Search Results (617)

Single point incremental forming (SPIF) represents a flexible manufacturing process capable of producing complex sheet metal parts without the need for dedicated forming dies. However, achieving high dimensional accuracy remains a major challenge due to phenomena such as elastic springback and localized deformation. In this context, the present study investigates the influence of tool-axis orientation on the dimensional accuracy of parts manufactured through robot-based single point incremental sheet forming (RB-SPIF). The experimental analysis considered two toolpath strategies (contour and spiral), two vertical step sizes (0.5 mm and 1 mm), and two tool-axis configurations (fixed tool-axis and wall-normal tool-axis orientation), resulting in eight experimental cases. The dimensional accuracy of the manufactured parts was evaluated using optical 3D scanning and cross-sectional profile analysis. The results show that the vertical step size has a significant influence on the resulting geometry, with smaller step sizes generating profiles closer to the nominal geometry. The toolpath strategy also affects the geometry, with spiral trajectories generally producing slightly improved profiles compared to contour strategies; however, this effect was not found to be statistically significant under the investigated conditions. Furthermore, the use of a wall-normal tool-axis configuration improves the agreement between the measured and nominal profiles by enhancing the contact conditions between the tool and the metal sheet surface. These findings indicate that adaptive tool-axis orientation represents a promising strategy for improving the dimensional accuracy of parts produced by robot-based incremental sheet forming systems. Full article

Environmentally friendly radiation shielding materials for medical institutions require lightweight characteristics and high flexibility as key performance indicators. One promising approach is the incorporation of lead-free materials that combine high-density shielding fillers with polymer matrices. High filler loading is necessary to maintain shielding performance while preserving the inherent flexibility of the polymer. However, during the mixing of shielding materials with polymers, microvoids may form. Therefore, strategies are required to enhance structural densification of the composite by reducing microvoid formation. This study aims to investigate the effects of interfacial design using an anchor–chain dispersant (APTES: 3-aminopropyltriethoxysilane) on micropore formation, effective density, and X-ray shielding performance in highly filled tungsten/thermoplastic polyurethane (TPU) composites. TPU-based composite shielding sheets containing 75–90 wt% tungsten were fabricated. The dispersant (APTES) can adsorb onto the surface of metal particles and form a stabilization layer. In this study, the observed reduction in particle agglomeration and porosity upon addition of the dispersant suggests that interfacial stabilization was induced. As a result, in the 85 wt% composite sheet, the porosity decreased from 5.89% without the dispersant to 0.56% with the dispersant, leading to an improvement in the densification level and effective density of the sheet. Under the same thickness condition (0.25 mm), the dispersant-containing sheet exhibited a shielding efficiency that was 3–4% p higher than that of the sheet without dispersant in the 100–120 kVp range. Meanwhile, as the tungsten content increased, the overall density and shielding efficiency of the sheets also increased. At 90 wt% tungsten loading, the composite demonstrated shielding performance approaching that of conventional lead shielding even at a reduced thickness. These results indicate that interfacial design using an anchor–chain dispersant is an effective processing strategy for improving density uniformity and radiation shielding performance in highly filled tungsten/TPU composite shielding materials by controlling microvoid formation. Full article

Background: Posterior spinal fusion (PSF) for adolescent idiopathic scoliosis (AIS) is a standard procedure with recognized long-term complications that may emerge years after surgery. Informed consent requires disclosure of material risks, but it is unclear whether these long-term sequelae are consistently communicated. This study systematically reviewed publicly available consent materials to assess disclosure of evidence-based long-term complications of PSF for AIS. Methods: Official websites of spine, orthopedic, and neurosurgical societies, along with major hospitals across North America, South America, Europe, and Australia, were searched for publicly available informed consent forms and patient information leaflets related to PSF for AIS. Documents were assessed for explicit mention of predefined long-term complications: chronic pain/health-related quality of life, pseudoarthrosis, adjacent segment degeneration, future surgery, pulmonary function impact, late infection, local tissue reaction to metal debris, and pregnancy-related issues. Disclosure frequencies were calculated. Results: Thirty-one documents from ten countries were included. Immediate perioperative risks were almost universally reported, whereas long-term complications were inconsistently disclosed. Reporting frequencies were: pseudoarthrosis, 80.6% (n = 25); future surgery, 67.7% (n = 21); adjacent segment degeneration, 51.6% (n = 16); chronic pain, 48.4% (n = 15); local tissue reaction to metal debris, 38.7% (n = 12); late infection, 25.8% (n = 8); pregnancy-related issues, 22.6% (n = 7); and pulmonary impact, 9.7% (n = 3). Conclusions: Publicly available consent materials for AIS surgery incompletely disclose long-term complications compared with the published evidence. However, written information sheets and consent forms represent only one component of the consent process. Consistently with the patient-centered standard articulated in Montgomery v Lanarkshire Health Board, informed consent should include discussion of material risks, benefits, reasonable alternative treatments including standard care, and the option of no treatment, with disclosure tailored to what matters to the patient and family. Updating written materials to better reflect lifelong risks may strengthen one important component of informed consent and shared decision-making for patients and families. Full article

This study presents a comparison between the results of process parameter optimization for the deep drawing of an AA5754-O automotive fuel tank, which utilizes two different objective functions. The first objective function is the maximum thinning percentage (max. %Thinning) of the formed part, which is a conventional formability index. The second is Q-value, a metric derived from the Thinning Limit Diagram that accounts for both necking-prone (excessive thinning) and wrinkling-prone (thickening) regions. The experiments were conducted using finite element simulation to model the forming behavior under an inscribed central composite design within the response surface methodology. Three process parameters, which are well known to be important for controlling material flow and achieving a balance between wrinkling and excessive thinning in deep drawing, were varied: blank holder pressure, the height of the male drawbead, and the radius of the female drawbead. Refined second-order response surface models were developed for both objective functions. Optimization based on the response surface models showed that, for the max. %Thinning objective function, the final part exhibited 19.46% maximum thinning but suffered from substantially higher wrinkling, as indicated by a maximum thickening of 36.39%. In contrast, the Q-value-based optimization resulted in a more balanced formability condition, with maximum thinning of 21.74% and maximum thickening of 13.17%. Moreover, the normalized density of elements in the safe zone of the Thinning Limit Diagram was higher, indicating an improvement in formability robustness. Therefore, this study highlights the limitations of conventional thinning-based optimization and demonstrates the potential of the Q-value as an extended practical quantitative formability tool that can simultaneously address necking and wrinkling in sheet metal forming, as presented through the studied automotive fuel tank on behalf of complex components. Full article

This study addresses energy-response prediction in sheet metal forming under small-data conditions, where conventional simulation-based approaches are computationally expensive and data acquisition is limited. We propose an Energy-Informed Neural Network (EINN) framework that integrates energy consistency constraints and a Fenchel–Young duality-based loss to enforce physically consistent learning without relying on explicit governing equations. Using a dataset generated from 54 finite element simulations across 18 materials and three friction conditions, the proposed model demonstrates significant performance improvements. Specifically, EINN achieves an RMSE of 0.0096, MAE of 0.0065, and R² of 0.9778, corresponding to approximately a 48% reduction in RMSE compared to the best baseline model. Compared to an energy-constrained neural network without the Fenchel–Young term, prediction error is reduced by approximately 50% with substantially improved stability. These results indicate that embedding energy-consistent dual structures enhances both prediction accuracy and robustness, providing a practical surrogate modeling approach for process optimization in sheet metal forming under limited data availability. Full article

Arsenic contamination, mainly in the arsenate (As(V)) form, continues to pose a serious threat to groundwater quality worldwide due to its long-term stability and toxicity at very low levels. Herein, we demonstrate, for the first time, a three-dimensional graphene oxide-based nanocomposite composed of Cu nanoparticle-doped, amino-functionalized UiO-66 (Cu/UiO-66-NH₂) anchored on a graphene oxide framework (Cu/UiO-66-NH₂@GO) as a novel and efficient nanosorbent for the rapid removal of As(V) in groundwater-like solutions. The nanocomposite was characterized by SEM and HRTEM to confirm the hybrid structure and by XRD, N₂ adsorption–desorption isotherms, and XPS to investigate crystallinity, porosity, and surface chemistry. The derived material exhibited a highly dispersed morphology and performed rapid arsenate solid-phase extraction to attain equilibration within 10 min and was effective for a wide pH range of 2–11. The best fit for the kinetic profiles was provided by the pseudo-second-order model. Interestingly, the maximum adsorption capacity of 747.9 mg g⁻¹ at pH 6.8 was achieved, demonstrating the benefits of the complementary pairing of dispersive GO sheets and Zr-MOF adsorption domains with Cu-derived active sites. Mechanistically, the enhanced uptake is ascribed to a combination of effects, including electrostatic pre-concentration, ligand exchange, and inner-sphere complexation at metal-oxo nodes; spectroscopic analysis (XPS and FTIR) suggests that the majority of arsenate is immobilized via a strong Zr-O-As bond at coordinatively unsaturated Zr centers, which is in line with t-ZrO₂-like surface domains formed within the nanocomposite. The embedded GO support inhibits further framework interpenetration and enhances active site availability and mass transport, leading to fast and high-capacity arsenate capture in groundwater samples with related conditions. Taken together, this work presents a powerful design concept that integrates unique GO-supported, Cu-modified UiO-66-NH₂ with Zr-O binding motifs to afford high-rate remediation nanocomposites, providing an excellent platform for next-generation arsenate remediation materials. Full article

Two trinuclear cobalt (Co₃)-based metal–organic frameworks, [Co₃(CHDC)₃(py)₄] (2; CHDC = trans-1,4-cyclohexanedicarboxylate, py = pyridine) and [Co₃(CHDC)₃(mpy)₂]· 2DMF (3; mpy = 4-methylpyridine, DMF = N,N-dimethylformamide), were successfully prepared via the solvothermal reactions of Co(NO₃)₂·6H₂O, trans-1,4-cyclohexanedicarboxylic acid, and py/mpy in DMF solution. Single crystal X-ray diffraction analyses revealed that the Co₃-secondary building units (SBUs) in 2 and 3 adopt Co^octahedral···Co^octahedral···Co^octahedral and Co^tetrahedral···Co^octahedral···Co^tetrahedral coordination environments, respectively, and are connected by six CHDC linkers to form two-dimensional sheet structures with a triangular lattice. The structural differences of these Co₃-SBUs led to clear differences in the magnetic properties and electronic spin states of 2 and 3; temperature-dependent magnetic susceptibility measurements revealed that 2 and 3 exhibited antiferromagnetic and ferromagnetic interactions, respectively, within the Co₃-SBUs. These experimental magnetic results are consistent with the density-functional theory calculations of the model structures of Co₃-SBUs, which indicate that the most stable spin states are S = 3/2 for 2 and S = 9/2 for 3. Full article

The selection of deformation mechanisms in hexagonal close-packed (HCP) metals is strongly influenced by both crystallographic orientation and macroscopic deformation constraints. In commercially pure titanium, plastic deformation under constrained loading conditions involves a complex interplay between dislocation slip and deformation twinning, whose respective activation cannot be fully described by classical stress-based criteria. In this study, the mechanical origin of slip and twinning variant selection in commercially pure titanium subjected to plane strain compression is investigated experimentally. Plane strain compression is used as a canonical loading condition representative of constrained deformation paths encountered in sheet metal forming. Interrupted in-situ electron backscatter diffraction is combined with slip trace and twin variant analyses to identify the active deformation mechanisms at the grain scale. Resolved shear stress calculations show that stress-based criteria provide a necessary first-order condition for the activation of both slip and twinning systems. While the Schmid factor reasonably predicts part of the observed slip activity, it fails to uniquely determine the selection of active twinning variants. A kinematic analysis reveals that twinning variant selection is governed by the compatibility between the deformation induced by twinning and the macroscopic strain constraints imposed by plane strain compression. Only variants whose deformation accommodates compression along the loading axis, extension along the free in-plane direction, and minimal strain along the constrained in-plane direction are preferentially activated. These results demonstrate that deformation mechanism selection in HCP titanium under constrained loading conditions results from a combined effect of resolved shear stress and kinematic compatibility. The proposed framework provides a physically grounded basis for interpreting deformation-induced texture evolution and offers clear perspectives for the development of crystal plasticity models incorporating twinning under complex strain paths. Full article

Friction in sheet metal forming processes is a key factor determining the material flow behavior and surface quality of products. Controlling friction conditions is crucial for ensuring the stability of the forming process. This article focuses on evaluating the influence of strip sample orientation, tool surface roughness, and contact forces on the coefficient of friction in the strip drawing test. Low-carbon, deep-drawing-quality steel sheets produced by rolling were used as the test material. Due to the complex influence of numerous parameters on the coefficient of friction, analysis of variance (ANOVA) was employed to evaluate the experimental results. A two-factor interaction model was used to analyze the data from the strip drawing test. An adequate precision of approximately 104.74 and coefficients of determination of R² = 0.9367, an adjusted R² = 0.9350, and a predicted R² = 0.9331 indicated that the regression model was sufficiently fitted to provide reliable predictions. It was found that the influence of sheet orientation on the coefficient of friction, under a varying load force, was minor; the difference in the CoF between the two sample orientations did not exceed about 0.01. On the other hand, among all the parameters of the strip drawing test, the load force was the decisive factor affecting the CoF. A trend was observed in which the coefficient of friction increased with a decreasing average roughness of the countersamples and load force. Full article

The application of machine learning (ML) methods enables the modeling of sheet metal friction phenomena based on experimental data, allowing for the prediction of the coefficient of friction (CoF) under various operating conditions. The aim of this article is to compare the predictive capability of a wide range of ML algorithms trained on the results of the strip drawing test. The variable parameters in the strip drawing test were sheet orientation, load, sample orientation relative to the sheet rolling direction, and the drawing quality of the low-carbon steel sheet metal. Based on the coefficient of determination (R²) and the root mean squared error (RMSE), it was determined that the best predictive performance was achieved by a trilayer neural network (R² = 0.986, RMSE = 0.0025). It was found that the CoF decreased with increasing countersample surface roughness and load. Meanwhile, the orientation of strip samples relative to the sheet rolling direction had a statistically insignificant effect on the CoF. Based on SHapley Additive exPlanations (SHAP) values, it was shown that the average roughness of the countersamples and the load had the most significant influence on the friction coefficient. This was also confirmed using the F-test and permutation importance analysis of the friction process parameters. Full article

The sustainable recycling of valuable metals from spent lithium-ion batteries (LIBs) is imperative for closing the resource loop. This study presents an integrated strategy for the stepwise recovery of metals from spent cathode sheets by in situ thermal reduction and selective leaching. The in situ thermal reduction converted the cathode material into a mixture of Li₂CO₃, LiAlO₂, Ni, Co, NiO, and CoO while simultaneously liberating the cathode materials from the Al current collector through binder removal. A combined process of water leaching, wet sieving, and filtration successfully achieved the separation and enrichment of Li-rich aqueous solution (near 60% Li), Al-rich coarse fraction (over 87% Al), and fine powder enriched with transition metals (over 90% of Ni, Co, and Mn). The pyrolysis gases released from binder decomposition were the key driver for forming Li₂CO₃, whereas the concurrent generation of LiF and LiAlO₂ limited direct water leaching efficiency. An alkaline leaching step was therefore introduced to co-extract Al and the associated Li from LiAlO₂, followed by an acid leaching step that recovered over 96% of the transition metals from the treated residue without external reductants. Complete mass balance analysis shows that the integrated process achieved overall recoveries of 91.86% for Li, 91.93% for Ni, 92.23% for Co, and 92.61% for Mn from all the combined leachate streams. Consequently, this work provides a reagent-saving, stepwise hydrometallurgical process for the comprehensive recycling of valuable metals from spent LIBs. Full article

Surface quality remains a critical factor limiting the widespread adoption of incremental sheet forming (ISF). This study proposes a novel acetal wheel-type rotating tool and systematically investigates the influence of tool structure and material on surface quality through experimental and numerical analyses. The results demonstrate that the acetal tool significantly improves surface quality by 32–40% compared to conventional metal ball tools, primarily due to enhanced sheet–tool contact area that effectively suppresses the formation of surface waviness topography. Furthermore, the wheel-type tool reduces contact stress by over 37.5% while improving surface quality by 21.1% relative to traditional metal ball tools. Notably, the acetal rotating wheel achieves a 32.0% surface quality enhancement while eliminating tool wear, highlighting its industrial applicability. These findings provide both a mechanistic understanding and a practical tooling solution, highlighting significant potential for improving surface quality in ISF industrial applications. Full article

This work aims to evaluate the economic and environmental performance of hybrid additive manufacturing (HAM) chains with metal forming operations in comparison with conventional manufacturing approaches. The approach integrates processes such as Wire-Arc Directed Energy Deposition (DED-Arc), machining, and incremental sheet forming to combine material deposition, shaping, and finishing within a single processing chain. To support this, a process-based cost model (PBCM) was developed to estimate production costs by linking process parameters with technological and operational variables and implementing computer-assisted modeling of the processing chain for identification of the production costs and corresponding key cost drivers. In parallel, a cradle-to-gate Life Cycle Assessment (LCA) was performed to evaluate environmental impacts across the stages of the HAM chain. The results indicate that direct labor, material, and machine usage are the primary cost drivers in the HAM chain. Compared to conventional chains of machining from solid or die casting, HAM achieves high reductions in production cost, from 67.8% to 84.5%, and in environmental impact of up to one order of magnitude, due to lower material consumption and independence from dedicated tooling. Overall, this work provides an integrated framework for the economic and environmental assessment of HAM, laying the foundation for future industrial implementation. Full article

To address the issues of excessive sheet metal thinning and geometric deviation in single point incremental forming (SPIF), this paper proposed a bi-objective process parameter optimization framework for Al1060 sheet based on a multilayer perceptron (MLP) surrogate model and an improved multi-objective grey wolf optimization (IMOGWO) algorithm. Finite element simulations based on ABAQUS were conducted to generate a dataset considering variations in tool radius, initial sheet thickness, tool path strategy, step depth and forming angle. The trained MLP was used as the objective function in the optimization process to enable the rapid prediction of forming quality. The IMOGWO algorithm, enhanced by the Spm chaotic mapping initialization, an improved convergence coefficient updating mechanism and associative learning mechanism, was then employed to efficiently search for Pareto optimal solutions. For a truncated conical component case, optimal parameter sets were selected from the Pareto front via the entropy-weighted TOPSIS method for order preference by similarity to an ideal solution. Experimental verification showed close agreement with the simulated results, with relative errors of only 0.58% for the thinning rate and 3.10% for the geometric deviation. This validation demonstrates the feasibility and potential of the proposed method and its practical potential for improving the quality of SPIF forming. Full article

Friction stir spot welding (FSSW) is a novel variant of Friction Stir welding (FSW), developed by Mazda Motors and Kawasaki Heavy Industries to join similar and dissimilar materials in a solid state. It is an economic and environmentally friendly alternative to resistance spot welding (RSW). The FSSW technique, however, includes some structural defects imbedded within the weld joint, such as keyhole formation, hook crack, and bond line oxidation challenging the joint strength. The unique properties of nanomaterials in the reinforcement of metal matrices motivated researchers to enhance the FSSW joints’ strength. Previous studies successfully fabricated nano-reinforced FSSW joints. At different volumetric ratios of nano-reinforcement, nanoparticles may agglomerate due to inefficient stirring of the welding tool pin, forming stress concentration sites and brittle phases, affecting tensile and fatigue strength under static and cyclic loading conditions, respectively. This work investigated how the welding tool pin affects stirring efficiency by controlling the distribution of a nano-reinforcing material within the joint stir zone (SZ), and thus the tensile and fatigue strength of the FSSW joints. Sheets of AA6061-T6 of 1.8 mm thickness were used as a base material. In addition, graphene nanoplatelets (GNPs) with lateral sizes of 1–10 µm and thicknesses of 3–9 nm were used as nano-reinforcements. GNP-reinforced FSSW specimens were prepared and successfully fabricated. Optical microscope (OM) and field emission scanning electron microscope (FE-SEM) methods were employed to visualize the GNPs’ incorporation into the SZs of the FSSW joints. Micrographs of as-welded specimens showed lower formations of scattered, clustered GNPs achieved by the threaded pin tool compared to continuous agglomerations observed when the cylindrical pin tool was used. Tensile test results revealed a significant improvement of about 30% exhibited by the threaded pin tool compared to the cylindrical pin tool, while fatigue test showed an improvement of 46–24% for the low- and high-cycle fatigue, respectively. Full article