Pub Date : 2025-08-25DOI: 10.1016/j.addma.2025.105000
Lars Vanmunster , Louca R. Goossens , Laurent Sergeant , Brecht Van Hooreweder , Bey Vrancken
Low productivity and high part cost remain key drivers preventing the widespread industrial adoption of Laser Powder Bed Fusion. While current strategies to increase build rates involve complex or expensive solutions such as beam shaping or multi-laser systems, an increased layer thickness offers a more elegant and simple alternative. However, productivity due to higher layer thickness often results in poor surface quality, specifically for near-horizontal surfaces. Adaptive slicing addresses this issue by varying the layer thickness based on local surface orientation — thin layers for near-horizontal surfaces and thicker layers for vertical surfaces — enabling significant gains in productivity without compromising part quality. This work introduces a simulation-informed algorithm for automated parameter generation, eliminating the need for extensive experimental calibration. Optimization of the algorithm’s boundary conditions allowed producing dense parts with layers gradually varying between 10 and . Applied to a hemispherical geometry, this approach reduced the scan time by 43% and simultaneously reduced recoating time by 45%, while maintaining 99.97% part relative density and preserving the dimensional accuracy. Unlike hardware-driven alternatives, the method is purely software-based and machine independent, making it highly suitable for concurrent improvement of part quality and large scale increase in LPBF productivity.
{"title":"Adaptive slicing for increased productivity of metal laser powder bed fusion","authors":"Lars Vanmunster , Louca R. Goossens , Laurent Sergeant , Brecht Van Hooreweder , Bey Vrancken","doi":"10.1016/j.addma.2025.105000","DOIUrl":"10.1016/j.addma.2025.105000","url":null,"abstract":"<div><div>Low productivity and high part cost remain key drivers preventing the widespread industrial adoption of Laser Powder Bed Fusion. While current strategies to increase build rates involve complex or expensive solutions such as beam shaping or multi-laser systems, an increased layer thickness offers a more elegant and simple alternative. However, productivity due to higher layer thickness often results in poor surface quality, specifically for near-horizontal surfaces. Adaptive slicing addresses this issue by varying the layer thickness based on local surface orientation — thin layers for near-horizontal surfaces and thicker layers for vertical surfaces — enabling significant gains in productivity without compromising part quality. This work introduces a simulation-informed algorithm for automated parameter generation, eliminating the need for extensive experimental calibration. Optimization of the algorithm’s boundary conditions allowed producing dense parts with layers gradually varying between 10 and <span><math><mrow><mn>100</mn><mspace></mspace><mi>μ</mi><mi>m</mi></mrow></math></span>. Applied to a hemispherical geometry, this approach reduced the scan time by 43% and simultaneously reduced recoating time by 45%, while maintaining 99.97% part relative density and preserving the dimensional accuracy. Unlike hardware-driven alternatives, the method is purely software-based and machine independent, making it highly suitable for concurrent improvement of part quality and large scale increase in LPBF productivity.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"112 ","pages":"Article 105000"},"PeriodicalIF":11.1,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145413641","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}
Pub Date : 2025-08-25DOI: 10.1016/j.addma.2025.105004
Jiayin Li , Bowen Ma , Dongxu Chen , Yuchuan Jiang , Xuan Luo , Dongdong Li , Pan Wang
{"title":"Corrigendum to “Spatial modulation of eutectoid element in melt pool by EB-PBF for constructing high-performance heterogeneous titanium alloys” [Addit. Manuf. 110 (2025) 104948]","authors":"Jiayin Li , Bowen Ma , Dongxu Chen , Yuchuan Jiang , Xuan Luo , Dongdong Li , Pan Wang","doi":"10.1016/j.addma.2025.105004","DOIUrl":"10.1016/j.addma.2025.105004","url":null,"abstract":"","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"112 ","pages":"Article 105004"},"PeriodicalIF":11.1,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145463265","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}
Edge bumping, a typical abnormal surface feature during the laser powder bed fusion (LPBF) process, can significantly affect the geometric accuracy of the final product. In a representative case, edge bumping induced severe geometric errors in lattice structures, including both strut necking and out-of-tolerance deviations. Despite the critical influences, the formation mechanisms and control strategies of edge bumping remain unclear. This study comprehensively investigated the characteristics of edge bumping for both standard octagonal specimens and general samples (such as topological features and overhang structures) with various geometries and dimensions, utilizing in-situ monitoring, ex-situ characterization and numerical modelling approaches. The results showed that edge bumping manifested as edge protrusions on the part top surface, exacerbated by higher laser power, slower scanning speeds, and increased laser rotations at edges. The formation mechanisms of edge bumping were revealed for the first time in this work, which comprised spatter knockdown by the laser, extra powder entrainment into the molten pool, and molten material flow and solidification at the rear of the molten pool. To mitigate the geometric errors, control strategies of edge bumping considering LPBF energy densities and inter-track cooling intervals were developed. Efficient suppressions were achieved, with edge bumping height reduced to 0.04 mm for the standard octagonal specimens, and the dimensional accuracy of lattice structures increased significantly from 68.0 % to over 96.9 %. The novel findings provide valuable insights for understanding the complexity of the transient processes, and improving the LPBF quality of engineering structures.
{"title":"Formation mechanisms and control strategies of geometric errors induced by edge bumping during laser powder bed fusion","authors":"Haolin Liu, Huiliang Wei, Qingyuan Yin, Jiashun Yue, Tingting Liu, Wenhe Liao","doi":"10.1016/j.addma.2025.104970","DOIUrl":"10.1016/j.addma.2025.104970","url":null,"abstract":"<div><div>Edge bumping, a typical abnormal surface feature during the laser powder bed fusion (LPBF) process, can significantly affect the geometric accuracy of the final product. In a representative case, edge bumping induced severe geometric errors in lattice structures, including both strut necking and out-of-tolerance deviations. Despite the critical influences, the formation mechanisms and control strategies of edge bumping remain unclear. This study comprehensively investigated the characteristics of edge bumping for both standard octagonal specimens and general samples (such as topological features and overhang structures) with various geometries and dimensions, utilizing in-situ monitoring, ex-situ characterization and numerical modelling approaches. The results showed that edge bumping manifested as edge protrusions on the part top surface, exacerbated by higher laser power, slower scanning speeds, and increased laser rotations at edges. The formation mechanisms of edge bumping were revealed for the first time in this work, which comprised spatter knockdown by the laser, extra powder entrainment into the molten pool, and molten material flow and solidification at the rear of the molten pool. To mitigate the geometric errors, control strategies of edge bumping considering LPBF energy densities and inter-track cooling intervals were developed. Efficient suppressions were achieved, with edge bumping height reduced to 0.04 mm for the standard octagonal specimens, and the dimensional accuracy of lattice structures increased significantly from 68.0 % to over 96.9 %. The novel findings provide valuable insights for understanding the complexity of the transient processes, and improving the LPBF quality of engineering structures.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"111 ","pages":"Article 104970"},"PeriodicalIF":11.1,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145155961","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}
Pub Date : 2025-08-05DOI: 10.1016/j.addma.2025.104977
Shichong Wang , Meichang Xie , Bing Yu , Zaoji Zu , Lanyue Zhang , Hongping Xiang
Cationic photocuring resins for UV-mask 3D printing exhibit lower volume shrinkage and higher printing accuracy compared to conventional free radical photocuring resins. However, their application is still hindered by low photoreactivity at 405 nm wavelength, with most improvements focusing on the development of novel photoinitiators. Herein, a synergistic strategy combining highly reactive cycloaliphatic epoxy groups with polysiloxane chains is proposed to develop novel cationic photocurable resins. Both cycloaliphatic epoxy-functionalized branched polysiloxane (CE-BSi) and linear polysiloxane (CE-LSi) are synthesized. Photocuring kinetics reveal that these resins exhibit significantly higher polymerization conversion (80 %), faster rate (25 s−1), and shorter gelation time (4 s) than conventional cationic photocuring resins. They are successfully used to fabricate different geometric objects via UV-mask 3D printing technology. The 3D printed objects show a maximum tensile strength of 21 MPa, minimum volume shrinkage of 0.2 %, and outstanding thermostability (5 % weight loss temperature of above 395 °C, heat deflection temperature exceeding 100 °C). Theoretical simulations and experimental results indicate that the enhanced photoreactivity is primarily attributed to the high reactivity of cycloaliphatic epoxy groups and the superior molecular mobility of polysiloxane chains. This strategy successfully enables UV-mask 3D printing via a pure cationic photopolymerization mechanism, producing 3D objects with low curing shrinkage and excellent thermostability, thereby significantly expanding the potential applications of photocuring 3D printing technology.
{"title":"Cycloaliphatic epoxy-functionalized polysiloxanes for UV-mask 3D printing via cationic photopolymerization","authors":"Shichong Wang , Meichang Xie , Bing Yu , Zaoji Zu , Lanyue Zhang , Hongping Xiang","doi":"10.1016/j.addma.2025.104977","DOIUrl":"10.1016/j.addma.2025.104977","url":null,"abstract":"<div><div>Cationic photocuring resins for UV-mask 3D printing exhibit lower volume shrinkage and higher printing accuracy compared to conventional free radical photocuring resins. However, their application is still hindered by low photoreactivity at 405 nm wavelength, with most improvements focusing on the development of novel photoinitiators. Herein, a synergistic strategy combining highly reactive cycloaliphatic epoxy groups with polysiloxane chains is proposed to develop novel cationic photocurable resins. Both cycloaliphatic epoxy-functionalized branched polysiloxane (CE-BSi) and linear polysiloxane (CE-LSi) are synthesized. Photocuring kinetics reveal that these resins exhibit significantly higher polymerization conversion (80 %), faster rate (25 s<sup>−1</sup>), and shorter gelation time (4 s) than conventional cationic photocuring resins. They are successfully used to fabricate different geometric objects via UV-mask 3D printing technology. The 3D printed objects show a maximum tensile strength of 21 MPa, minimum volume shrinkage of 0.2 %, and outstanding thermostability (5 % weight loss temperature of above 395 °C, heat deflection temperature exceeding 100 °C). Theoretical simulations and experimental results indicate that the enhanced photoreactivity is primarily attributed to the high reactivity of cycloaliphatic epoxy groups and the superior molecular mobility of polysiloxane chains. This strategy successfully enables UV-mask 3D printing via a pure cationic photopolymerization mechanism, producing 3D objects with low curing shrinkage and excellent thermostability, thereby significantly expanding the potential applications of photocuring 3D printing technology.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"111 ","pages":"Article 104977"},"PeriodicalIF":11.1,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217732","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}
Pub Date : 2025-08-05DOI: 10.1016/j.addma.2025.104978
Xiangxu Deng , Huichun Tian , Zhen Wang , Feng Xiao , Jing Qiao , Longqiu Li
Material extrusion has become the most common additive manufacturing (AM) method, but its further industrial applications are limited by low reliability and error susceptibility. Therefore, defect detection and process control are of crucial importance. The lack of theoretical analysis in the closed-loop process control prevents both the rapidity and robustness of defect mitigation. Meanwhile, obtaining sufficient labelled datasets for non-parametric defects is challenging. A real-time visual prediction and fuzzy control system was proposed to achieve rapid and stable defect mitigation. A visual foundation model (VFM) was trained by the dataset with over 560,000 images generated through a visualized automatic annotation system (VAAS). A closed-loop system with VFM was modelled and identified to clarify the control challenges: the time delay and variable response of closed-loop process control, as well as demonstrate the instability of proportional control. Besides, a fuzzy controller was designed to address the control challenges. Additionally, a self-supervised transfer learning (TL) framework is introduced, combining clustering pseudo-label and fine-tuning, for the cross-domain and cross-task adaptation of the VFM. Experiments show that the fuzzy controller significantly reduces the disturbance rejection time to 15.6 % compared with the current method and improves the stability of the system. Through the TL framework, defect detection in robotic-arm fused deposition modelling (FDM) for a specific printed part was achieved with 89.4 % accuracy with the balanced fine-tuning strategy, paving a way for the wider application of defect detection in AM.
{"title":"In-situ real-time defect detection, mitigation and self-supervised adaptation based on visual foundation model for material extrusion additive manufacturing","authors":"Xiangxu Deng , Huichun Tian , Zhen Wang , Feng Xiao , Jing Qiao , Longqiu Li","doi":"10.1016/j.addma.2025.104978","DOIUrl":"10.1016/j.addma.2025.104978","url":null,"abstract":"<div><div>Material extrusion has become the most common additive manufacturing (AM) method, but its further industrial applications are limited by low reliability and error susceptibility. Therefore, defect detection and process control are of crucial importance. The lack of theoretical analysis in the closed-loop process control prevents both the rapidity and robustness of defect mitigation. Meanwhile, obtaining sufficient labelled datasets for non-parametric defects is challenging. A real-time visual prediction and fuzzy control system was proposed to achieve rapid and stable defect mitigation. A visual foundation model (VFM) was trained by the dataset with over 560,000 images generated through a visualized automatic annotation system (VAAS). A closed-loop system with VFM was modelled and identified to clarify the control challenges: the time delay and variable response of closed-loop process control, as well as demonstrate the instability of proportional control. Besides, a fuzzy controller was designed to address the control challenges. Additionally, a self-supervised transfer learning (TL) framework is introduced, combining clustering pseudo-label and fine-tuning, for the cross-domain and cross-task adaptation of the VFM. Experiments show that the fuzzy controller significantly reduces the disturbance rejection time to 15.6 % compared with the current method and improves the stability of the system. Through the TL framework, defect detection in robotic-arm fused deposition modelling (FDM) for a specific printed part was achieved with 89.4 % accuracy with the balanced fine-tuning strategy, paving a way for the wider application of defect detection in AM.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"111 ","pages":"Article 104978"},"PeriodicalIF":11.1,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262899","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}
Pub Date : 2025-08-05DOI: 10.1016/j.addma.2025.104992
Hichem Seriket , Oualid Bougzime , Yuyang Song , H. Jerry Qi , Frédéric Demoly
Additive manufacturing (AM) has significantly expanded the possibilities to design sophisticated shapes and structures with unique properties and materials to achieve unprecedented functionalities. A notable trend in AM is the integration of multiple materials within a single structure to achieve multifunctionality while minimizing part count. However, multi-material AM presents inherent challenges, particularly in terms of printability constraints and environmental considerations, such as the recyclability of composite structures. Although the current effort in hybrid AM offers a partial solution to address some of these challenges, material versatility and sustainable disassembly remain major barriers. This research aims to introduce a computational interlocking design strategy for multi-material AM on a voxel basis, thus enabling controlled material disassembly and reuse. Reinforcement learning, especially Q-learning, is employed to optimize and explore the spatial arrangement of topological interlocking materials in the three-dimensional design space, which facilitates modularity while maintaining structural stability. Implemented via a Python-based computational framework interfaced with a computer-aided design environment, this approach is validated across various structural configurations, including cubic, beam, and irregular shapes. Our findings demonstrate a path towards sustainable, reusable, and recyclable multi-material AM, offering new possibilities for circular manufacturing and resource-efficient design.
{"title":"Reinforcement learning-enabled design of topological interlocking materials for sustainable multi-material additive manufacturing","authors":"Hichem Seriket , Oualid Bougzime , Yuyang Song , H. Jerry Qi , Frédéric Demoly","doi":"10.1016/j.addma.2025.104992","DOIUrl":"10.1016/j.addma.2025.104992","url":null,"abstract":"<div><div>Additive manufacturing (AM) has significantly expanded the possibilities to design sophisticated shapes and structures with unique properties and materials to achieve unprecedented functionalities. A notable trend in AM is the integration of multiple materials within a single structure to achieve multifunctionality while minimizing part count. However, multi-material AM presents inherent challenges, particularly in terms of printability constraints and environmental considerations, such as the recyclability of composite structures. Although the current effort in hybrid AM offers a partial solution to address some of these challenges, material versatility and sustainable disassembly remain major barriers. This research aims to introduce a computational interlocking design strategy for multi-material AM on a voxel basis, thus enabling controlled material disassembly and reuse. Reinforcement learning, especially Q-learning, is employed to optimize and explore the spatial arrangement of topological interlocking materials in the three-dimensional design space, which facilitates modularity while maintaining structural stability. Implemented via a Python-based computational framework interfaced with a computer-aided design environment, this approach is validated across various structural configurations, including cubic, beam, and irregular shapes. Our findings demonstrate a path towards sustainable, reusable, and recyclable multi-material AM, offering new possibilities for circular manufacturing and resource-efficient design.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"111 ","pages":"Article 104992"},"PeriodicalIF":11.1,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145324500","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}
Pub Date : 2025-08-05DOI: 10.1016/j.addma.2025.104982
Patrick L. Taylor , Richard J. Williams , Henry C. de Winton , Vincent Fernandez , Sebastian Larsen , Paul A. Hooper
Adoption of metal additive manufacturing for critical applications is hindered by the costs of post-build quality inspection. In-process monitoring offers a promising alternative by enabling parallel construction of digital 3D defect maps for every component manufactured. In this work, we present a system to detect local regions of porosity, containing both keyhole and lack-of-fusion defects, in laser powder bed fusion parts. A coaxial high-speed melt pool imaging setup operating at acquires feature-rich data, capturing images approximately every along scan tracks and records over 30 million melt pool images per hour of build time. Using these data, a gradient-boosted decision tree model is trained to classify porosity levels in localised voxel bins. The system achieves a state-of-the-art detection threshold of 0.11% porosity, defined by the standard non-destructive evaluation criterion of 90% probability of detection at 95% confidence. By training on datasets containing realistic, organically generated porosity and demonstrating the most accurate localised porosity detection yet reported, this work represents a significant advance towards practical, industrially relevant in-process defect detection for additive manufacturing.
{"title":"Digital 3D defect maps: Detecting localised porosity with high-speed melt pool imaging data in LPBF","authors":"Patrick L. Taylor , Richard J. Williams , Henry C. de Winton , Vincent Fernandez , Sebastian Larsen , Paul A. Hooper","doi":"10.1016/j.addma.2025.104982","DOIUrl":"10.1016/j.addma.2025.104982","url":null,"abstract":"<div><div>Adoption of metal additive manufacturing for critical applications is hindered by the costs of post-build quality inspection. In-process monitoring offers a promising alternative by enabling parallel construction of digital 3D defect maps for every component manufactured. In this work, we present a system to detect local regions of porosity, containing both keyhole and lack-of-fusion defects, in laser powder bed fusion parts. A coaxial high-speed melt pool imaging setup operating at <span><math><mrow><mn>20</mn><mspace></mspace><mstyle><mi>k</mi><mi>H</mi><mi>z</mi></mstyle></mrow></math></span> acquires feature-rich data, capturing images approximately every <span><math><mrow><mn>37</mn><mo>.</mo><mn>5</mn><mspace></mspace><mstyle><mi>µ</mi><mi>m</mi></mstyle></mrow></math></span> along scan tracks and records over 30 million melt pool images per hour of build time. Using these data, a gradient-boosted decision tree model is trained to classify porosity levels in localised <span><math><mrow><mn>2</mn><mspace></mspace><mstyle><mi>m</mi><mi>m</mi></mstyle></mrow></math></span> voxel bins. The system achieves a state-of-the-art detection threshold of 0.11% porosity, defined by the standard non-destructive evaluation criterion of 90% probability of detection at 95% confidence. By training on datasets containing realistic, organically generated porosity and demonstrating the most accurate localised porosity detection yet reported, this work represents a significant advance towards practical, industrially relevant in-process defect detection for additive manufacturing.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"111 ","pages":"Article 104982"},"PeriodicalIF":11.1,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145262937","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}
Pub Date : 2025-08-05DOI: 10.1016/j.addma.2025.104986
O. Eldaly , H. Zhang , T. Virazels , J.A. Rodríguez-Martínez , T.J. Horn , M.A. Zikry
Niobium alloys, such as C-103, have been used for high-temperature applications due to their oxidation resistance, high-temperature behavior, and ductility. These characteristics also render C-103 as an attractive material for additive manufacturing (AM) processing. However, there is a lack of fundamental understanding of how defects, such as dislocation density and dislocation density interactions, and texture affect high strain-rate and spall behavior in body-centered cubic (b.c.c.) AM processed C-103 alloys. To address these challenges, electron beam powder bed fusion (EB-PBF) was used to process and fabricate C-103 samples with highly textured columnar grains. Disc-shaped plate-impact test specimens were extracted from the AM-fabricated samples, with the grains oriented either parallel or perpendicular to the build direction, for experiments with loading velocities of up to 600 m/s. The tests were instrumented with a photonic Doppler velocimetry (PDV) system to obtain time-resolved free surface velocity data of the sample and compute the spall strength of C-103 across a wide range of loading rates. These experimental measurements were then integrated with computational predictions based on a dislocation-based crystalline plasticity (DCP) approach coupled with a fracture formulation to understand how defects, such as dislocation densities, affect the spall strength and the defect behavior of C-103. The predictive framework provided insights into how spall cracks nucleate due to a combination of tensile wave reflection and dislocation-density accumulation, and how immobile dislocation accumulation ahead of multiple crack fronts can blunt spall propagation. This interrelated approach provides an understanding of high strain-rate and dynamic fracture of textured AM b.c.c. microstructures that can be tailored to mitigate high-impact velocity and spall in niobium alloys.
{"title":"An integrated microstructural high strain-rate experimental and computational analysis of the spall behavior of additively manufactured niobium C-103 alloys","authors":"O. Eldaly , H. Zhang , T. Virazels , J.A. Rodríguez-Martínez , T.J. Horn , M.A. Zikry","doi":"10.1016/j.addma.2025.104986","DOIUrl":"10.1016/j.addma.2025.104986","url":null,"abstract":"<div><div>Niobium alloys, such as C-103, have been used for high-temperature applications due to their oxidation resistance, high-temperature behavior, and ductility. These characteristics also render C-103 as an attractive material for additive manufacturing (AM) processing. However, there is a lack of fundamental understanding of how defects, such as dislocation density and dislocation density interactions, and texture affect high strain-rate and spall behavior in body-centered cubic (b.c.c.) AM processed C-103 alloys. To address these challenges, electron beam powder bed fusion (EB-PBF) was used to process and fabricate C-103 samples with highly textured columnar grains. Disc-shaped plate-impact test specimens were extracted from the AM-fabricated samples, with the grains oriented either parallel or perpendicular to the build direction, for experiments with loading velocities of up to 600 m/s. The tests were instrumented with a photonic Doppler velocimetry (PDV) system to obtain time-resolved free surface velocity data of the sample and compute the spall strength of C-103 across a wide range of loading rates. These experimental measurements were then integrated with computational predictions based on a dislocation-based crystalline plasticity (DCP) approach coupled with a fracture formulation to understand how defects, such as dislocation densities, affect the spall strength and the defect behavior of C-103. The predictive framework provided insights into how spall cracks nucleate due to a combination of tensile wave reflection and dislocation-density accumulation, and how immobile dislocation accumulation ahead of multiple crack fronts can blunt spall propagation. This interrelated approach provides an understanding of high strain-rate and dynamic fracture of textured AM b.c.c. microstructures that can be tailored to mitigate high-impact velocity and spall in niobium alloys.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"111 ","pages":"Article 104986"},"PeriodicalIF":11.1,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145263060","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}
Pub Date : 2025-08-05DOI: 10.1016/j.addma.2025.104969
Jaime A. Benavides-Guerrero , Luis F. Gerlein , Astrid C. Angel-Ospina , Paul Fourmont , Abhiroop Bhattacharya , Abbas Zirakjou , Fabrice Vaussenat , Caroline A. Ross , Sylvain G. Cloutier
We demonstrate how strategically engineered oxygen vacancies enable room-temperature laser crystallization of zirconia (ZrO₂) in ambient air. Our sol-gel chelation synthesis creates amorphous ZrO₂ nanoparticles with a high concentration of oxygen vacancies that fundamentally alter the material's energy landscape. These defects create sub-bandgap states that facilitate visible light absorption and dramatically reduce the energy barrier for crystallization. Under low-energy laser irradiation (405–532 nm), oxygen vacancies mediate a rapid phase transformation mechanism where atmospheric oxygen interacts with vacancy sites, triggering ionic rearrangement and crystallization without conventional high-temperature processing. For comparison purposes, this study also explores the thermal crystallization of black zirconia in an oxidative atmosphere, a process typically performed under vacuum or inert conditions. Through comprehensive characterization (FTIR, EPR, XPS, XRD, Raman), we establish that vacancy-mediated crystallization produces monoclinic ZrO₂ with preserved defect structures, yielding a distinctive black phase with 25.6 % oxygen vacancy concentration, significantly higher than thermally processed counterparts (9.2 %). This vacancy-enabled crystallization circumvents the need for extreme temperatures (>1170°C) typically required for ZrO₂ processing, making it compatible with additive manufacturing. Using a modified 3D printer with a 405 nm laser, we demonstrate patterned crystallization of complex architectures, opening new possibilities for fabricating advanced ZrO₂-based devices for photocatalysis, fuel cells, and energy applications. This work provides fundamental insights into defect-mediated phase transformations and establishes a new paradigm for room-temperature ceramic processing.
{"title":"Room-temperature laser crystallization of oxygen vacancy-engineered zirconia for additive manufacturing","authors":"Jaime A. Benavides-Guerrero , Luis F. Gerlein , Astrid C. Angel-Ospina , Paul Fourmont , Abhiroop Bhattacharya , Abbas Zirakjou , Fabrice Vaussenat , Caroline A. Ross , Sylvain G. Cloutier","doi":"10.1016/j.addma.2025.104969","DOIUrl":"10.1016/j.addma.2025.104969","url":null,"abstract":"<div><div>We demonstrate how strategically engineered oxygen vacancies enable room-temperature laser crystallization of zirconia (ZrO₂) in ambient air. Our sol-gel chelation synthesis creates amorphous ZrO₂ nanoparticles with a high concentration of oxygen vacancies that fundamentally alter the material's energy landscape. These defects create sub-bandgap states that facilitate visible light absorption and dramatically reduce the energy barrier for crystallization. Under low-energy laser irradiation (405–532 nm), oxygen vacancies mediate a rapid phase transformation mechanism where atmospheric oxygen interacts with vacancy sites, triggering ionic rearrangement and crystallization without conventional high-temperature processing. For comparison purposes, this study also explores the thermal crystallization of black zirconia in an oxidative atmosphere, a process typically performed under vacuum or inert conditions. Through comprehensive characterization (FTIR, EPR, XPS, XRD, Raman), we establish that vacancy-mediated crystallization produces monoclinic ZrO₂ with preserved defect structures, yielding a distinctive black phase with 25.6 % oxygen vacancy concentration, significantly higher than thermally processed counterparts (9.2 %). This vacancy-enabled crystallization circumvents the need for extreme temperatures (>1170°C) typically required for ZrO₂ processing, making it compatible with additive manufacturing. Using a modified 3D printer with a 405 nm laser, we demonstrate patterned crystallization of complex architectures, opening new possibilities for fabricating advanced ZrO₂-based devices for photocatalysis, fuel cells, and energy applications. This work provides fundamental insights into defect-mediated phase transformations and establishes a new paradigm for room-temperature ceramic processing.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"111 ","pages":"Article 104969"},"PeriodicalIF":11.1,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107675","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}
Pub Date : 2025-08-05DOI: 10.1016/j.addma.2025.104954
Carlos Samuel Alves da Silva , Hugo Magalhães de Azevedo , Matheus Valentim , Gilberto Vicente Prandi , João Felipe Queiroz Rodrigues , Kaio Niitsu Campo , Hamilton Ferreira Gomes de Abreu , Rubens Caram
This investigation aims to explore the unresolved crack formation mechanism in compression, based on the influence of the crystallographic nature in the Ti-5553 alloy, which is susceptible to Laser Powder Bed Fusion (PBF-LB) defects as well as stress-induced martensitic transformations (SIMT). The cylindrical samples were obtained and subsequently subjected to a compressive load to investigate the BCC/orthorhombic transformation in the failure behaviour. Here, the variant selection approach based on the Schmid factor (SF) criteria was employed to elucidate the martensitic phase transformations and their role in the crack path. It was demonstrated that the accumulation of plastic strain at discontinuities that result from the processing route initiate the martensitic transformation. Additionally, a stacking fault in the orthorhombic phase will assist the α’’/α’ (Orthorhombic/Hexagonal closed packed - HCP) transformation. The analysis showed that the SIMT mechanism follows the //// and //// orientation relationship and that the failure on the transverse direction follows a direction close to // //TD.
{"title":"Stress-induced martensitic transformation mechanism in the crack behaviour of compressed additively manufactured Ti-5553 alloy: A variant selection approach","authors":"Carlos Samuel Alves da Silva , Hugo Magalhães de Azevedo , Matheus Valentim , Gilberto Vicente Prandi , João Felipe Queiroz Rodrigues , Kaio Niitsu Campo , Hamilton Ferreira Gomes de Abreu , Rubens Caram","doi":"10.1016/j.addma.2025.104954","DOIUrl":"10.1016/j.addma.2025.104954","url":null,"abstract":"<div><div>This investigation aims to explore the unresolved crack formation mechanism in compression, based on the influence of the crystallographic nature in the Ti-5553 alloy, which is susceptible to Laser Powder Bed Fusion (PBF-LB) defects as well as stress-induced martensitic transformations (SIMT). The cylindrical samples were obtained and subsequently subjected to a compressive load to investigate the BCC/orthorhombic transformation in the failure behaviour. Here, the variant selection approach based on the Schmid factor (SF) criteria was employed to elucidate the martensitic phase transformations and their role in the crack path. It was demonstrated that the accumulation of plastic strain at discontinuities that result from the processing route initiate the martensitic transformation. Additionally, a stacking fault in the orthorhombic phase will assist the α’’/α’ (Orthorhombic/Hexagonal closed packed - HCP) transformation. The analysis showed that the SIMT mechanism follows the <span><math><msub><mrow><mo>{</mo><mn>101</mn><mo>}</mo></mrow><mrow><mi>β</mi></mrow></msub></math></span>//<span><math><msub><mrow><mo>{</mo><mn>001</mn><mo>}</mo></mrow><mrow><mi>α</mi><mo>′</mo><mo>′</mo></mrow></msub></math></span>//<span><math><msub><mrow><mo>{</mo><mn>0001</mn><mo>}</mo></mrow><mrow><mi>α</mi><mo>′</mo></mrow></msub></math></span> and <span><math><msub><mrow><mo><</mo><mn>111</mn><mo>></mo></mrow><mrow><mi>β</mi></mrow></msub></math></span>//<span><math><msub><mrow><mo><</mo><mn>110</mn><mo>></mo></mrow><mrow><mi>α</mi><mo>′</mo><mo>′</mo></mrow></msub></math></span>//<span><math><msub><mrow><mo><</mo><mn>11</mn><mover><mrow><mn>2</mn></mrow><mo>̅</mo></mover><mn>0</mn><mo>></mo></mrow><mrow><mi>α</mi><mo>′</mo></mrow></msub></math></span> orientation relationship and that the failure on the transverse direction follows a direction close to <span><math><msub><mrow><mo><</mo><mn>212</mn><mo>></mo></mrow><mrow><mi>β</mi></mrow></msub></math></span> // <span><math><msub><mrow><mo><</mo><mn>211</mn><mo>></mo></mrow><mrow><mi>α</mi><mo>′</mo><mo>′</mo></mrow></msub></math></span>//TD.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"111 ","pages":"Article 104954"},"PeriodicalIF":11.1,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145155962","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}
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