nd-Zr合金工件的有效途径，有望用于mg基生物可吸收植入物和轻量化结构应用。

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引用次数: 0

Carbon fibre for applications in aerospace: A review 碳纤维在航空航天中的应用综述

Journal of Alloys and Metallurgical Systems

Pub Date : 2025-11-19 DOI: 10.1016/j.jalmes.2025.100227

Rizalman Mamat , Muhammad Ikram Mohd Rashid , A.Z. Syahir , Erdiwansyah , Ahmad Fitri Yusop , Ahmad Tamimi

The aerospace industry increasingly relies on advanced composite materials to enhance structural performance while reducing environmental impact. Among these materials, carbon fibre-reinforced polymers (CFRPs) have emerged as the dominant choice due to their exceptional strength-to-weight ratio, fatigue resistance, and thermal stability. This review aims to provide a comprehensive analysis of the development, properties, manufacturing techniques, and sustainability aspects of carbon fibre composites in aerospace applications. A systematic literature-based approach was employed to evaluate recent advancements in microstructural design, automated manufacturing, and recycling technologies. The findings reveal that carbon fibre composites achieve 30–50 % weight reduction and 20–25 % fuel savings compared to traditional aluminium and titanium alloys, while maintaining superior mechanical and thermal performance. Emerging AI-driven, digital twin-based manufacturing systems improve process reliability, reducing defect rates by up to 30 % and reducing production cycles by 25–35 %. Moreover, hybrid and nanoreinforced composites incorporating carbon nanotubes or graphene demonstrate 10–25 % improvements in interlaminar strength and damage tolerance. From a sustainability perspective, recycling methods such as pyrolysis and solvolysis enable the recovery of 90–95 % of carbon fibres with minimal property degradation, supporting circular economy goals. The novelty of this review lies in integrating materials science, digital manufacturing, and sustainability to establish a unified framework for next-generation aerospace composites. In conclusion, carbon fibre technology stands at the intersection of high performance, intelligent manufacturing, and environmental responsibility, driving the evolution toward lighter, stronger, and more innovative aerospace systems.

航空航天工业越来越依赖于先进的复合材料来增强结构性能，同时减少对环境的影响。在这些材料中，碳纤维增强聚合物（CFRPs）因其卓越的强度重量比、抗疲劳性和热稳定性而成为主要选择。本文综述了碳纤维复合材料在航空航天领域的发展、性能、制造技术和可持续性等方面的综合分析。采用基于文献的系统方法来评估微结构设计、自动化制造和回收技术的最新进展。研究结果表明，与传统的铝合金和钛合金相比，碳纤维复合材料的重量减轻了30 - 50% %，燃料节省了20 - 25% %，同时保持了卓越的机械和热性能。新兴的人工智能驱动、基于数字孪生的制造系统提高了工艺可靠性，将缺缺率降低了30% %，将生产周期缩短了25 - 35% %。此外，含有碳纳米管或石墨烯的杂化和纳米增强复合材料在层间强度和损伤容限方面提高了10-25 %。从可持续发展的角度来看，热解和溶剂分解等回收方法能够以最小的性能降解回收90 - 95% %的碳纤维，支持循环经济目标。该综述的新颖之处在于将材料科学、数字制造和可持续性相结合，建立了下一代航空航天复合材料的统一框架。总之，碳纤维技术是高性能、智能制造和环境责任的交汇点，推动了航空航天系统向更轻、更强、更创新的方向发展。

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引用次数: 0

Ensemble analysis of parameters optimizations of copper electroplated NiTinol Plate through Matlab and robotic swarm particle 基于Matlab和机器人群粒子的镀铜镍钛诺板参数优化的集合分析

Journal of Alloys and Metallurgical Systems

Pub Date : 2025-11-18 DOI: 10.1016/j.jalmes.2025.100225

Kavita Kripalani

Ensemble analysis of parameters optimization using Artificial Intelligence (AI) techniques of full factorial Swarm Differential Algorithm (SDA) and further with Matlab was applied in experimental procedure conducted in copper electroplated NiTinol Plate by evaluating its surface roughness of NiTinol plate. This approach applied optimization module using Artificial Intelligence model of swarm particle optimization which enhanced the accuracy and reliability of the parameters implied control. The analysis was done based on parameter analysis of temperature, thickness of Copper electroplated NiTinol plate, current density. After Data prepossessing, support vector Regression (SVR) was analyzed for pragmatic. Further, datasets were splatted into trained AI Model using subsequently its each dataset and then validating sets by evaluating individual performances. Stacking was used for training meta-model for combined predictions of individual models. Optimized parameters using Swarm differential algorithm in MATLAB was deployed. The results of the ensemble analysis were used to further validate the parameters of temperature and current density of electroplated NiTi plates. Optimized parameters model was further used for predicting and controlling the surface roughness in electroplated NiTinol plate which hence enhanced its surface finish. The analysis of Nitinol electroplating using swarm intelligence technique optimized coating thickness and surface roughness thus enhanced solder ability providing a sacrificial layer of micro fabrication,corrosion resistant biocompatible surface layer. The approach utilized a simulated 10 × 10 grid of measurements to identify under plated regions and rough surface areas, followed by a Particle Swarm Optimization (PSO) and MATLAB based parameters optimization strategy.

通过对镀铜镍钛诺板表面粗糙度的评价，将人工智能（AI）全因子群微分算法（SDA）参数优化的集成分析和Matlab应用于镍钛诺板的实验过程中。该方法将优化模块应用于人工智能的群粒子优化模型，提高了参数隐含控制的准确性和可靠性。通过对温度、镀铜镍钛诺板厚度、电流密度等参数的分析。数据预处理后，对支持向量回归（SVR）进行了实用分析。此外，数据集被分散到经过训练的人工智能模型中，随后使用其每个数据集，然后通过评估个人性能来验证集。使用堆叠方法训练元模型，对单个模型进行组合预测。利用MATLAB中的群微分算法对参数进行优化。利用系综分析的结果进一步验证了电镀镍钛板的温度和电流密度参数。利用优化后的参数模型对电镀镍钛诺板的表面粗糙度进行预测和控制，从而提高镀层的表面光洁度。利用群智能技术对镍钛诺镀层进行分析，优化镀层厚度和表面粗糙度，从而提高焊点性能，为微加工牺牲层、耐腐蚀生物相容性面层提供了有利条件。该方法利用模拟的10 × 10测量网格来识别镀下区域和粗糙表面，然后采用粒子群优化（PSO）和基于MATLAB的参数优化策略。

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