Additive manufacturing最新文献

{"title":"An efficient and uncertainty-aware reinforcement learning framework for quality assurance in extrusion additive manufacturing","authors":"Xiaohan Li,&nbsp;Sebastian W. Pattinson","doi":"10.1016/j.addma.2025.104912","DOIUrl":"10.1016/j.addma.2025.104912","url":null,"abstract":"<div><div>Defects in extrusion additive manufacturing remain common despite its prevalent use. While numerous AI-based quality assurance approaches have been proposed, the dynamic nature of printing processes often causes deterministic models to lose robustness and, in some cases, fail entirely in new or slightly altered environments. This work introduces an agent that adjusts flow rate and temperature in real-time to optimize control while addressing bottlenecks in training efficiency and uncertainty management. A vision-based uncertainty quantification module generates probabilistic distributions from classified extrusion states, which are integrated with a deep Q-learning controller. While the underlying networks are deterministic, the evolving distributions introduce adaptability to the decision-making process. The controller learns optimal asynchronous actions in a simulation calibrated to vision accuracy and trained with progressively tightened elliptically shaped rewards that account for parameter coupling. With zero-shot learning, the agent bridges the sim-to-real gap and reliably corrects 21 tests across three extrusion error levels—slight, moderate, and severe—with average convergence steps of <span><math><mrow><mn>40</mn><mo>.</mo><mn>67</mn><mo>±</mo><mn>17</mn><mo>.</mo><mn>41</mn></mrow></math></span>, <span><math><mrow><mn>44</mn><mo>.</mo><mn>00</mn><mo>±</mo><mn>13</mn><mo>.</mo><mn>56</mn></mrow></math></span>, and <span><math><mrow><mn>49</mn><mo>.</mo><mn>11</mn><mo>±</mo><mn>17</mn><mo>.</mo><mn>91</mn></mrow></math></span>, respectively. The modest increase in convergence steps and stable standard deviations across error levels underscore the controller’s effectiveness and robustness. Beyond extrusion, this scalable framework supports practical AI-driven quality assurance across various additive manufacturing.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"110 ","pages":"Article 104912"},"PeriodicalIF":11.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144893267","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}

{"title":"Spatiotemporal monitoring and control for foam additive manufacturing processes of thermoplastics","authors":"Zhaowei Zhou,&nbsp;Kaicheng Ruan,&nbsp;Donghua Zhao,&nbsp;Xuguang Xu,&nbsp;Ziwen Chen,&nbsp;Yi Xiong","doi":"10.1016/j.addma.2025.104949","DOIUrl":"10.1016/j.addma.2025.104949","url":null,"abstract":"<div><div>Foam Additive Manufacturing (Foam-AM) offers a novel approach to fabricating architected structures with tunable density by leveraging in-situ foaming. However, precise control of the foaming process remains challenging due to the complex interplay of multiple process parameters. This complexity has limited the broader adoption of Foam-AM in applications such as packaging, protective gear, automotive components, and beyond. To address these challenges, this study proposes a novel spatial-temporal monitoring and control method using a multi-sensor platform to optimize the performance and geometry of Foam-AM. The platform integrates a thermal camera and positioning encoders to monitor the temperature field and speed distribution, identifying bead interference and speed variations as the primary causes of foaming defects. Additionally, a line laser profiler is used to measure sample’s spatial information, complemented by extruder encoder data for in-situ density estimation. This in-situ approach facilitates high-throughput data acquisition, forming the basis for a process-performance model developed using Invertible Neural Networks (INN). Leveraging the INN model, two major advancements are achieved: (1) off-line control strategies effectively minimize bead interference, ensuring consistent density and geometric precision; and (2) localized foaming defects, especially in regions with rapid speed changes, are accurately identified and addressed through real-time parameter adjustments, significantly improving overall print quality.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"110 ","pages":"Article 104949"},"PeriodicalIF":11.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144932611","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}

{"title":"High speed thermal imaging and modeling of laser powder bed fusion manufactured WC–Ni cemented carbides","authors":"Guadalupe Quirarte,&nbsp;Alexander J. Myers,&nbsp;Alexander Gourley,&nbsp;Craig M. Weeks,&nbsp;B. Reeja-Jayan,&nbsp;Jack Beuth,&nbsp;Jonathan A. Malen","doi":"10.1016/j.addma.2025.104913","DOIUrl":"10.1016/j.addma.2025.104913","url":null,"abstract":"<div><div>Cemented carbides such as cemented tungsten carbide (WC) are known for their use in resilient wear-resistant applications where hardness and thermal stability are imperative. They are composed of carbide particles embedded in a metal binder. Laser Powder Bed Fusion (L-PBF) is a favorable method to form cemented carbides into complex geometries, but composites pose unique challenges relative to metals typically processed by L-PBF. Resolving the melt pool temperature distributions in L-PBF is key to understanding the underlying physics of the fusion process. Using a two-color thermal imaging method, melt pool thermal maps of WC_0.83-Ni_0.17 were captured with linear energy densities ranging from 500–1750 J/m with and without powder. WC_0.83-Ni_0.17 melt pools exhibit temperatures above 4000 K, which can lead to the generation of other WC phases. Compared to more common L-PBF materials such as 316L stainless steel (SS), WC_0.83-Ni_0.17 melt pools reach higher temperatures. Our direct measurements find that the thermal conductivity of WC_0.83-Ni_0.17 is 30 W/m-K at 300 K, which is higher than the thermal conductivity of 316L SS and suggests that other heat transfer limitations must cause the elevated melt pool temperatures. A FLOW-3D CFD model based on the composite properties was compared to both the melt pool centerline temperatures and width measurements of the samples fabricated by L-PBF. The simulations indicate that specifying the onset of fluidity is key to reproducing the high temperatures observed experimentally. Although Ni has a melting point of 1728 K, the simulations do not match experiments unless the onset of fluidity is set at the melting point of WC (3143 K). Within FLOW-3D, the onset of fluidity is controlled by the critical solid fraction, which is a uniquely important parameter for simulating composite materials.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"110 ","pages":"Article 104913"},"PeriodicalIF":11.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144852416","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}

{"title":"A novel dual-phase Bayesian estimation and multi-task learning method for process optimization for reducing lack-of-fusion defects during laser powder bed fusion","authors":"Yusheng Chen ,&nbsp;Dongdong Gu ,&nbsp;Keyu Shi ,&nbsp;Yanze Li ,&nbsp;Wenxin Chen","doi":"10.1016/j.addma.2025.104926","DOIUrl":"10.1016/j.addma.2025.104926","url":null,"abstract":"<div><div>In metal additive manufacturing, lack-of-fusion is one of the most critical porosity defects. Its complex formation mechanism makes the modeling process highly challenging. While existing researches have focused on high-fidelity simulations, high-performance predictions and process map based on single-track scenarios, the actual printing process requires consideration of the interlapping and stacking of multi-layer and multi-track melt pools. This significantly increases the computational cost of high-fidelity simulations and the computational error of traditional analytical models. In this study, we developed the dual-phase Bayesian estimation and multi-task learning (Dual-BE&amp;ML) method. This approach innovatively “teaches” the machine learning models to account for system error and uncertainty by incorporating physical laws. It also demonstrates enhanced fitting capabilities for the melt pool width. Using a set of dimensionless numbers, we constructed a sensitivity map for inter-layer lack-of-fusion porosity in laser powder bed fusion of 316 L stainless steel. This allows us to accurately avoid process regions prone to inter-layer lack-of-fusion porosity during the process optimization. The results show that when the ratio of melt pool depth to layer thickness exceeds 1.62 and the ratio of hatch spacing to melt pool width is less than 0.76, the inter-layer lack-of-fusion porosity disappears. This not only confirms the reliability of our approach but also provides important guidance for accelerating process optimization and product design.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"110 ","pages":"Article 104926"},"PeriodicalIF":11.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144852418","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}

{"title":"Combinatorial mapping of high-temperature oxidation in SS316L–IN718 dissimilar alloys printed by laser-directed energy deposition","authors":"Mustafa Kas ,&nbsp;Oguzhan Yilmaz ,&nbsp;Wei Xiong","doi":"10.1016/j.addma.2025.104932","DOIUrl":"10.1016/j.addma.2025.104932","url":null,"abstract":"<div><div>Functionally graded materials (FGMs) enable the investigation of oxidation behavior across variable compositions, allowing efficient evaluation of how gradual changes in alloy content influence high-temperature performance. In this study, stainless steel 316 L (SS316L) and Inconel 718 (IN718) were combined to produce both a nine-layer gradient FGM and a bimetallic sample via laser-directed energy deposition (LDED). After prolonged high-temperature exposure to 500 h at 850 °C in air, the effects of composition and interface design on oxidation resistance were systematically examined using localized analysis of oxide scale formation and microstructural evolution. A clear improvement in oxidation resistance and oxide adhesion was observed above a threshold of 30 wt.% IN718 in the FGM with gradient composition. At the same time, the abrupt transition in bimetallic print did not result in severe spallation due to interdiffusion at the interface. The results further reveal that an intermediate IN718 region (10–20 wt.%) is prone to solidification cracks that promote internal oxidation, and that, in the IN718-rich areas (70–100 wt.%), microhardness decreases after oxidation due to the dissolution of strengthening phases (γ'/γ'') and grain coarsening. This combinatorial and composition-sensitive approach, utilizing FGMs, offers valuable new insights for designing oxidation-resistant materials for high-temperature applications.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"110 ","pages":"Article 104932"},"PeriodicalIF":11.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144864434","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}

{"title":"Novel 3D printed BaTiO3-based ceramics with high PTC effect via vat photopolymerization and vacuum infiltration","authors":"Wen Zheng ,&nbsp;Xi Chen ,&nbsp;Bingxiao Xue ,&nbsp;Tianwen Dong ,&nbsp;Kaixin Chen ,&nbsp;Wei Luo ,&nbsp;Qiuyun Fu","doi":"10.1016/j.addma.2025.104945","DOIUrl":"10.1016/j.addma.2025.104945","url":null,"abstract":"<div><div>Structural modification is a feasible and effective method to improve the heating efficiency and uniformity of BaTiO₃-based ceramics with positive temperature coefficient (PTC) of resistance. However, modifying three-dimensional (3D) structures by traditional manufacturing methods is very challenging due to the inhomogeneous mixing of raw materials and high mold dependency. Additionally, the realization of complex structures using emerging vat photopolymerization (VPP) technology is limited by the poor curing properties of leaded PTC ceramic slurry. Herein, this study presents an innovative approach of combining VPP technology with vacuum infiltration (VI) process for fabricating high-performance PTC ceramics. Notably, the introduction of soluble starch significantly enhances the curing depth and printability of PTC ceramic slurry. Meanwhile, silica nanoparticles in silica sols are infiltrated into 3D printed green bodies to improve the electrical properties of PTC ceramics. At optimal soluble starch content and silica concentration, a lower room temperature resistivity (ρ=207 Ω·cm) and a higher temperature coefficient of resistance (α_0–15=25.14 %/℃) are obtained in printed PTC ceramics compared to dry pressed PTC ceramics (ρ=301 Ω·cm, α_0–15=19.32 %/℃). Therefore, this work provides a novel technological strategy for fabricating high-performance PTC ceramics with desirable structures and can promote the wide application of PTC heating elements.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"110 ","pages":"Article 104945"},"PeriodicalIF":11.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144996417","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}

{"title":"Ultrasound-assisted 3D printing of glass fiber-reinforced polymers: Hierarchical fiber alignment and property enhancement","authors":"Linhao Guo ,&nbsp;Tianyu Yu ,&nbsp;Jiahui Yao ,&nbsp;Yikai Ma ,&nbsp;Mingjun Chen","doi":"10.1016/j.addma.2025.104940","DOIUrl":"10.1016/j.addma.2025.104940","url":null,"abstract":"<div><div>Particle-reinforced polymers attracted great attention in aerospace and automotive, where fiber alignment plays a critical role. Conventional manufacturing methods and magnetic/electric field-based fiber alignment techniques require certain filler geometries and electromagnetic properties, severely limiting their applicability. In this study, a novel ultrasound-assisted stereolithography additive manufacturing technique was developed, exploiting acoustic radiation forces generated from the acoustic property mismatches between fiber fillers and polymer matrix, manipulating multidirectional alignment of glass fibers and graphene particles during 3D printing. A method to quantify the fiber alignment level was developed and profound effects of ultrasonic driving voltage and fiber mass fraction on the fiber alignment rates were clarified, enabling up to 93.44 % orientation rate within the target angular range. Tensile testing of five fiber-aligned specimens revealed that the 0° unidirectionally aligned sample exhibited superior performance, with tensile strength increasing by 46.29 % compared to random-aligned samples and by 91.43 % compared with pure polymers. By integrating a rotating platform with the acoustic radiation force field, layer-by-layer fiber angle control was realized, facilitating the fabrication of complex 3D structures—including bionic flowers, character patterns, and intricate geometries. The developed technique was further validated using spherical nickel-coated graphite particles, attaining a 90.20 % orientation rate, expanding its potential for aligning particles with different geometries during 3D printing of particle-reinforced polymers.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"110 ","pages":"Article 104940"},"PeriodicalIF":11.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144996418","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}

{"title":"Correlation between microstructure and anisotropic mechanical behavior of Fe-riched FeCoCrNiMn high-entropy alloy prepared via laser powder bed fusion: Experimental and crystal plasticity finite element analysis","authors":"Tao Wang ,&nbsp;Chen Li ,&nbsp;Yixiong Hu ,&nbsp;Hongyu Chen ,&nbsp;Tiwen Lu ,&nbsp;Mina Zhang ,&nbsp;Feng Yu ,&nbsp;Yang Liu ,&nbsp;Yonggang Wang","doi":"10.1016/j.addma.2025.104927","DOIUrl":"10.1016/j.addma.2025.104927","url":null,"abstract":"<div><div>Laser powder bed fusion (LPBF) of metals often have anisotropic microstructure, e. g. heterogeneous grain structure and preferential crystalline texture, both of which affect the mechanical properties and deformation behavior significantly. To clarify the contributions of grain morphology and crystalline texture to the anisotropy of mechanical properties, this paper investigates the correlation between the anisotropic microstructure and mechanical properties of Fe₆₀(CoCrNiMn)₄₀ high-entropy alloys (HEAs) prepared via LPBF by combining experimental and crystal plasticity finite element (CPFE) analyses. The results indicate that significant microstructural anisotropy is produced in the as-built samples along the building direction, with the samples characterized by columnar grains (aspect ratio of ∼0.35) and a strong texture (texture intensity of ∼15.7) along the &lt; 001 &gt; direction. Samples perpendicular to the building direction (HS0) exhibit higher tensile strength (∼590 MPa) and lower fracture strain (∼50 %), while samples parallel to the building direction (HS90) has reduced strength (∼500 MPa) and augmented fracture strain (∼80 %). During early-stage deformation, anisotropy is mainly generated by the cooperative effect of the anisotropic grain morphology and crystalline texture. In the late stage, the &lt; 110 &gt; to &lt; 111 &gt; texture change in the HS0 via dislocation-driven rotation activates the deformation twins with high Taylor factor, thus enhancing dislocation storage for sustained strengthening. While the stable &lt; 100 &gt; texture in the HS90 suppresses deformation twinning, promotes dynamic recovery-driven dislocation annihilation, and thus weakening the strain strengthening.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"110 ","pages":"Article 104927"},"PeriodicalIF":11.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144831414","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}

{"title":"DED bead geometry and profile prediction with multimodal spatio-temporal neural networks","authors":"Wenze Zhang ,&nbsp;Yichen Wang ,&nbsp;Yuanzhi Chen ,&nbsp;Xiaoke Deng ,&nbsp;Yihe Wang ,&nbsp;Molong Duan ,&nbsp;Pengcheng Hu ,&nbsp;Kai Tang","doi":"10.1016/j.addma.2025.104952","DOIUrl":"10.1016/j.addma.2025.104952","url":null,"abstract":"<div><div>Accurate prediction of bead geometry in multi-axis directed energy deposition (DED) remains challenging due to dynamic interactions between process parameters, positional dynamics, and rapid melt pool evolution. This study introduces MST-Net, a multimodal spatio-temporal neural network, alongside a comprehensive dataset of 1.2 million samples from a five-axis DED system, integrating co-axial melt pool images, control parameters, positional variables, and high-resolution point cloud labels. MST-Net employs a hierarchical architecture to fuse spatio-temporal features, achieving state-of-the-art prediction accuracy with a mean intersection over union (mIoU) of 0.93 for cross-sectional profiles and mean average precision (mAP) of 0.95 for bead dimensions. Ablation studies reveal melt pool images as the most critical input modality, while positional data governs peak localization. Temporal analysis shows asymmetric weighting of historical (look-back) and future (look-ahead) contexts optimizes predictions, with 201-step sequences balancing accuracy and computational efficiency at 116 FPS, which provides a foundation for real-time control given the predictive model. Transfer learning experiments highlight MST-Net’s adaptability, maintaining 0.95 mAP with only 10 % of training data for new printing path geometries. By addressing data scarcity and spatio-temporal complexity, this work advances predictive modeling for multi-axis DED, offering a robust framework for real-time process control in industrial applications. The dataset and model are publicly released to foster innovation in metal additive manufacturing.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"110 ","pages":"Article 104952"},"PeriodicalIF":11.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144996280","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}

{"title":"Phase-separation-driven cracking in additive manufacturing of Ni-Cu alloy systems","authors":"Andaç Özsoy ,&nbsp;Steve Gaudez ,&nbsp;William A. Hearn ,&nbsp;Antonios Baganis ,&nbsp;Zoltán Hegedüs ,&nbsp;Yunhui Chen ,&nbsp;Alexander Rack ,&nbsp;Roland E. Logé ,&nbsp;Steven Van Petegem","doi":"10.1016/j.addma.2025.104950","DOIUrl":"10.1016/j.addma.2025.104950","url":null,"abstract":"<div><div>This study investigates the cracking mechanism in additive manufacturing of Ni-Cu multi-material combinations using <em>operando</em> X-ray diffraction and imaging experiments during laser powder-bed fusion (L-PBF) of CuCrZr and IN625. It is shown that liquid immiscibility between the two alloy systems stems from the interaction between Cu and the alloying elements in IN625, causing both Cu-rich and Ni-rich liquids to form with different freezing ranges. Consequently, solidification cracking takes place due to the large solidification range where the Ni-rich solid and Cu-rich liquid co-exist. Guided by thermodynamic calculations, it was identified that the highest crack susceptibility occurs between 20 and 40 wt% CuCrZr-IN625, which was further validated by printing mixtures of the two alloys in different ratios. <em>Operando</em> X-ray imaging and scanning electron microscopy characterization revealed that the cracking occurred during the terminal stage of solidification. It was observed that the columnar grains of the Ni-rich primary solid separate into cracks, where Cu-rich liquid regions persist over a wide temperature range as the solidification of these regions begin significantly later. It was concluded that the mechanism of cracking explained in this study could be extended to other Cu-Ni alloy combinations containing elements that induce immiscibility when mixed with Cu during fusion-based processing methods.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"110 ","pages":"Article 104950"},"PeriodicalIF":11.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144932614","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}