International Journal of Material Forming最新文献

{"title":"Thermally-induced free vibration behavior of curved laminated composite and sandwich beams using high-fidelity hybridized physics-informed neural network-support vector machine learning algorithm","authors":"Ashish,&nbsp;S. Anbukumar","doi":"10.1007/s12289-026-02046-2","DOIUrl":"10.1007/s12289-026-02046-2","url":null,"abstract":"<div><p>The thermally induced free vibration behavior of curved laminated composite and sandwich beams is investigated using a rigorously coupled computational–data-driven framework. Curved geometries introduce membrane–bending coupling and anisotropic interactions that significantly complicate dynamic response prediction, particularly under thermal loading where material degradation alters stiffness characteristics. To address this, a higher-order zigzag theory (HOZT)-based finite element formulation is developed to accurately capture interlaminar kinematics and transverse shear effects without ad hoc corrections. The numerical model is validated against literature benchmarks and ABAQUS simulations, demonstrating high fidelity. A large-scale parametric dataset (10,000 samples) is generated using Sobol sequence sampling across geometric, material, layup, boundary, and thermal variables. A hybrid physics-informed artificial neural network–support vector machine (ANN–SVM) surrogate is then constructed, embedding variational bounds, sensitivity constraints, and uncertainty quantification within the learning process. This is not just curve-fitting, the model is explicitly regularized by mechanics. Results show a consistent reduction in natural frequencies with increasing temperature due to stiffness degradation, while curvature and ply orientation induce nontrivial modal coupling effects. The proposed hybrid model outperforms standalone approaches, achieving R² ≈ 0.98 (training) and 0.96 (testing), with unbiased residuals and well-calibrated prediction intervals.</p></div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148323939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-response optimization of turning parameters for laser powder bed fusion 17-4PH stainless steel using PCA-GRA","authors":"Thabet A. M. Sghaier,&nbsp;Habib Sahlaoui,&nbsp;Tarek Mabrouki,&nbsp;Haifa Sallem,&nbsp;Mohamed Athmane Yallese,&nbsp;Joel Rech","doi":"10.1007/s12289-026-02047-1","DOIUrl":"10.1007/s12289-026-02047-1","url":null,"abstract":"<div><p>This study investigates the influence of cutting parameters and lubrication mode on the turning performance of 17-4PH stainless steel produced by Laser Powder Bed Fusion (LPBF). A mixed-level Taguchi L18 orthogonal array was employed to evaluate the effects of depth of cut, feed rate, cutting speed, and lubrication (dry and MQL) on surface roughness (Ra), cutting force (F), and material removal rate (MRR). Single-response optimization based on signal-to-noise (S/N) ratios revealed conflicting optimal conditions among the responses, highlighting the limitations of conventional Taguchi approaches for multi-objective problems. To overcome this limitation, Grey Relational Analysis (GRA) combined with Principal Component Analysis (PCA) was applied to transform the multi-response problem into a single weighted performance index (W-GRG). The weighting coefficients were derived objectively from PCA, ensuring a data-driven and statistically consistent optimization framework. Surface characterization showed that as-built LPBF surfaces exhibit high roughness and irregular topography due to partially melted particles and layer-wise deposition. These features significantly influence machining behavior and can be effectively reduced through finishing operations. The results indicate that feed rate predominantly affects surface roughness, while depth of cut governs both cutting force and overall machining performance. The influence of MQL remains limited compared to geometrical parameters, mainly contributing to improved cutting stability and surface integrity. Multi-response optimization identified the optimal parameter combination that provides a balanced compromise between surface quality, cutting load, and productivity. The proposed PCA–GRA methodology offers a robust and systematic framework for multi-criteria optimization and provides deeper insights into the specific machining behavior of LPBF materials, thereby enhancing the industrial applicability of additively manufactured 17-4PH components.</p></div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148323386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review of neural networks used in plastic deformation of materials and an electromagnetic forming application","authors":"Dorin Luca,&nbsp;Florin Leon,&nbsp;Narcis-Nicolae Popescu,&nbsp;Dorian D. Luca,&nbsp;Georgian Artene","doi":"10.1007/s12289-026-02032-8","DOIUrl":"10.1007/s12289-026-02032-8","url":null,"abstract":"<div><p>This article presents a review of the current state of neural network applications in plastic deformation processes, together with an experimental study and modeling of the electromagnetic forming process of AlMn0.5Mg0.5 aluminum alloy sheet. The first part summarizes several case studies that demonstrate the potential of neural networks in the plastic deformation of metallic and non-metallic materials such as composites, glasses, polymers, foams, clay, as well as shape memory alloys. This part examines different types of neural networks, learning algorithms, feature selection methods, and optimization techniques that apply to plastic deformation processes. It also explores their integration with other modeling approaches, such as regression and finite element analysis. The second part focuses on predicting the maximum deformation depth, which serves as an indicator of formability, in the electromagnetic bulging of round cups. Six process parameters (deformed part size, thickness of specimen, gap distance, number of coil turns, capacitance of capacitor bank and the charging voltage) are identified as significantly influential and serve as input variables for both the experimental design and modeling. The study applies both nonlinear regression and neural networks to predict the output parameter. Both models reliably predict the output parameter, and their performance is demonstrated by an average relative error of 2.53% for the nonlinear regression model and a coefficient of determination of 0.9971 for the neural network model, which indicate their potential for manufacturing process control.</p></div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12289-026-02032-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148261806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of joint strength in PP-GF / aluminum hybrid components using a novel bulk forming process","authors":"Calvin Ebert,&nbsp;Philip Reitinger,&nbsp;Diego Rafael Alba,&nbsp;Andreas Hansen Gonçalves,&nbsp;Bedi Berk Karanlık,&nbsp;Mathias Liewald,&nbsp;Christian Bonten","doi":"10.1007/s12289-026-02043-5","DOIUrl":"10.1007/s12289-026-02043-5","url":null,"abstract":"<div><p>Hybrid components can effectively combine the advantageous properties of different materials, such as the excellent mechanical performance of metals and the light-weight characteristics of polymers. This study therefore investigates the manufacturing and mechanical performance of hybrid components comprising a metallic tube with a polymer core. The hybrid parts were produced by pressing a polymer into the metallic tube using a compression process at temperatures ranging from 100 °C to 150 °C, which is below the polymer’s melting temperature. This novel process differs significantly from conventional methods, such as injection molding with overmolding, as it enables simultaneous deformation of the metallic tube and forming of the plastic in solid state. To analyze the bond strength and assess the mechanical interlocking and adhesion at the interface, push-out tests and torsional loading experiments were conducted. The bond strength reached values of up to 8.4 MPa. Further, a finite element model was developed to simulate the forming process, enabling analysis of interfacial contact pressure, geometry variation, and local stress and strain states to provide deeper insights into material flow and deformation mechanisms.</p></div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12289-026-02043-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148261747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on regulating the anisotropy of mechanical properties of spray-extruded 7055 aluminum alloy by multi-directional forging","authors":"Menghan Wang,&nbsp;Guojun Tang,&nbsp;Yuanyuan Zheng,&nbsp;Songlin Li,&nbsp;Mingliang Cui","doi":"10.1007/s12289-026-02044-4","DOIUrl":"10.1007/s12289-026-02044-4","url":null,"abstract":"<div><p>The spray-extruded 7055 aluminum alloy exhibits significant anisotropy due to the fibrous texture formed by extrusion deformation, which easily leads to cracking and folding during the forging of large structural components. Targeting the unique microstructure of this composite-processed alloy, this paper combines theoretical modeling, finite element simulation, and production experiments to systematically investigate the coupled influence of multi-directional forging (MDF) parameters (initial forging temperature, deformation rate, forging passes) on the alloy’s strain distribution, dynamic recrystallization behavior, and mechanical property anisotropy, and clarifies its regulation mechanism. A strain-compensated Arrhenius constitutive model modified by the k (ε,T) coupling function is established, which is embedded into finite element software to construct a reliable MDF simulation model. The results show that 450℃, 2 mm/s, and 3 passes are the optimal parameters; under these conditions, the strain ratio between the extrusion direction (ED) and radial direction (RD) decreases from 2.10 to 1.01, and the anisotropy coefficients of tensile strength, yield strength, and elongation are reduced to 1.00, 1.03, and 1.04 respectively, effectively improving the directional consistency of the material’s properties. This study fills the gap in MDF research on spray-extruded 7055 aluminum alloy and provides a scientific basis for the blooming process of large aluminum alloy forgings.</p></div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148261692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of non-uniform meshes for accelerated simulation of aluminum foam based on conditioned 3D U-Net","authors":"Weimin Zhuang,&nbsp;Bu Yang,&nbsp;Fan Zhang,&nbsp;Xin Deng","doi":"10.1007/s12289-026-02045-3","DOIUrl":"10.1007/s12289-026-02045-3","url":null,"abstract":"<div><p>A deep learning-based method for predicting the optimized mesh of metallic foams is established to enhance the efficiency of the preprocessing for finite element (FE) modeling of metallic foams and reduce the reliance on expert experience. A framework for predicting the non-uniform mesh density of aluminum foam based on a conditioned 3D U-Net (C-3D-U-Net) is proposed. A voxel dataset of size 256³ was constructed using a foam aluminum generation plugin based on a Voronoi-based aluminum foam generation plugin and voxelization processing, with the mesh density information encoded as voxel values. Meanwhile, the stress-strain curves obtained via Abaqus were employed as conditional controls for the network. A C-3D-U-Net model was developed, and the stress-strain curves were injected into each stage of the decoder through the adaptive instance normalization (AdaIN) module as conditions to guide the network to generate non-uniform mesh density distributions that conform to mechanical properties. The results show that the non-uniform mesh partitioning scheme predicted by the model saves an average of 10.4% of the computing time while maintaining a high consistency with the simulation results of the original high-density mesh. This study provides a new data-driven solution for the automation of preprocessing in finite element simulation of complex structures and offers an approach to address the data volume challenge in applying deep learning methods to materials science.</p></div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 3","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148261691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of a clinched joint strength of dissimilar aluminium alloy sheets based on ductile rupture model","authors":"Abhishek Kumar,&nbsp;Sandrine Thuillier","doi":"10.1007/s12289-026-02041-7","DOIUrl":"10.1007/s12289-026-02041-7","url":null,"abstract":"<div><p>This article investigates the clinching process for joining dissimilar aluminium alloy sheets, focusing on the prediction of joint strength using an uncoupled rupture criterion. Clinching is a mechanical sheet metal joining technique that does not require additional materials, making it efficient for use in industries like automotive manufacturing, where weight reduction is critical. In the present study finite element analysis (FEA) based numerical simulations were developed, to explore the formation and strength of clinched joints between two aluminium alloys, AA5182-O and AA6016-T4, which are known for their anisotropic properties. A key aspect of the research is the calibration of material models using a hybrid experimental-numerical approach. The study incorporates advanced yield criterion and hardening models (Yld2004-18p, combined Swift-Voce) and an uncoupled ductile rupture model (Lou2012) to predict damage and failure during the clinching process. Both 2D and 3D simulations are employed to assess the clinch joint formation, material flow, and joint strength under tensile-shear loading conditions. The simulations were validated against experimental results, showing the effectiveness of the considered models. The research highlights the challenges of accurately simulating clinched joints due to high plastic deformation and complex material behaviors. Moreover, the importance of integrating material anisotropy and damage models in predicting the performance of clinched joints under operational stresses are discussed. This work advances the understanding of clinch joint behavior, particularly for dissimilar materials, and provides insights for improving joint quality and strength prediction through enhanced simulation techniques.</p></div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148236607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preliminary study on the microstructure evolution and deformation behavior of Ti6Al4V-5Cu alloy at low forming temperatures","authors":"Solomon Kerealme Yeshanew,&nbsp;Chunguang Bai,&nbsp;Qing Jia,&nbsp;Tong Xi,&nbsp;Zhiqiang Zhang,&nbsp;Diaofeng Li,&nbsp;Zhizhou Xia,&nbsp;Rui Yang,&nbsp;Ke Yang","doi":"10.1007/s12289-026-02039-1","DOIUrl":"10.1007/s12289-026-02039-1","url":null,"abstract":"<div><p>The cold workability behavior of the Ti6Al4V–5Cu alloy was investigated using a hot compression experiment in the temperature range of 450–650 °C and strain rates interval of 10^− 4 – 10^− 1 s^− 1 with strains of 0.4 and 0.6. Deformation mechanisms and microstructural evolution of the alloy are characterized by means of the Gleeble 3800 compression test, establishing constitutive relationship that relates the microstructure of the deformed specimen with process variables (temperature, strain rate, and strain). Unpleasant product features identified using a scanning electron microscope and an electron backscattered diffraction study, such as edge cracking defects caused by high strain conditions at low deformation temperatures (&lt; 450 °C) and faster strain rates. Grain boundary splitting occurs at the α/α phase interface. The splitting occurred because of the formation of weak structures due to the presence of aluminum as a major phase constituent element, indicating that pseudo super plasticity behavior existed via the sliding of α/α phase grains. The β – phase was found in relatively dense concentrations at the grain boundary teared region of the α/α phase interface, which helped to prevent the cracked edges along the grain boundaries from widening and propagating further. On the single α – phase region, the alloy activation energy (Q) monitored to be 29.58 kJ/mol. The alloy strain rate sensitivity (m) and power dissipation efficiency (η) were also calculated as 0.45 and 22.22%, respectively. Together with the microstructure evolution, true strain-stress curve, and generated processing map, Ti6Al4V–5Cu alloy was found with low metallurgical transformation ability during forming below 650 °C (&lt; 0.39T_m).</p></div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148236942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anisotropic behavior and micromechanisms of Ti60 alloy sheet","authors":"Yanxin Shao,&nbsp;Hui Zheng,&nbsp;Yongliang Zhang,&nbsp;Jue Wang,&nbsp;Yingjie Han,&nbsp;Tianzhang Zhao,&nbsp;Yingwei Qi,&nbsp;Yiqiang Mu","doi":"10.1007/s12289-026-02038-2","DOIUrl":"10.1007/s12289-026-02038-2","url":null,"abstract":"<div><p>The mechanical anisotropy of near-<span>(varvec{alpha })</span> titanium alloys under high-temperature service conditions plays a critical role in determining their formability and structural reliability. In this study, a Ti60 rolled plate was selected as the research material, and the evolution of tensile anisotropy along the RD, TD, and DD was systematically investigated at room temperature and within the temperature range of 720-840<span>(^circ )</span>C. The results reveal that the anisotropy of yield strength in the Ti60 plate can be divided into three distinct stages. At room temperature, the yield strengths along the TD and RD are comparable and higher than that along the DD, following the order TD&gt;RD&gt;DD. In the intermediate temperature range of 720-780<span>(^circ )</span>C, the yield strengths along the RD and DD become comparable and are lower than that along the TD, maintaining the same ranking of TD&gt;RD&gt;DD. At 840<span>(^circ )</span>C, the yield strengths along the TD and RD become comparable, while the anisotropy exhibits a reversal, following the order DD&gt;RD&gt;TD. Based on texture data obtained from EBSD analysis, the distributions and average values of the Schmid factors for the primary slip systems along the three directions were calculated. Combined with the temperature-dependent variations in the critical resolved shear stress (CRSS) of different slip systems, a slip activity parameter was introduced to quantitatively elucidate the origins of mechanical anisotropy. The results indicate that at room temperature, plastic deformation is primarily governed by prismatic slip and basal slip, together with non-thermally activated path-controlled mechanisms, which collectively influence the anisotropic behavior of the titanium alloy. The ranking of slip activity, DD&gt;RD&gt;TD, provides a reasonable explanation for the observed yield strength anisotropy at room temperature. In the intermediate temperature range of 720-780<span>(^circ )</span>C, plastic deformation becomes increasingly dependent on thermally activated dislocation slip, and the yield strength exhibits a strong negative correlation with slip activity. Although the CRSS values of various slip systems decrease significantly, their rates of reduction differ, leading to the concurrent activation of multiple <span>(varvec{langle arangle })</span>-type slip systems and resulting in the yield strength along the RD decreasing to a level comparable to that along the DD. When the temperature reaches 840<span>(^circ )</span>C, the dominant deformation mechanism undergoes a fundamental transition, shifting to grain boundary sliding-dominated deformation accompanied by the simultaneous activation of multiple dislocation slip systems, which ultimately leads to the reversal of yield strength anisotropy at 840<span>(^circ )</span>C.</p></div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148172124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Variants of cold extrusion of hollow semi-finished products for drawing with thinning","authors":"Vladymyr L. Kaliuzhnyi,&nbsp;Oleg E. Markov,&nbsp;Olexandr V. Kaliuzhnyi,&nbsp;Vadym M. Gornostai,&nbsp;Olha V. Kholiavik","doi":"10.1007/s12289-026-02040-8","DOIUrl":"10.1007/s12289-026-02040-8","url":null,"abstract":"<div><p>The article presents a comprehensive study of cold extrusion processes for hollow semi-finished products made of AISI 1015 steel, intended for further drawing with thinning. The finite element method was applied in the DEFORM environment using an elastic-plastic metal model. The results of traditional reverse extrusion and reverse extrusion with expansion in a movable die were considered and compared. The dependencies of the extrusion forces, the extraction of punches from deformed workpieces, and the ejection of semi-finished products from dies on the movement of tools were determined. The exact distributions of specific forces on punches, ejectors, and dies were established. The distributions of temperature, stress components, and deformations in the deformed metal of semi-finished products at the end of the extrusion processes were determined. The metal structure was evaluated by cold plastic deformation based on the distribution of deformation intensity. The results presented for the extrusion process with expansion in a movable die are new. When using a movable die, lower deformation forces and specific forces were obtained, as well as a more uniform and deeper processing of the metal structure, which has a positive effect on the mechanical properties of the semi-finished product. Based on the simulation results, an extrusion die was designed and manufactured, and experimental tests were conducted on a hydraulic press. A good match was found between the calculated and experimental data for the extrusion force. The study allows for the optimization of the manufacturing technology for precision semi-finished products and contributes to an increase in the service life of the forming tool.</p></div>","PeriodicalId":591,"journal":{"name":"International Journal of Material Forming","volume":"19 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148172123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}