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High-quality laser slicing of single-crystal semiconductors guided by energy-dependent phase transition and crack propagation: A 4H-SiC case study 基于能量依赖相变和裂纹扩展的单晶半导体高质量激光切片:以4H-SiC为例
IF 18.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2026-01-06 DOI: 10.1016/j.ijmachtools.2026.104365
Zelong Qing , Bo Liu , Yaoen Luo , Yi Zhang
Laser internal modification slicing has emerged as a high-efficiency, low-damage technique for slicing single-crystal semiconductor substrates like 4H-SiC. However, its widespread adoption has been hindered by a limited mechanistic understanding of how laser energy couples with material response to govern phase transitions and crack propagation, especially at the atomic scale. In particular, the roles of nanosecond laser thermal effects in driving controllable phase transformation and the underlying crack dynamics remain unclear, making process optimization largely empirical. Here, by combining energy-controlled experiments with molecular dynamics (MD) simulations, we elucidate an energy-dependent, multistage phase transition pathway in laser-sliced 4H-SiC. This pathway progresses from initial amorphization with Si/C precipitation to thermal-stress-induced plastic slip that generates stacking faults and cubic 3C-SiC at the amorphous–crystalline interface. A critical energy threshold is identified that dictates the transition between distinct modification regimes and governs corresponding crack propagation behavior. Atomistic simulations further reveal the mechanisms of thermal stress-driven crack nucleation and propagation, along with a temperature-dependent fracture strength and shift in crystallographic cracking preference—from low-index planes under high temperature to high-index planes during cooling. The insights presented in this work bridge laser processing parameters with intrinsic material behavior, offering a mechanistic foundation for the rational design of laser-based slicing processes and achieving optimized processing quality. While demonstrated on 4H-SiC, the underlying energy- and stress-governed principles are applicable to a wider class of hard-brittle, anisotropic semiconductors, advancing the transition from empirical tuning to physics-informed manufacturing.
激光内修饰切片是一种高效率、低损伤的单晶半导体衬底切片技术。然而,由于对激光能量如何与材料响应耦合以控制相变和裂纹扩展(特别是在原子尺度上)的有限机制理解,阻碍了其广泛采用。特别是,纳秒激光热效应在驱动可控相变和潜在裂纹动力学中的作用尚不清楚,使得工艺优化主要是经验的。在这里,通过结合能量控制实验和分子动力学(MD)模拟,我们阐明了激光切割4H-SiC的能量依赖的多阶段相变途径。这一过程从Si/C析出的初始非晶化到热应力诱发的塑性滑移,从而在非晶界面产生层错和立方3C-SiC。确定了一个临界能量阈值,该阈值决定了不同变形机制之间的转变,并控制了相应的裂纹扩展行为。原子模拟进一步揭示了热应力驱动裂纹形核和扩展的机制,以及与温度相关的断裂强度和晶体开裂偏好的转变——从高温下的低折射率面到冷却时的高折射率面。本工作提出的见解将激光加工参数与材料的内在行为联系起来,为合理设计基于激光的切片工艺和实现优化的加工质量提供了机制基础。虽然在4H-SiC上进行了演示,但潜在的能量和应力控制原理适用于更广泛的硬脆、各向异性半导体,推进了从经验调谐到物理信息制造的转变。
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引用次数: 0
Investigation of the 3D-posture planning for space-restricted robotic milling: A potential network architecture 空间受限机器人铣削三维姿态规划研究:一种潜在的网络架构
IF 18.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2026-01-05 DOI: 10.1016/j.ijmachtools.2026.104364
Juntong Su , Shengqiang Zhao , Fangyu Peng , Xiaowei Tang , Rong Yan
Industrial robots are beneficial in the machining of large and complex parts because of their high flexibility and large workspace. Numerous studies have demonstrated that the geometric, kinematic, static and dynamic performances of robotic milling processes exhibit a high degree of posture dependence. Therefore, ensuring the spatial accessibility and machining performance of a robotic milling task through posture planning is essential. Posture planning has been employed in prior research to enhance robotic milling performance in open scenarios. However, several limitations are persistent. At the methodological level, multi-dimensional posture planning algorithms suitable for robotic milling tasks in restricted spaces are unavailable. The capacity of existing planning algorithms to balance multiple constraints and objectives, along with their scalability, requires further optimisation. As complex curved surface parts tend towards larger sizes, robotic posture planning faces significant challenges in complex milling scenarios. Therefore, this paper proposes a novel 3D posture planning strategy. First, a potential network architecture for multi-constraint and multi-objective planning tasks is proposed, offering the advantages of flexible expansion and portable deployment. The architecture models the dynamic distribution law of input constraint-objective sets in the planning space to formulate appropriate planning strategies. Furthermore, a posture manifold considering the cutter-workpiece engagement state is proposed to balance the flexibility of posture adjustment and machining quality. By altering the parametric equations of the posture manifold, posture planning execution can be adjusted rapidly to adapt to various machining conditions. To verify the effectiveness of the proposed method, a benchmark task for robotic milling in a restricted space is designed. The further experimental validations of propellers machining show that the proposed planning method can generate feasible machining posture trajectories under multi-constraint working conditions in a restricted space. The proposed method provides a foundation for the robotic milling of large-scale and space-restricted core components, including aircraft parts, aerospace cabins and marine propellers.
工业机器人具有高度的灵活性和较大的工作空间,有利于大型复杂零件的加工。大量研究表明,机器人铣削过程的几何、运动学、静态和动态性能表现出高度的姿态依赖性。因此,通过姿态规划确保机器人铣削任务的空间可达性和加工性能至关重要。姿态规划已经在先前的研究中用于提高机器人在开放场景下的铣削性能。然而,一些限制仍然存在。在方法层面上,适合机器人在有限空间铣削任务的多维姿态规划算法是不可用的。现有规划算法平衡多个约束和目标的能力,以及它们的可扩展性,需要进一步优化。随着复杂曲面零件尺寸的增大,复杂铣削场景下的机器人姿态规划面临重大挑战。为此,本文提出了一种新的三维姿态规划策略。首先,提出了一种多约束、多目标规划任务的潜在网络架构,具有灵活扩展和可移植部署的优点;该体系结构对输入约束目标集在规划空间中的动态分布规律进行建模,以制定相应的规划策略。在此基础上,提出了考虑刀-工件啮合状态的姿态流形,以平衡姿态调整的灵活性和加工质量。通过改变姿态流形的参数方程,可以快速调整姿态规划的执行,以适应各种加工条件。为了验证该方法的有效性,设计了一个受限空间机器人铣削基准任务。螺旋桨加工的进一步实验验证表明,该规划方法能够在有限空间内的多约束工况下生成可行的加工姿态轨迹。提出的方法为大型和空间受限的核心部件的机器人铣削提供了基础,包括飞机零件、航空舱室和船舶螺旋桨。
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引用次数: 0
Micrometric orthogonal cutting can lead to sideway chip flow: Uncovering crystallographic orientation and grain boundary effects 微尺度正交切削可导致切屑侧向流动:揭示晶体取向和晶界效应
IF 18.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2025-12-20 DOI: 10.1016/j.ijmachtools.2025.104363
Shusong Zan, Zhirong Liao, Jose A. Robles Linares, Kieran Winter, Dragos Axinte
Micrometric cutting has attracted great research interest both in academic and industrial areas due to its vital role in microfabrication. Different from macro-cutting where many grains are involved in the process that averages/minimises the crystallographic effects, in micrometric cutting localised crystallographic deformation mechanisms can highly affect the machining results. However, experimental challenges of micrometric level cutting have confined most investigations to simulations or less-ideal tests (e.g. micro-scratching and single-point diamond turning), leaving the detailed interplay between chip flow and microstructure largely unexplored. In an apparent paradox, in orthogonal micrometric level cutting conditions, expected to yield forward (2D) chip flow, can produce pronounced sideway (3D) chip flow when grain-orientation anisotropy and boundary-induced kinematic constraints dominate; such aspects cannot be captured in macro-cutting. Based on these, when cutting at micrometric level it is important to understand how the slip system of the grains will be activated, what will happen when the grain boundary is encountered, as well as why the specific chip form and flow direction is generated under different conditions of these. To resolve this, grain orientations and boundaries were pre-characterised on a Ni-based superalloy sample, on which micrometric boss features were subsequently fabricated. Orthogonal grain-level cutting tests were then conducted on these structures, effectively isolating the deformation region, eliminating constraints from adjacent material, and allowing the chip to flow freely on both sides. Chip morphology, flow direction, and local deformation mechanisms were examined via advanced material characterisation technologies. Key findings that are specifically manifested at micro level include: The formation of serrated chips is influenced by the Schmid factor, resulting in variations in segment morphology across different crystallographic orientations. Sideway chip flow can be generated in micrometric orthogonal cutting process due to the selective activation of the slip-systems and inclined grain boundary guided sliding. Furthermore, when twin boundary exists, periodic extrusion-shear dominated material deformation cycle can happen in chip formation process due to the alternated stress. Therefore, we reveal for the first time that when cutting at grain levels, although geometrically defined orthogonal cutting was performed, the chip follows crystallographic rules imposed by slip planes and grain boundary conditions. These insights provide a new mechanistic framework for understanding micrometric level cutting anisotropy and the boundary-driven paradox of sideways chips, offering guidelines to optimise micrometric machining strategies in microfabrication applications.
微切削由于其在微细加工中的重要作用而引起了学术界和工业界的极大兴趣。与宏观切削不同的是,在微观切削中,许多晶粒参与到平均/最小化晶体效应的过程中,局部晶体变形机制会严重影响加工结果。然而,微米水平切削的实验挑战限制了大多数研究仅限于模拟或不太理想的测试(例如微划痕和单点金刚石车削),使得切屑流动和微观结构之间的详细相互作用在很大程度上未被探索。一个明显的悖论是,在正交微米级切削条件下,当晶粒取向各向异性和边界诱导的运动学约束占主导地位时,预期会产生正向(2D)切屑流动,却会产生明显的侧向(3D)切屑流动;这些方面无法在宏观裁剪中捕捉到。在此基础上,在微米级切削时,重要的是要了解晶粒的滑移系统是如何被激活的,当遇到晶界时会发生什么,以及为什么在这些不同的条件下会产生特定的切屑形式和流动方向。为了解决这个问题,在镍基高温合金样品上预先表征了晶粒取向和边界,随后在其上制备了微米凸台特征。然后对这些结构进行正交晶级切削试验,有效地隔离了变形区域,消除了相邻材料的约束,使切屑在两侧自由流动。通过先进的材料表征技术,研究了切屑形态、流动方向和局部变形机制。在微观层面上具体表现的关键发现包括:锯齿状芯片的形成受到施密德因子的影响,导致不同晶体学取向的片段形态变化。在微尺度正交切削过程中,由于滑移系统的选择性激活和斜晶界导向滑动,会产生侧向切屑流。当孪晶边界存在时,由于交变应力的作用,切屑形成过程中会发生以挤压-剪切为主的周期性材料变形循环。因此,我们首次揭示了当在晶粒水平切割时,尽管进行了几何定义的正交切割,但切屑遵循滑移面和晶界条件施加的晶体学规则。这些见解为理解微米级切削各向异性和横向芯片的边界驱动悖论提供了新的机制框架,为优化微加工应用中的微米加工策略提供了指导。
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引用次数: 0
Online time-optimal trajectory planning along parametric toolpaths with strict constraint satisfaction and certifiable feasibility guarantee 基于参数化刀具路径的在线时间最优轨迹规划,具有严格的约束满足和可验证的可行性保证
IF 18.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2025-12-18 DOI: 10.1016/j.ijmachtools.2025.104355
Yunan Wang, Chuxiong Hu, Yuanshenglong Li, Jichuan Yu, Jizhou Yan, Yixuan Liang, Zhao Jin
As a fundamental technique in computer numerical control (CNC) machining, time-optimal trajectory planning (TOTP) is crucial for enhancing machining efficiency, geometric accuracy, and surface quality. However, it remains challenging to reliably generate smooth time-optimal trajectories online, particularly under complex constraints. This study aims to address the above longstanding challenges which limit the reliability and efficiency of online optimization-based TOTP approaches, thereby unlocking their practical advantages in real-world machining. A TOTP method along parametric toolpaths, namely TOTP-SPLP, is developed. The proposed piecewise linear objective function and sequential procedure improve time-optimality and avoid singularities at zero feedrate compared with existing linear formulations. Complex constraints are strictly satisfied at grid points over the entire toolpath without relying on static approximations, where exceedance between grid points is negligible and theoretically bounded by the grid density based on the developed analytical interpolation. To certifiably guarantee the feasibility during online TOTP, a hierarchical look-ahead windowing (HLAW) framework is established, which achieves a 100% success rate of optimization feasibility for long toolpaths. Simulation and real-world experiments demonstrate that the proposed TOTP-SPLP significantly outperforms existing online TOTP baselines in terms of time-optimality and numerical stability within limited computational cost. Specifically, TOTP-SPLP reduces terminal time by 15.6%–56.0% compared with baselines of lower computational cost, and outperforms more computationally expensive baselines by 9.5%. Comparable performance to our TOTP-SPLP is achieved by offline baselines only when consuming tenfold computational time. For a long toolpath with millions of grid points, the developed HLAW reduces the thousands of infeasibility cases encountered by existing online framework to zero. The strict satisfaction of complex constraints helps suppress vibrations and improve surface quality in real-world machining. In summary, this work fundamentally advances online TOTP by achieving offline-level time-optimality with certifiable feasibility under strict complex constraints, making reliable online optimization-based TOTP possible and practical in CNC machining.
作为数控加工的一项基本技术,时间最优轨迹规划(TOTP)对提高加工效率、几何精度和表面质量至关重要。然而,可靠地在线生成光滑的时间最优轨迹仍然是一个挑战,特别是在复杂的约束条件下。本研究旨在解决上述长期存在的挑战,这些挑战限制了基于在线优化的TOTP方法的可靠性和效率,从而释放了它们在实际加工中的实际优势。提出了一种沿参数化刀具路径的topp方法,即topp - splp。所提出的分段线性目标函数和顺序过程与现有的线性公式相比,提高了时间最优性,避免了零进料速率下的奇异性。在整个刀具路径上的网格点上严格满足复杂的约束,而不依赖于静态近似,其中网格点之间的超出可以忽略不计,并且理论上由基于开发的解析插值的网格密度限定。为了验证在线topp的可行性,建立了分层预瞄窗口(HLAW)框架,实现了长刀具路径优化可行性的100%成功率。仿真和实际实验表明,在有限的计算成本下,所提出的topp - splp在时间最优性和数值稳定性方面明显优于现有的在线topp基线。具体而言,与计算成本较低的基准相比,TOTP-SPLP将终端时间减少了15.6%-56.0%,比计算成本较高的基准性能高出9.5%。只有在消耗10倍的计算时间时,离线基线才能实现与我们的topp - splp相当的性能。对于具有数百万网格点的长刀具轨迹,所开发的HLAW将现有在线框架遇到的数千种不可行情况减少到零。在实际加工中,严格满足复杂约束有助于抑制振动和提高表面质量。综上所述,本工作从根本上推进了在线TOTP,在严格复杂约束条件下实现了离线级时间最优性,并具有可验证的可行性,使基于在线优化的可靠TOTP在数控加工中成为可能和实用。
{"title":"Online time-optimal trajectory planning along parametric toolpaths with strict constraint satisfaction and certifiable feasibility guarantee","authors":"Yunan Wang,&nbsp;Chuxiong Hu,&nbsp;Yuanshenglong Li,&nbsp;Jichuan Yu,&nbsp;Jizhou Yan,&nbsp;Yixuan Liang,&nbsp;Zhao Jin","doi":"10.1016/j.ijmachtools.2025.104355","DOIUrl":"10.1016/j.ijmachtools.2025.104355","url":null,"abstract":"<div><div>As a fundamental technique in computer numerical control (CNC) machining, time-optimal trajectory planning (TOTP) is crucial for enhancing machining efficiency, geometric accuracy, and surface quality. However, it remains challenging to reliably generate smooth time-optimal trajectories online, particularly under complex constraints. This study aims to address the above longstanding challenges which limit the reliability and efficiency of online optimization-based TOTP approaches, thereby unlocking their practical advantages in real-world machining. A TOTP method along parametric toolpaths, namely TOTP-SPLP, is developed. The proposed piecewise linear objective function and sequential procedure improve time-optimality and avoid singularities at zero feedrate compared with existing linear formulations. Complex constraints are strictly satisfied at grid points over the entire toolpath without relying on static approximations, where exceedance between grid points is negligible and theoretically bounded by the grid density based on the developed analytical interpolation. To certifiably guarantee the feasibility during online TOTP, a hierarchical look-ahead windowing (HLAW) framework is established, which achieves a 100% success rate of optimization feasibility for long toolpaths. Simulation and real-world experiments demonstrate that the proposed TOTP-SPLP significantly outperforms existing online TOTP baselines in terms of time-optimality and numerical stability within limited computational cost. Specifically, TOTP-SPLP reduces terminal time by 15.6%–56.0% compared with baselines of lower computational cost, and outperforms more computationally expensive baselines by 9.5%. Comparable performance to our TOTP-SPLP is achieved by offline baselines only when consuming tenfold computational time. For a long toolpath with millions of grid points, the developed HLAW reduces the thousands of infeasibility cases encountered by existing online framework to zero. The strict satisfaction of complex constraints helps suppress vibrations and improve surface quality in real-world machining. In summary, this work fundamentally advances online TOTP by achieving offline-level time-optimality with certifiable feasibility under strict complex constraints, making reliable online optimization-based TOTP possible and practical in CNC machining.</div></div>","PeriodicalId":14011,"journal":{"name":"International Journal of Machine Tools & Manufacture","volume":"215 ","pages":"Article 104355"},"PeriodicalIF":18.8,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145784998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Process-driven microstructure design of 3D-Printed porous magnesium alloy scaffolds with tunable biodegradation kinetics 具有可调生物降解动力学的3d打印多孔镁合金支架的工艺驱动微观结构设计
IF 18.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2025-12-11 DOI: 10.1016/j.ijmachtools.2025.104362
Weiyun Xu , Hualuo Pang , Haojing Xu , Jinge Liu , Yufeng Zheng , Peng Wen
3D-printed biodegradable magnesium (Mg) alloy scaffolds are emerging as promising candidates for customized bone implants, offering tailored structure, mechanical performance, and bioactive functions to address diverse bone defects. However, the premature loss of structural integrity remains a critical challenge for clinical applications due to the complex kinetics of biodegradation. This study posits that the tunability of degradation, inherently governed by microstructure, is rooted in the 3D printing and heat treatment processes, which have been underexplored and lack scientific understanding. Using a process-driven microstructural design approach, we investigated how manufacturing influence the corrosion behavior of porous Mg alloy scaffolds. By analyzing the combined effects of layer thickness on microstructural evolution in laser powder bed fusion and high-temperature oxidation heat treatment, it was revealed that the as-printed microstructural features, governed by the printing parameters, exert a critical influence on the biodegradable performance after heat treatment. Comprehensive evaluations of fusion quality, mechanical responses, electrochemical properties, and immersion degradation behavior further indicated that the multi-level heterogeneous microstructure, formed by local elemental migration, anisotropic grain growth, and the development of layered oxide films, was identified as the key factor in regulating degradation. Our findings highlight a synergistic manufacturing-dominant mechanism for tuning biodegradation kinetics through control of microstructure, resulting in porous Mg alloy scaffolds with significantly improved durability. These advancements not only provide a pathway for developing high-performance 3D-printed biodegradable bone implants but also establish a generalized framework for fabricating reactive materials with intricate geometries and tailored functionalities.
3d打印可生物降解镁(Mg)合金支架正在成为定制骨植入物的有希望的候选材料,提供定制的结构,机械性能和生物活性功能,以解决各种骨缺陷。然而,由于生物降解的复杂动力学,结构完整性的过早丧失仍然是临床应用的关键挑战。该研究认为,降解的可调节性本质上受微观结构的控制,其根源在于3D打印和热处理工艺,而这些工艺尚未得到充分的探索和科学的理解。采用工艺驱动的微观结构设计方法,我们研究了制造如何影响多孔镁合金支架的腐蚀行为。通过分析层厚对激光粉末床熔合和高温氧化热处理过程中微观组织演变的综合影响,发现在打印参数的控制下,打印后的微观组织特征对热处理后的生物降解性能有着至关重要的影响。融合质量、力学响应、电化学性能和浸渍降解行为的综合评价进一步表明,局部元素迁移、各向异性晶粒生长和层状氧化膜形成的多层次非均质微观结构是调控降解的关键因素。我们的研究结果强调了通过控制微观结构来调节生物降解动力学的协同制造主导机制,从而显著提高了多孔镁合金支架的耐久性。这些进步不仅为开发高性能3d打印可生物降解骨植入物提供了途径,而且为制造具有复杂几何形状和定制功能的反应材料建立了一个通用框架。
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引用次数: 0
Martensitic transformation sensitivity–driven processing roadmap for laser powder bed fusion of NiTi shape memory alloys: Paradigm shift from defect elimination to precise performance control 激光粉末床熔合NiTi形状记忆合金马氏体相变灵敏度驱动工艺路线图:从缺陷消除到精确性能控制的范式转变
IF 18.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2025-12-02 DOI: 10.1016/j.ijmachtools.2025.104352
Dan Zheng , Ruidi Li , Jingtao Kang , Tiechui Yuan , Kefu Gan
Laser powder bed fusion (LPBF) fabricated NiTi shape memory alloys (SMAs) fabricated to comparably high density using different processing parameters can exhibit significant differences in martensitic transformation temperature (MTT) (differing by > 50 °C), altering their functional performance and making precise performance control challenging. Herein, we establish a simple but generalisable law, EL/v (where EL and v denote linear energy density and scan velocity, respectively), which governs densification and martensitic transformation behaviours in LPBF-processed Ni-rich NiTi SMAs. MTT sensitivity was introduced as a process evaluation metric, shifting the paradigm from conventional defect-centric frameworks toward performance-oriented optimisation. A parameter-dependent and universal vaporisation model is established by systematically decoupling the roles of energy input in MTT. Results demonstrate that Ni loss and MTT sensitivity depend on EL/v rather than on EL, with ∼0.67 at.% Ni loss per kJ·s·m−2 and a linear increase in the martensite start (MS) temperature of ∼83 K. Microstructural analyses confirm that EL/v governs melt pool overlap, mode stability and microstructural and transformational homogeneity. It is revealed that the amount of input energy density (e.g. EL) dictates melt pool geometry and densification, while the manner of input energy density (e.g. normalised input energy density rate, EL/v) governs melt pool dynamics, elemental vaporisation and microstructure evolution. This dual-criterion rationalises the MS temperature variability observed under identical energy densities and enables predictive control of transformation features, residual stress and precipitation. The proposed framework delivers NiTi components with superior tensile elongation (∼22 %), surpassing that of most LPBF-processed Ni-rich counterparts. Moreover, its universality is validated in 304L stainless steel and CuAlMn SMA, underscoring its applicability beyond NiTi SMAs. This study offers mechanistic insights into processing–melt pool dynamics–structure–property interactions and offers a universal roadmap for LPBF parameter design, advancing process optimisation beyond defect mitigation and enabling precise performance control through melt pool management.
激光粉末床熔合(LPBF)制备的NiTi形状记忆合金(sma)使用不同的工艺参数制备到相对较高的密度,可以表现出显著的马氏体转变温度(MTT)差异(相差50°C),改变其功能性能,并使精确的性能控制具有挑战性。在此,我们建立了一个简单但可推广的规律,EL/v (EL和v分别表示线性能量密度和扫描速度),它控制了lpbf加工的富ni NiTi sma的致密化和马氏体转变行为。MTT敏感性作为过程评估度量引入,将范式从传统的以缺陷为中心的框架转变为面向性能的优化。通过系统解耦能量输入在MTT过程中的作用,建立了一个参数依赖的通用汽化模型。结果表明,Ni损耗和MTT灵敏度取决于EL/v而不是EL,为~ 0.67 at。每kJ·s·m−2的Ni损失率为%,马氏体起始(MS)温度为~ 83 K时呈线性升高。微观结构分析证实EL/v控制熔池重叠、模态稳定性以及微观结构和相变均匀性。研究表明,输入能量密度的大小(如EL)决定了熔池的几何形状和致密化,而输入能量密度的方式(如归一化输入能量密度率,EL/v)决定了熔池动力学、元素汽化和微观结构演变。这一双重准则使在相同能量密度下观察到的质谱温度变化合理化,并使转化特征、残余应力和沉淀的预测控制成为可能。所提出的框架提供了具有优异拉伸伸长率(~ 22%)的NiTi组件,超过了大多数lpbf加工的富镍组件。此外,它的通用性在304L不锈钢和CuAlMn SMA中得到了验证,强调了它在NiTi SMA之外的适用性。该研究为工艺-熔池动力学-结构-性能相互作用提供了机制见解,并为LPBF参数设计提供了通用路线图,推进了工艺优化,超越了缺陷缓解,并通过熔池管理实现了精确的性能控制。
{"title":"Martensitic transformation sensitivity–driven processing roadmap for laser powder bed fusion of NiTi shape memory alloys: Paradigm shift from defect elimination to precise performance control","authors":"Dan Zheng ,&nbsp;Ruidi Li ,&nbsp;Jingtao Kang ,&nbsp;Tiechui Yuan ,&nbsp;Kefu Gan","doi":"10.1016/j.ijmachtools.2025.104352","DOIUrl":"10.1016/j.ijmachtools.2025.104352","url":null,"abstract":"<div><div>Laser powder bed fusion (LPBF) fabricated NiTi shape memory alloys (SMAs) fabricated to comparably high density using different processing parameters can exhibit significant differences in martensitic transformation temperature (MTT) (differing by &gt; 50 °C), altering their functional performance and making precise performance control challenging. Herein, we establish a simple but generalisable law, <strong><em>E</em><sub><em>L</em></sub></strong>/<strong><em>v</em></strong> (where <strong><em>E</em><sub><em>L</em></sub></strong> and <strong><em>v</em></strong> denote linear energy density and scan velocity, respectively), which governs densification and martensitic transformation behaviours in LPBF-processed Ni-rich NiTi SMAs. MTT sensitivity was introduced as a process evaluation metric, shifting the paradigm from conventional defect-centric frameworks toward performance-oriented optimisation. A parameter-dependent and universal vaporisation model is established by systematically decoupling the roles of energy input in MTT. Results demonstrate that Ni loss and MTT sensitivity depend on <strong><em>E</em><sub><em>L</em></sub></strong>/<strong><em>v</em></strong> rather than on <strong><em>E</em><sub><em>L</em></sub></strong>, with ∼0.67 at.% Ni loss per kJ·s·m<sup>−2</sup> and a linear increase in the martensite start (<strong><em>M</em><sub><em>S</em></sub></strong>) temperature of ∼83 K. Microstructural analyses confirm that <strong><em>E</em><sub><em>L</em></sub></strong>/<strong><em>v</em></strong> governs melt pool overlap, mode stability and microstructural and transformational homogeneity. It is revealed that the amount of input energy density (e.g. <strong><em>E</em><sub><em>L</em></sub></strong>) dictates melt pool geometry and densification, while the manner of input energy density (e.g. normalised input energy density rate, <strong><em>E</em><sub><em>L</em></sub></strong>/<strong><em>v</em></strong>) governs melt pool dynamics, elemental vaporisation and microstructure evolution. This dual-criterion rationalises the <strong><em>M</em><sub><em>S</em></sub></strong> temperature variability observed under identical energy densities and enables predictive control of transformation features, residual stress and precipitation. The proposed framework delivers NiTi components with superior tensile elongation (∼22 %), surpassing that of most LPBF-processed Ni-rich counterparts. Moreover, its universality is validated in 304L stainless steel and CuAlMn SMA, underscoring its applicability beyond NiTi SMAs. This study offers mechanistic insights into processing–melt pool dynamics–structure–property interactions and offers a universal roadmap for LPBF parameter design, advancing process optimisation beyond defect mitigation and enabling precise performance control through melt pool management.</div></div>","PeriodicalId":14011,"journal":{"name":"International Journal of Machine Tools & Manufacture","volume":"214 ","pages":"Article 104352"},"PeriodicalIF":18.8,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145657706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Surface and subsurface evolution mechanism in continuous wave laser ablation process of Cf/SiC ceramic matrix composites: A multiscale investigation Cf/SiC陶瓷基复合材料连续波激光烧蚀过程中的表面和亚表面演化机制:多尺度研究
IF 18.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2025-11-26 DOI: 10.1016/j.ijmachtools.2025.104354
Dongdong Xu , Tiancheng Ai , Guojian Yang , Shusong Zan , Zhirong Liao
Due to the excellent material properties, ceramic matrix composites (CMCs) are increasingly favored in aerospace and other high-performance applications. As the industry advances, both the reinforcement and matrix materials tend to be more difficult to machine. Laser-based processing methods are becoming increasingly popular. However, the underlying mechanisms and the formation of surface integrity in such complex materials remain unclear. At present, the overall ablation process of complex CMCs has not been studied. To address these gaps, this study investigates the surface integrity induced by laser ablation and its underlying mechanisms of CMCs. The results reveal that post-ablation surface morphologies vary significantly across different regions of Cf/SiC CMCs—those with vertically oriented fibers, where the height is relatively high, and those with horizontally oriented fibers, where the height is comparatively low. At a scanning speed of 400 mm/min, the laser energy corresponding to a power of 3 kW can be regarded as the threshold between rough and fine machining. It was further clarified that the spherical particles formed on the ablated surface were composed of elemental silicon rather than the commonly assumed oxides. The surface region exhibited a loose four-layer structure consisting of silica, elemental silicon, silicon carbide, and a pyrolytic carbon layer. In addition, a typical multi-layered surface structure—arising from the superior thermal conductivity of the fibers—was also observed on the surfaces of fibers located within the subsurface region of the workpiece. A model of the temperature distribution was established to elucidate how differences in thermal conduction induced by fiber orientation influence the ablated surface morphology of the CMC. Overall, these findings comprehensively explain the ablation process, surface integrity evolution, and underlying mechanisms of CMCs subjected to laser ablation.
陶瓷基复合材料由于其优异的材料性能,在航空航天和其他高性能应用领域受到越来越多的青睐。随着工业的发展,增强材料和基体材料的加工难度越来越大。基于激光的加工方法正变得越来越流行。然而,这种复杂材料的潜在机制和表面完整性的形成仍不清楚。目前,尚未对复合cmc的整体烧蚀过程进行研究。为了解决这些空白,本研究探讨了激光烧蚀诱导cmc的表面完整性及其潜在机制。结果表明,Cf/SiC复合材料不同区域的烧蚀后表面形貌存在显著差异——垂直取向纤维区高度较高,水平取向纤维区高度较低。在扫描速度为400mm /min时,对应功率为3kw的激光能量可视为粗加工与精加工之间的阈值。进一步澄清了在烧蚀表面形成的球形颗粒是由元素硅组成的,而不是通常假设的氧化物。表面呈现松散的四层结构,由二氧化硅、单质硅、碳化硅和热解碳层组成。此外,在位于工件亚表面区域的纤维表面上也观察到典型的多层表面结构-由纤维的优越导热性引起。建立了温度分布模型,阐明了纤维取向引起的热传导差异对CMC烧蚀表面形貌的影响。总的来说,这些发现全面地解释了激光烧蚀cmc的烧蚀过程、表面完整性演变和潜在机制。
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引用次数: 0
Model-based design of strength–toughness synergy for additively manufactured layered heterostructured metallic materials 基于模型的增材制造层状异质结构金属材料强韧性协同设计
IF 18.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2025-11-19 DOI: 10.1016/j.ijmachtools.2025.104353
Jianglong Wang , Haihong Huang , Yu Kong , Zhifeng Liu
The inherent contradiction between strength and toughness in additively manufactured metallic materials can be coordinated through a layered heterostructured design, which tailors the distribution of two dissimilar materials. To quantitatively describe the strength and toughness of heterostructured metallic materials, a strength–toughness coupling mechanical model for layered heterostructures was established according to the weight function principle in this research. On this basis, a laser interface remelting (LIR) process was initially developed; then, after evaluating the metallurgical compatibility, the layered heterostructures of IN718/316L bimetallic materials were fabricated by the laser-directed energy deposition (LDED) technology. The results manifested that this LIR process could synthesize composition transition zones in situ, ensuring a controllable bonding quality for the heterostructured interface. The modelling also exhibited that the toughness of heterogeneous metal layered structures decreased with the increase in strength, and there was an emblematic trade-off between strength and toughness. Additionally, the two toughening mechanisms were discussed in terms of hindering crack nucleation and shielding strain spread. Furthermore, it was found that the matching form of the layer thickness with “more hard and less soft” could induce sub-critical cracks on the surface, and activate the extra strengthening potential. Ultimately, a new approach to determining the layer thickness ratio of layered heterostructures by the modelling calculation was proposed, and the process feasibility of additive manufacturing following this model-based design was also confirmed via a case study. This method of synergistic regulation could provide effective guidance for the on-demand optimization of strength–toughness aimed at heterostructured metallic materials.
增材制造金属材料的强度和韧性之间的内在矛盾可以通过分层异质结构设计来协调,从而定制两种不同材料的分布。为了定量描述异质结构金属材料的强度和韧性,本研究根据权函数原理建立了层状异质结构的强度-韧性耦合力学模型。在此基础上,初步开发了激光界面重熔(LIR)工艺;然后,通过金相相容性评价,采用激光定向能沉积(LDED)技术制备了IN718/316L双金属材料的层状异质结构。结果表明,该工艺可以原位合成化合物过渡区,保证了异质结构界面的键合质量可控。该模型还表明,非均质金属层状结构的韧性随着强度的增加而降低,并且在强度和韧性之间存在象征性的权衡。此外,从阻碍裂纹形核和屏蔽应变扩散两方面讨论了两种增韧机制。此外,发现“多硬少软”的层厚匹配形式可诱发表面亚临界裂纹,激活额外强化电位。最后,提出了一种通过建模计算确定层状异质结构层厚比的新方法,并通过实例验证了基于模型设计的增材制造工艺的可行性。这种协同调节方法可以为针对异质结构金属材料的强度-韧性按需优化提供有效的指导。
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引用次数: 0
AI-powered semiconductor wafer fabrication: A manufacturing paradigm shift 人工智能驱动的半导体晶圆制造:制造模式的转变
IF 18.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2025-11-07 DOI: 10.1016/j.ijmachtools.2025.104345
Guanwei He , Qingqing Huang , Xinhao Li , Libo Zhou , Miao Yang , Yadan Luo , Marian Wiercigroch , Han Huang
Artificial intelligence (AI) is reshaping the landscape of modern manufacturing by enabling intelligent, adaptive, and increasingly autonomous production systems. In high-end manufacturing processes, persistent challenges such as complex machine-tool dynamics, variability in equipment performance, and environmental instabilities hinder consistent quality and high efficiency. These challenges are further amplified in advanced manufacturing domains, particularly in semiconductor wafer fabrication, which demands ultra-high precision to be attained. AI offers powerful solutions to these challenges through its capability in real-time decision making, data driving modelling, and predictive analysis of manufacturing processes. By learning from vast datasets generated during manufacturing, AI systems can identify working patterns, optimize process parameters, detect anomalies, and guide autonomous control strategies. These advantages position AI as a key enabler for enhancing process understanding, ensuring quality assurance, and accelerating innovation in fabrication technologies. Semiconductor wafer fabrication is the cornerstone of modern electronics manufacturing, serving as the foundation process for integrated circuits production. This article reviews the transformative role of AI in wafer fabrication, highlighting its principles, applications, and prospects. Key AI technologies such as deep learning, reinforcement learning, and generative algorithms that have been widely adopted in wafer fabrication are surveyed. Special attention is given to their deployment across critical fabrication procedures including crystal growth, ingot slicing and ultraprecision machining. The review further presents state-of-the-art research and industrial implementations of AI in these domains, showcasing how intelligent models can be employed in quality prediction, regime classification, process optimization, and system control. Finally, emerging trends and future perspectives aimed at fostering more practical, deeply integrated, and robust AI applications across the manufacturing ecosystem are discussed, paving the way toward fully autonomous and self-optimizing future manufacturing processes.
人工智能(AI)通过实现智能、自适应和日益自主的生产系统,正在重塑现代制造业的格局。在高端制造过程中,持续的挑战,如复杂的机床动力学、设备性能的可变性和环境的不稳定性,阻碍了始终如一的质量和高效率。这些挑战在先进制造领域进一步放大,特别是在半导体晶圆制造领域,这需要达到超高的精度。人工智能通过其实时决策、数据驱动建模和制造过程预测分析的能力,为这些挑战提供了强大的解决方案。通过学习制造过程中产生的大量数据集,人工智能系统可以识别工作模式、优化工艺参数、检测异常并指导自主控制策略。这些优势使人工智能成为增强工艺理解、确保质量保证和加速制造技术创新的关键推动者。半导体晶圆制造是现代电子制造业的基石,是集成电路生产的基础工艺。本文综述了人工智能在晶圆制造中的变革作用,重点介绍了其原理,应用和前景。综述了在晶圆制造中广泛采用的关键人工智能技术,如深度学习、强化学习和生成算法。特别关注它们在关键制造过程中的部署,包括晶体生长,铸锭切片和超精密加工。本文进一步介绍了人工智能在这些领域的最新研究和工业实现,展示了智能模型如何应用于质量预测、状态分类、过程优化和系统控制。最后,讨论了旨在促进整个制造生态系统中更实用、深度集成和强大的人工智能应用的新兴趋势和未来前景,为实现完全自主和自我优化的未来制造流程铺平了道路。
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引用次数: 0
Machine learning applications in welding processes: Progresses and opportunities 机器学习在焊接工艺中的应用:进展与机遇
IF 18.8 1区 工程技术 Q1 ENGINEERING, MANUFACTURING Pub Date : 2025-11-03 DOI: 10.1016/j.ijmachtools.2025.104344
Peihao Geng , Yujun Xia , Zhiqiao Dong , Boxuan Men , Bo Pan , Chenhui Shao , Yongbing Li , Jingjing Li
The increasing demand for intelligent and autonomous manufacturing has driven the integration of machine learning (ML) into modern welding processes. Owing to its ability to model nonlinear and cross-scale interactions and extract critical features from complex, high-dimensional data, ML is rapidly transforming the design, monitoring, and evaluation of welding processes. Based on this, the paper systematically reviews research progress in ML for four representative welding processes (arc, laser, resistance and friction stir welding) over the past decade. First, typical welding tasks are categorized into three domains: pre-weld design, in-process monitoring, and post-weld quality assessment. It then elaborates on the types of welding data used and their input-output relationships across different tasks and analyzes the architecture and algorithmic characteristics of mainstream ML models. Cross-process comparison reveals that the physical nature of each welding process determines the focus of ML research, model selection, and performance metrics. The study quantitatively compares the task-specific metrics of various models and presents successful industrial application cases. Despite significant progress, challenges persist in constructing high-quality and standardized datasets, improving model interpretability and generalization, and achieving robust real-time control in dynamic industrial environments. Based on the summarized emerging challenges, the perspectives on further development direction of applying ML in intelligent welding are also discussed.
对智能和自主制造日益增长的需求推动了机器学习(ML)与现代焊接工艺的集成。由于它能够模拟非线性和跨尺度的相互作用,并从复杂的高维数据中提取关键特征,机器学习正在迅速改变焊接过程的设计、监测和评估。在此基础上,系统综述了近十年来四种典型焊接工艺(电弧焊、激光焊、电阻焊和搅拌摩擦焊)在机器学习方面的研究进展。首先,典型的焊接任务分为三个领域:焊前设计、焊中监测和焊后质量评估。然后详细阐述了所使用的焊接数据类型及其跨不同任务的输入输出关系,并分析了主流ML模型的架构和算法特征。跨工艺比较表明,每个焊接工艺的物理性质决定了机器学习研究、模型选择和性能指标的重点。该研究定量地比较了各种模型的特定任务度量,并给出了成功的工业应用案例。尽管取得了重大进展,但在构建高质量和标准化数据集、提高模型可解释性和泛化以及在动态工业环境中实现鲁棒实时控制方面仍然存在挑战。在总结当前面临的挑战的基础上,对机器学习在智能焊接领域的进一步发展方向进行了展望。
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引用次数: 0
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International Journal of Machine Tools & Manufacture
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