Additive manufacturing最新文献

{"title":"Vector-level feedforward control of LPBF melt pool area using a physics-based thermal model","authors":"Nicholas Kirschbaum ,&nbsp;Nathaniel Wood ,&nbsp;Chang-Eun Kim ,&nbsp;Thejaswi U. Tumkur ,&nbsp;Chinedum Okwudire","doi":"10.1016/j.addma.2025.104981","DOIUrl":"10.1016/j.addma.2025.104981","url":null,"abstract":"<div><div>Laser powder bed fusion (LPBF) is an additive manufacturing technique that has gained popularity thanks to its ability to produce geometrically complex, fully dense metal parts. However, these parts are prone to internal defects and geometric inaccuracies, stemming in part from variations in the melt pool. This paper proposes a novel vector-level feedforward control framework for regulating melt pool area in LPBF. By decoupling part-scale thermal behavior from small-scale melt pool physics, the controller provides a scale-agnostic prediction of melt pool area and efficient optimization over it. This is done by operating on two coupled lightweight models: a finite-difference thermal model that efficiently captures vector-level temperature fields and a reduced-order, analytical melt pool model. Each model is calibrated separately with minimal single-track and 2D experiments, and the framework is validated on a complex 3D geometry in both Inconel 718 and 316L stainless steel. Results showed that feedforward vector-level laser power scheduling reduced geometric inaccuracy in key dimensions by 62%, overall porosity by 16.5%, and photodiode root-mean-squared deviation by 38.5% on average. Overall, this modular, data-efficient approach demonstrates that proactively compensating for known thermal effects can significantly improve part quality while remaining computationally efficient and readily extensible to other materials and machines.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"112 ","pages":"Article 104981"},"PeriodicalIF":11.1,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145323429","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":"Machining mechanics of additively manufactured metallic parts: Material characterization and constitutive modeling","authors":"Farshad Kazemi,&nbsp;Adam T. Clare,&nbsp;Xiaoliang Jin","doi":"10.1016/j.addma.2025.104996","DOIUrl":"10.1016/j.addma.2025.104996","url":null,"abstract":"<div><div>Additive manufacturing (AM) enables the production of complex, customized parts through its layer-by-layer process. However, high surface roughness and geometrical distortions often necessitate post-processing, with machining being the most widely used method. Therefore, understanding the machinability of AM parts is essential for selecting appropriate tooling and machining parameters. This requires insight into the material’s microstructure and mechanical behavior, which are significantly influenced by AM process conditions. Rapid solidification and steep thermal gradients inherent to AM processes result in distinct crystallographic textures and columnar grain growth, which affect the material’s response during machining. Due to inconsistent experimental findings in the literature, there is a need for microstructure-informed constitutive modeling. This study presents a comprehensive constitutive model to predict flow stress and cutting forces during orthogonal cutting, incorporating key strengthening mechanisms: thermal activation, solid solution, lattice resistance, grain boundary influence, and forest dislocation interactions. AM Inconel 718 which is widely used in critical industrial applications was fabricated using laser powder bed fusion (LPBF). Microstructural features and solute atom concentrations were characterized using electron backscatter diffraction (EBSD) and energy-dispersive X-ray spectroscopy (EDS), providing input for the constitutive model. Model validation was performed through orthogonal cutting experiments under various cutting conditions. Cutting forces were measured using a dynamometer, and chips were examined via scanning electron microscopy (SEM). The model predicts flow stress and cutting forces within 10 % of experimental values. Moreover, it enables a quantitative evaluation of each strengthening mechanism’s contribution, providing insight into their individual effects on the machining behavior of AM-fabricated parts.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"112 ","pages":"Article 104996"},"PeriodicalIF":11.1,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145323433","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":"Local microstructure engineering of super duplex stainless steel via dual laser powder bed fusion – An analytical modeling and experimental approach","authors":"Michele Vanini ,&nbsp;Samuel Searle ,&nbsp;Lars Vanmunster ,&nbsp;Kim Vanmeensel ,&nbsp;Bey Vrancken","doi":"10.1016/j.addma.2025.104994","DOIUrl":"10.1016/j.addma.2025.104994","url":null,"abstract":"<div><div>Laser powder bed fusion is a metal additive manufacturing technique, valued for its ability to produce near-net-shaped components with high precision. Its layer-by-layer approach and localized melting create complex temperature cycles, allowing for potential in-situ microstructure modifications. Recently, the productivity of laser beam-based additive manufacturing processes has been increased substantially by the introduction of multiple beams that operate in a parallel way, e.g. building at different locations on the same build platform. However, two laser beams can also be operated in tandem, i.e. using an additional laser beam as a trailing laser that follows the primary melting laser, enabling in-situ heat treatment and local microstructure control. This study investigates the application of dual laser powder bed fusion to locally tailor the microstructure of super duplex stainless steel, a material characterized by a dual-phase microstructure composed of δ-ferrite and γ-austenite. The phase ratio of ferrite and austenite is highly sensitive to the thermal trajectory experienced by the fabricated part, particularly in the critical temperature range of 800–1200 °C, where austenite nucleation and growth from the primary solidified δ-ferrite can occur. An analytical modeling approach, utilizing the thermal field solution based on a moving Goldak heat source, was employed to optimize the parameters of the second laser beam to maximize the residence time within the critical temperature range, thereby enhancing austenite formation. The modeling insights were then qualitatively compared through a dual-laser single-track campaign before being applied to bulk samples. This approach successfully produced specimens with varying austenite contents, ranging from 0 % under high-speed single-laser conditions to 48 % using optimized dual-laser settings. These results demonstrate that careful tuning of laser parameters enables exceptional local microstructure control along both the build and scan directions, i.e. in full 3D. On the other hand, achieving this optimal microstructure required a low scanning speed of 15 mm/s, which reduced the build rate to about 0.07 mm³/s, approximately an order of magnitude lower than the one achieved with higher-speed parameters. Although this demonstrates potential for precise 3D microstructure control, it also underscores a significant trade-off with productivity, presenting a practical limitation for industrial applications.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"112 ","pages":"Article 104994"},"PeriodicalIF":11.1,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145323432","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":"Traveling cellsman: Partition-cluster co-parameterization for multi-robot cooperative 3D printing","authors":"Matthew Ebert ,&nbsp;Ronnie Stone ,&nbsp;Ergun Akleman ,&nbsp;Zhenghui Sha ,&nbsp;Vinayak Krishnamurthy","doi":"10.1016/j.addma.2025.104987","DOIUrl":"10.1016/j.addma.2025.104987","url":null,"abstract":"<div><div>We present <em>Traveling Cellsman</em>, an approach for creating a parameterization for task scheduling and collision avoidance with Cooperative 3D printing (C3DP). The parameterization is based on the distribution of work between robots (partition), which allows the robots to navigate through their printing tasks effectively while also allowing for collision avoidance with other robots. The parameterization provides straightforward optimization of makespan. Inspired by the multiple traveling salesman problem (MTSP), we schedule tasks by first clustering tasks together based on a parameterization of the partition. The clustered tasks can then be ordered for printing. Numerical results indicate that our clustering approach finds an optimal solution faster than the non-clustered approach for minimizing the pause and movement time of the robots. Physical results also show that optimization allows for faster printing time as compared to non-optimized or slicer-based methods for generating a printing schedule. While we demonstrate our method using C3DP, it is generally applicable to other multi-robot task scheduling problems where collision may occur.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"112 ","pages":"Article 104987"},"PeriodicalIF":11.1,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145323431","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":"Creep ductility limiting mechanisms in an additively manufactured Al-Ce-Ni-Mn-Zr alloy","authors":"Jovid Rakhmonov ,&nbsp;Obaidullah Rahman ,&nbsp;Sumit Bahl ,&nbsp;Amir Koushyar Ziabari ,&nbsp;Alex Plotkowski ,&nbsp;Amit Shyam","doi":"10.1016/j.addma.2025.104983","DOIUrl":"10.1016/j.addma.2025.104983","url":null,"abstract":"<div><div>Tensile creep response and cavitation damage evolution in an additively manufactured Al-7.5Ce-4.5Ni-0.4Mn-0.7Zr (wt%) alloy with peak-aging and overaging treatments were investigated in the 300–400 ºC range. Microstructural heterogeneity and its response to heat treatment and subsequent creep deformation were studied to understand the interplay between cavity formation, creep lifetime and ductility. Increasing the applied stress activated the nucleation of more cavities, an experimental observation that is well described using the vacancy accumulation model. Cavities nucleated prematurely due to localized plasticity in the denuded zones that formed at/near melt-pool or grain boundaries. Microstructure/deformation heterogeneity with consequent evolution of stress triaxiality, especially at lower stresses, causes accelerated cavitation, thus producing low creep ductility (∼ 0.2–2.4 %), compared to (∼12–21 %) ductility of the alloy measured by regular tensile tests at equivalent temperatures. A constrained diffusional cavity growth mechanism with continuous cavity nucleation during creep is established as the dominant mechanism, implying that cavitation involves vacancy diffusion, yet its growth rate is dictated by the minimum creep rate. The ductility-limiting creep and cavitation mechanisms discussed here provide new insight into the creep behavior of 3D-printed metallic alloys.</div></div>","PeriodicalId":7172,"journal":{"name":"Additive manufacturing","volume":"112 ","pages":"Article 104983"},"PeriodicalIF":11.1,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145278293","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":"Formation mechanisms and control strategies of geometric errors induced by edge bumping during laser powder bed fusion","authors":"Haolin Liu,&nbsp;Huiliang Wei,&nbsp;Qingyuan Yin,&nbsp;Jiashun Yue,&nbsp;Tingting Liu,&nbsp;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}

{"title":"Cycloaliphatic epoxy-functionalized polysiloxanes for UV-mask 3D printing via cationic photopolymerization","authors":"Shichong Wang ,&nbsp;Meichang Xie ,&nbsp;Bing Yu ,&nbsp;Zaoji Zu ,&nbsp;Lanyue Zhang ,&nbsp;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⁻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.</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}

{"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 ,&nbsp;Huichun Tian ,&nbsp;Zhen Wang ,&nbsp;Feng Xiao ,&nbsp;Jing Qiao ,&nbsp;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}

{"title":"Reinforcement learning-enabled design of topological interlocking materials for sustainable multi-material additive manufacturing","authors":"Hichem Seriket ,&nbsp;Oualid Bougzime ,&nbsp;Yuyang Song ,&nbsp;H. Jerry Qi ,&nbsp;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}

{"title":"Digital 3D defect maps: Detecting localised porosity with high-speed melt pool imaging data in LPBF","authors":"Patrick L. Taylor ,&nbsp;Richard J. Williams ,&nbsp;Henry C. de Winton ,&nbsp;Vincent Fernandez ,&nbsp;Sebastian Larsen ,&nbsp;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}