Additive manufacturing最新文献

{"title":"Laser induced keyhole reshaping in laser powder bed fusion of aluminum alloy","authors":"Shiwei Hua,&nbsp;Yangyi Pan,&nbsp;Qinghu Guo,&nbsp;Guoqing Zhang,&nbsp;Fang Dong,&nbsp;Chen Zhang,&nbsp;Sheng Liu","doi":"10.1016/j.addma.2025.104993","DOIUrl":"10.1016/j.addma.2025.104993","url":null,"abstract":"<div><div>Conventional powder bed fusion by laser beam (PBF-LB) utilizing high beam energy often generates unstable keyhole dynamics, leading to pore formation and compromised mechanical performance, especially for aluminum alloys. To address this limitation, we propose a novel Laser Keyhole Reshaping technology enhanced PBF-LB (LKRS-PBF-LB) strategy, integrating pulsed and continuous lasers to stabilize keyhole morphology. Experimental and computational analyses reveal that pulsed-laser-induced shockwaves dynamically reverse keyhole wall pressures, expanding the keyhole diameter (43→58 μm) and stabilizing its shape (J→I transition), thereby reducing porosity by an order of magnitude (3.63 %→0.14 %). Keyhole stabilization concurrently suppresses spattering by mitigating vapor pressure fluctuations and lowering peak pressures. Numerical simulations demonstrate enhanced melt flow and attenuated thermal gradients, promoting columnar-to-equiaxed transition and grain refinement. The LKRS-processed samples exhibited simultaneous enhancement in tensile strength (59.6 % increase) and ductility (0.78 %→2 %), attributable to porosity elimination and grain refinement. This approach introduces a novel keyhole reshaping technique that mitigates intrinsic instability, thereby enabling new avenues for advanced additive manufacturing with enhanced performance.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"111 ","pages":"Article 104993"},"PeriodicalIF":11.1,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145324499","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":"Efficient part-scale thermal modeling of laser powder bed fusion via a multilevel finite element framework","authors":"S.M. Elahi,&nbsp;J.P. Leonor,&nbsp;R.Y. Wu,&nbsp;G.J. Wagner","doi":"10.1016/j.addma.2025.104897","DOIUrl":"10.1016/j.addma.2025.104897","url":null,"abstract":"<div><div>In this work, we show that a multilevel finite element algorithm previously demonstrated for linear problems can, using a novel time integration method and other improvements, give efficient and accurate part-scale simulations of real additive manufacturing processes. The GPU-optimized multilevel finite element framework (GO-MELT) uses multiple moving meshes to simulate thermal behavior in laser powder bed fusion (LPBF) processes; fixed mesh sizes and data structures allow straightforward implementation of this algorithm on GPU hardware. Building on this framework, we introduce key advancements including G-code parsing for complex laser paths, temperature-dependent material properties with distinct definitions for powder, solid, and fluid states, and time step subcycling across levels to manage computational loads effectively. These improvements enable precise simulation across the different material states encountered in LPBF while minimizing computational cost. Verification studies show that first-order time convergence is preserved even in the presence of nonlinearities, and the fidelity of the enhanced framework is validated against well-established experimental benchmarks, including in-situ X-ray diffraction data for Hastelloy-X and time above melting measurements from the NIST AM-Bench cantilever model. Computational tests demonstrate that our approach achieves an average execution time of 1.8 ms per time step, enabling a high-fidelity thermal simulation of 350 million time steps to be solved on a single GPU in 7.3 days, comparable to published simulations on much larger parallel systems. An analysis of thermal decay times can be used to further reduce simulation time by limiting simulation to time-points of interest. These results underscore the potential of this algorithm for advancing real-time process optimization and part quality improvement in LPBF.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"109 ","pages":"Article 104897"},"PeriodicalIF":11.1,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144738457","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 integrated forming process for fabricating complex thin-walled AlSi10Mg alloy tubular parts via laser powder bed fusion and hot gas forming","authors":"Jiangkai Liang ,&nbsp;Gaoning Tian ,&nbsp;Quan Gao ,&nbsp;Wei Du ,&nbsp;Yanli Lin ,&nbsp;Zhubin He","doi":"10.1016/j.addma.2025.104936","DOIUrl":"10.1016/j.addma.2025.104936","url":null,"abstract":"<div><div>Currently, both additive manufacturing technologies and fluid pressure forming process face significant challenges in fabricating large-sized, complex thin-walled metal components. To address these challenges, this paper introduces a novel integrated forming process that utilizes laser powder bed fusion (LPBF) preforming and hot gas forming (HGF). This method employs LPBF technology to fabricate near-net-shape preforms, which are subsequently subjected to HGF treatment to realize micro-scale precise deformation. This study systematically investigates the performance of AlSi10Mg alloy thin-walled preforms prepared by LPBF, along with the characteristics of the formed parts following the HGF process. Furthermore, subsequent heat treatment protocols are employed to improve the microstructural properties of the formed parts. Compared to the direct LPBF technology, this method exhibits marked enhancements in dimensional accuracy and density of the fabricated parts, effectively controlling dimensional deviations and substantially reducing porosity. Ultimately, the process culminates in the fabrication of complex thin-walled AlSi10Mg alloy parts characterized by a superior microstructure and mechanical properties. Specifically, the formed parts, measuring 165 mm with a wall thickness of 1.2 mm, achieve a dimensional accuracy of ± 0.24 mm and a maximum wall thickness reduction rate of less than 14.2 %, while attaining an impressive density of 99.93 %. Additionally, the parts exhibit excellent uniformity concerning the distribution and morphology of the precipitated phases, along with the shape and structure of the grains. Following solution heat treatment, the formed parts exhibited tensile strengths of 282 MPa at room temperature and 186 MPa at 230 °C, accompanied by elongations of 15.9 % and 11.7 %, respectively. This favorable combination of strength and ductility renders these materials well-suited for engineering applications that demand high overall mechanical performance. However, aging heat treatment after solution treatment resulted in a significantly improved of the mechanical properties. The tensile strengths increased to 350 MPa at room temperature and 201 MPa at 230°C, while the elongations were concurrently reduced to 6.9 % and 10.1 %, respectively. Such a property profile makes these materials particularly suitable for specialized applications where high strength is prioritized over ductility. The feasibility of LPBF-prepared preforms via the subsequent HGF process was systematically confirmed, thereby establishing a foundational basis for the prospective application of this integrated forming methodology.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"110 ","pages":"Article 104936"},"PeriodicalIF":11.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144864432","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":"Radiometric temperature measurement for metal additive manufacturing via temperature emissivity separation","authors":"Ryan W. Penny,&nbsp;A. John Hart","doi":"10.1016/j.addma.2025.104904","DOIUrl":"10.1016/j.addma.2025.104904","url":null,"abstract":"<div><div>Emission of blackbody radiation from the meltpool and surrounding area in laser powder bed fusion (LPBF) makes this process visible to a range of optical monitoring instruments intended for online process and quality assessment. Yet, these instruments have not proven capable of reliably detecting the finest flaws that influence LPBF component mechanical performance, limiting their adoption. One hindrance lies in interpreting measurements of radiance as temperature, despite the physical link between these variables being readily understood as a combination of Planck’s Law and spectral emissivity. Uncertainty in spectral emissivity arises as it is nearly impossible to predict and can be a strong function of wavelength; in turn, this manifests uncertainty in estimated temperatures and thereby obscures the LPBF process dynamics that indicate component defects. This paper presents temperature emissivity separation (TES) as a method for accurate retrieval of optically-measured temperatures in LPBF. TES simultaneously calculates both temperature and spectral emissivity from spectrally-resolved radiance measurements and, as the latter term is effectively measured, more accurate process temperatures result. Using a bespoke imaging spectrometer integrated with an LPBF testbed to evaluate this approach, three basic TES algorithms are compared in a validation experiment that demonstrates retrieval of temperatures accurate to <span><math><mrow><mo>±</mo><mn>28</mn></mrow></math></span> K over a 1000 K range. A second investigation proves industrial feasibility through fabrication of an LPBF test artifact. Temperature data are used to study the evolution of fusion process boundary conditions, including a decrease in cooling rate as layerwise printing proceeds. A provisional correlation of temperature fields to component porosity assessed by 3D computed tomography demonstrates in situ optical detection of micron-scale porous defects in LPBF.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"110 ","pages":"Article 104904"},"PeriodicalIF":11.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144864423","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":"Convolutional autoencoder frameworks for projection multi-photon 3D printing","authors":"Ishat Raihan Jamil ,&nbsp;Jason E. Johnson ,&nbsp;Xianfan Xu","doi":"10.1016/j.addma.2025.104929","DOIUrl":"10.1016/j.addma.2025.104929","url":null,"abstract":"<div><div>Projection multi-photon 3D printing is an emerging technique for fabricating micro-nano structures at exceptionally high speeds. It leverages the use of a digital micromirror (DMD) to project and print entire 2D layers at once, offering higher throughput and scalability than conventional point-by-point laser scanning. While two photon polymerization is widely regarded as an outstanding method for achieving high dimensional accuracy at the nanoscale, the projection aspect introduces a new set of challenges, such as under-printing due to oxygen inhibition. The inherently complex photopolymerization dynamics make it difficult to model and simulate efficiently. To address this, we introduce a data-driven methodology employing deep learning to build a surrogate model of the printing process and an inverse model for 2D DMD pattern optimization to achieve desirable printed shapes. By printing diverse shapes morphed by various parametrization schemes, we built a dataset for training convolutional encoder-decoder (autoencoder) neural networks. The trained surrogate accurately maps input DMD patterns to their final printed geometries, capturing nonlinearities introduced by process physics. Inverting the inputs and outputs further enabled us to train an inverse model for generating pre-compensated DMD patterns to print desirable target geometries. Experimental findings demonstrate that this deep learning approach accurately predicts printed outputs and enhances dimensional accuracy in the printing of 2D layers. Our results reveal a viable approach to overcome inhibition-induced constraints, enabling more accurate projection-based multi-photon printing at the micro and nanoscale.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"110 ","pages":"Article 104929"},"PeriodicalIF":11.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144880392","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":"Multi-layer thermal history prediction framework for directed energy deposition based on extended physics-informed neural networks (XPINN)","authors":"Bohan Peng,&nbsp;Ajit Panesar","doi":"10.1016/j.addma.2025.104953","DOIUrl":"10.1016/j.addma.2025.104953","url":null,"abstract":"<div><div>This paper presents an eXtended physics-informed neural networks (XPINN)-based framework for predicting the temperature history during a multi-layer Directed Energy Deposition (DED) process. The proposed XPINN-based framework, advancing from its PINN-based counterpart, demonstrates significant accuracy improvement, around <span><math><mrow><mn>50</mn><mo>%</mo></mrow></math></span> reduction in RMSE and maximum absolute error, and extended capability of temperature history prediction with domain decomposition for more complex configurations such as interpass time, void, and interruption of scan that are prevalent in real-life DED designs. It is validated via a series of 2D benchmark tests against numerical simulations with an increasing degree of complexity. The effect of different domain decompositions is compared and discussed. Strategies that improve the training outcome are also proposed and analysed. With the enhanced capability of working on more complex configurations while retaining the characteristic availability of derivative information, the proposed framework brings process-ware design optimisation based on scientific machine learning (SciML) techniques one step closer to the application to real-life additive manufacturing applications.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"110 ","pages":"Article 104953"},"PeriodicalIF":11.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144932612","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":"Spatial modulation of eutectoid element in melt pool by EB-PBF for constructing high-performance heterogeneous titanium alloys","authors":"Jiayin Li ,&nbsp;Bowen Ma ,&nbsp;Dongxu Chen ,&nbsp;Yuchuan Jiang ,&nbsp;Xuan Luo ,&nbsp;Dongdong Li ,&nbsp;Pan Wang","doi":"10.1016/j.addma.2025.104948","DOIUrl":"10.1016/j.addma.2025.104948","url":null,"abstract":"<div><div>The construction of heterogeneous structures for synergistic enhancement of strength and ductility in metallic materials represents a research hotspot in materials science. Additive manufacturing has achieved progress in fabricating heterogeneous titanium alloys, yet current designs primarily rely on single-phase boundary regulation, lacking multidimensional synergy in controlling precipitate distribution and grain orientation, thus hindering breakthroughs in overcoming the strength-ductility trade-off. Here, we demonstrate the fabrication of high-performance titanium alloys with hierarchical precipitate structure (HPS) via spatial control of eutectoid decomposition during electron beam powder bed fusion (EB-PBF). These structures are characterized by alternating Cu-rich solute matrices and ultrafine-grained (UFG) domains enriched with multi-scale Ti₂Cu precipitates. The alloy achieved an ultimate tensile strength of 1244 MPa, a 37.9 % increase compared to the as-bult Ti6Al4V, while maintaining good ductility (15.7 %). This exceptional mechanical performance is attributed to multi-scale precipitation strengthening facilitated by fine Ti₂Cu dispersions, heterogeneous deformation-induced strengthening across hierarchical domains, and crack deflection accompanied by micro-shear banding, which collectively enhances fracture resistance by dissipating crack propagation energy. Our findings establish a novel pathway for spatially controlled phase decomposition in AM, providing a promising approach for designing damage-tolerant, high-strength titanium alloys. This work opens new avenues for advanced applications in aerospace, biomedical, and structural components.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"110 ","pages":"Article 104948"},"PeriodicalIF":11.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144912628","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":"Rapid forming of programmable shaped morphogenic composite through additive manufacturing & frontal polymerization","authors":"Ivan C.L. Wu,&nbsp;Jeffery W. Baur","doi":"10.1016/j.addma.2025.104911","DOIUrl":"10.1016/j.addma.2025.104911","url":null,"abstract":"<div><div>Compared to thermoplastics, continuous fiber thermosets offer the potential for diverse reaction chemistry, improved thermo-mechanical properties, and new processing routes. In this work, flat preforms of additively deposited reactive resin infused fiber tows (ADRRIFT) are combined with frontally polymerizable gels of dicyclopentadiene (DCPD) to autonomously produce, upon initiation of frontal polymerization (FP), cured composites with controlled curvature. These morphogenic composites provide a low initiation energy (<span><math><mo>≈</mo></math></span>10–20 J) and rapid (<span><math><mrow><mo>≈</mo><mn>70</mn><mspace></mspace><msup><mrow><mi>cm</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></math></span>/<span><math><mi>min</mi></math></span>) method to form 3D shaped composites. Using an analytical model, 2D printed patterns of continuous carbon fiber tows are designed to produce shapes with an apparent Gaussian curvature that is positive (parabolic dish), zero (cone), and negative (saddle). To achieve the strain needed for desired shapes, these morphogenic composites have low fiber volume fraction (FVF), 3%–9%. However, we also demonstrate in this work that the shaped morphogenic composites can serve as rapid tooling for DCPD infused laminates with higher FVF (30%–42%) and mechanical stiffness. Due to the inherent surface chemistry, cured laminates easily separate from the shaped tooling without additional release agents. Together these approaches provide rapid manufacturing of shaped composites with a range of FVF and properties for application constrained in transportation volume and energy expenditure.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"110 ","pages":"Article 104911"},"PeriodicalIF":11.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144908552","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 compressive energy absorption and shape recovery behavior of additively manufactured textile-inspired cylindrical braided metamaterials","authors":"Ajay Jayswal,&nbsp;Polyxeni P. Angelopoulou,&nbsp;Sargun Singh Rohewal,&nbsp;Logan T. Kearney,&nbsp;Sumit Gupta,&nbsp;Christopher C. Bowland,&nbsp;Michael D. Toomey,&nbsp;Amit K. Naskar","doi":"10.1016/j.addma.2025.104925","DOIUrl":"10.1016/j.addma.2025.104925","url":null,"abstract":"<div><div>Mechanical metamaterials (MMs) are engineered structures with unique mechanical properties that arise from their unique spatial arrangement or lattice-like structure. The most commonly designed MMs such as honeycomb and re-entrant auxetics are prone to failure at the sharp corners and weak joints due to the increased stress concentration under deformation. To mitigate this challenge, braided MM structures involving intertwining threads of nylon—forming curved unit cells—have been studied. These textile-inspired cylindrical braided metamaterials (CBMMs) with contrasting unit cells, namely diamond and regular CBMMs, were fabricated by 3D printing. The layer-by-layer deposited structure built by fused filament fabrication delivered an assembly of overlapped threads that are fused at the contact point. To understand deformation behavior of these MMs, finite element models were developed for various load scenarios including quasi-static compression, cyclic and creep loads at room temperature. Stress distribution, deformation mechanisms, and failure modes were analyzed and validated by experiments to analyze the geometries and associated performance. The diamond CBMMs showed stress softening at 30 % compressive strain, withstanding a load of ∼440 N, whereas the regular CBMMs at 50 % strain experienced ∼250 N. The diamond CBMMs delivered higher creep resistance under sustained load and better energy absorption under cyclic loading than the regular CBMMs. The latter, however, exhibited 94 % shape recovery in contrast to 88 % recovery in former prototype during their first cyclic load. This study helps design mechanical lightweight devices that endure significant sustained load and exhibit enhanced energy absorption and shape recovery characteristics in cyclic loading.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"110 ","pages":"Article 104925"},"PeriodicalIF":11.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144852417","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":"Identifying fracture location in additively manufactured samples based on defect characteristics: Demonstration using AlSi10Mg","authors":"Nancy Huang ,&nbsp;Erik T. Furton ,&nbsp;Yasham A. Mundada ,&nbsp;Allison M. Beese","doi":"10.1016/j.addma.2025.104935","DOIUrl":"10.1016/j.addma.2025.104935","url":null,"abstract":"<div><div>A new metric was developed to quantify the impact of surface-connected defects and internal pores of different morphologies, namely irregular lack of fusion (LoF) pores and spherical keyhole pores, on the mechanical properties and fracture location of AlSi10Mg tensile samples fabricated using laser powder bed fusion additive manufacturing. As defect volume alone has been shown to be insufficient to predict fracture location, the proposed defect impact metric (DIM) incorporates contributions from additional defect features, including proximity to the surface, interaction with neighboring defects, morphology, and reduction in load-bearing cross-sectional area to better assess a defect’s propensity for corresponding to fracture location. The fracture location of keyhole samples was captured by large surface-connected defects with numerous neighboring defects and resulted in increased losses in load-bearing area. In contrast, LoF samples fractured at regions with either large surface-connected defects or large internal pores with many defects in close proximity, high curvatures, and large projected areas. The proposed DIM outperformed existing defect-based frameworks in identifying fracture locations in both LoF and keyhole samples by incorporating surface roughness, defect projected area, and interactions between defects based on distance, volume, and configuration. Additionally, the maximum DIM value within the fracture range was more strongly correlated to strength and ductility than porosity or defect size for LoF samples, demonstrating the potential of the DIM to non-destructively assess the effects of defects on mechanical behavior. The broader applicability of the DIM framework was demonstrated in its ability to capture fracture in both PBF-LB AlSi10Mg and Alloy 718.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"110 ","pages":"Article 104935"},"PeriodicalIF":11.1,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144903824","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}