Fusion Process Research Articles

Quantum machine learning for additive manufacturing process monitoring

Machine learning is useful for analyzing and monitoring complex manufacturing processes. However, it has several limitations including the curse-of-dimensionality and lack of training data. In this paper, we propose a quantum machine learning strategy to tackle these challenges. Quantum support vector machine is applied to identify the states of machines in fused filament fabrication process based on acoustic emission data. Quantum convolutional neural network is used to detect spatters in laser powder bed fusion process based on coaxial optical images. Our results show that quantum machine learning can achieve the similar accuracy levels of predictions by classical machine learning counterparts, but with exponentially fewer parameters.

SFFN: Serial Feature Fusion Network for Visual Tracking

Abstract Recently, The Transformer tracker has excellent visual target tracking performance. The parallel arrangement of structural feature fusion networks proposed by the TransT tracker makes the Transformer learn the erroneous information. To address the issue, this paper proposes the SFFN tracker. It constructed a serial feature fusion network with the Transformer module in a serial interleaved arrangement to avoid learning erroneous information during the Transformer feature fusion process. The experiments show that SFFN performs well on the GOT-10k dataset, and it improves over TransT by 2.6%, 2.6%, and 2.3% in AO, SR0.5, and SR0.75, respectively.

A finite volume–based thermo-fluid-mechanical model of the LPBF process

The multi-physics coupling feature of the laser powder bed fusion (LPBF) process poses great challenges to numerical models regarding computational fidelity and efficiency. This paper proposed a finite volume–based model for predicting integrated thermo-fluid-mechanical behaviors of the LPBF process. The model directly unifies the heat transfer, fluid flow and solid mechanics simulations within a predefined mesh, enabling simultaneous solutions for the fluid domain under Eulerian description and the solid domain under Lagrangian description. Three benchmark tests accounting for individual problems were conducted to validate the model's accuracy and effectiveness. Track-scale LPBF simulations were performed to unravel the intricate interplay between thermal, fluid and mechanical behaviors. The numerical predictions of surface morphologies, molten pool dynamics and melt track dimensions aligned well with the experimental observations. The spatiotemporal evolution of transient thermal stress was accurately captured and the predicted residual stress field showed consistency with nanoindentation measurements. The proposed model was found robust in simultaneously predicting the temperature distribution, melt flow and residual stress evolutions of the LPBF process, and showed strong potential for addressing other similar multi-physics coupling problems.

Improvement of strength in single-lap adhesive joints of AlSi10Mg alloys fabricated by laser powder bed fusion

This study deals with the mechanical strength of metallic single-lap joints bonded with adhesive and fabricated by Additive Manufacturing (AM). To this aim, AlSi10Mg alloy has been used to manufacture the specimens using Laser Powder Bed Fusion (LPBF) process. Based on a series of tensile tests on AMed joints, the mechanical strength of the joints was determined. In this paper, a procedure is recommended to improve the strength of AMed single-lap joints. Particularly, a notch is introduced in the adherends, which plays a crucial role in the mechanical strength and failure load of the joints. Therefore, a series of single-lap joints with notch have been printed and examined. Based on the conducted tests, failure load and fracture behavior of the joints with and without notches have been compared. Here, we used the digital image correlation technique to determine strain fields on the surface of the joints. In addition, a series of finite element models has been developed to investigate the stress distributions in the adhesive and simulate the load-carrying behavior of the joints. The obtained results confirm the effective role of notches in adhesive joints for strength improvement of AMed single-lap joints. The outcome of this study can be utilized for fabrication of AMed metallic joints with a higher mechanical strength.

Evaluation of MgO-rich materials obtained from Ferronickel slag for CO2 sequestration

Because it has a high magnesium content, ferronickel (FeNi) slag is a potential alternative material for CO2 sequestration. The slag can be pretreated by alkali fusion with NaOH to obtain MgO-rich materials. In this study, the potential of this MgO-rich material for CO2 sequestration was investigated using MgO from FeNi slag (MgO-FS) and MgNa2SiO4 from FeNi slag (MNA). A MgO reagent (MgO-R) and FeNi slag were used as reference materials. The carbonation process was carried out using a batch autoclave with various liquid-to-solid (L/S) ratios, initial pressures, times, and CO2 concentrations. The MgO-FS effectively captured CO2 and had a carbonation performance comparable to that of MgO-R. The degrees of carbonation for MgO-R, MgO-FS, and MNA were 68.43 %, 65.53 %, and 39.40 %, respectively, when carbonation was carried out at 423 K and 8 bar with an L/S ratio of 10 mL/g and pure CO2 for 9 h. Combination of the FeNi slag alkali fusion process (1:2 FeNi slag/NaOH mass ratio, 773 K, and 4 h) with water washing and carbonation (4 bar, 423 K, 10 mL/g L/S ratio, 3 h, and pure CO2) gave a CO2 uptake efficiency of 0.119 ± 0.004 g CO2/g FeNi slag. The results of the degree of carbonation (i.e. 65.53 %), X-Ray diffraction spectra (magnesite mineral peak), and scanning electron microscope observations (magnesite crystal appearance) provide evidence that MgO-FS is an effective alternative material for indirect CO2 sequestration.

Pixel-Level Decision Fusion for Land Cover Classification Using PolSAR Data and Local Pattern Differences

Combining various viewpoints to produce coherent and cohesive results requires decision fusion. These methodologies are essential for synthesizing data from multiple sensors in remote sensing classification in order to make conclusive decisions. Using fully polarimetric Synthetic Aperture Radar (PolSAR) imagery, our study combines the benefits of both approaches for detection by extracting Pauli’s and Krogager’s decomposition components. The Local Pattern Differences (LPD) method was employed on every decomposition component for pixel-level texture feature extraction. These extracted features were utilized to train three independent classifiers. Ultimately, these findings were handled as independent decisions for each land cover type and were fused together using a decision fusion rule to produce complete and enhanced classification results. As part of our approach, after a thorough examination, the most appropriate classifiers and decision rules were exploited, as well as the mathematical foundations required for effective decision fusion. Incorporating qualitative and quantitative information into the decision fusion process ensures robust and reliable classification results. The innovation of our approach lies in the dual use of decomposition methods and the application of a simple but effective decision fusion strategy.

MMAE: A universal image fusion method via mask attention mechanism

As an important carrier of data, images contain a huge amount of information. The purpose of image fusion is to integrate the information from source images into a single image. Since the source images are from the same scene, there is much redundant information between them. Common fusion methods do not filter this information and the fusion process is often disturbed. This leads to degradation in the quality of the reconstructed fused image. To solve this problem, this paper explores the strategies of information filtering and fusion control, and proposes a universal image fusion method based on the mask attention mechanism. It can be divided into pre-training stage and formal fusion stage. In the pre-training stage, coarse-grained mask maps are generated which are employed to improve the mask autoencoder and the mask attention mechanism. In the image formal fusion stage, with the help of coarse-grained mask maps, the mask autoencoder changes the process of random masking and discards redundant features between source images. Meanwhile the mask attention mechanism focuses on the distinctions between various source images and retains effective complementary information. Qualitative and quantitative extension experiments on different modal datasets validate the applicability of the model in multi-focus image fusion, infrared and visible image fusion, and medical image fusion. Our method achieves excellent performance in all these tasks and performs better than existing fusion methods. Our code is publicly available at https://github.com/xiangxiang-wang/MMAE.

Exploring fusion domain: Advancing infrared and visible image fusion via IDFFN-GAN

Infrared (IR) and visible (VI) images are crucial in applications such as surveillance and night vision, where each modality provides complementary information—IR captures thermal details, while VI captures textures. Fusing these images is essential to combine their strengths, resulting in a more comprehensive and informative image. In this work, we introduce the “fusion domain” concept, a unique distribution that optimally blends IR and VI features. Our primary contribution is developing the Intermediate Domain Feature Fusion Network (IDFFN), which employs an MLP to learn the optimal domain factor for this fusion. Integrated with the IDFFN-GAN’s dual discriminators, our approach refines the fusion process to produce images that better preserve thermal and texture details from the proposed fusion and gradient domains. Experimental results demonstrate that our method achieves a 5% boost in Entropy (EN), a 50% rise in Spatial Frequency (SF), a 58% improvement in Average Gradient (AG), a 10% enhancement in Standard Deviation (SD), and a remarkable 198% increase in NAB/F compared to state-of-the-art techniques, ensuring superior retention of specific features from both modalities.

Molecular mechanism and structure-guided humanization of a broadly neutralizing antibody against SFTSV.

Severe fever with thrombocytopenia syndrome virus (SFTSV) is a novel tick-borne bunyavirus that causes severe fever with thrombocytopenia syndrome (SFTS), with a high mortality rate of up to 30%. The envelope glycoproteins of SFTSV, glycoprotein N (Gn) and glycoprotein C (Gc), facilitate the recognition of host receptors and the process of membrane fusion, allowing the virus to enter host cells. We previously reported a monoclonal antibody, mAb 40C10, capable of neutralizing different genotypes of SFTSV and SFTSV-related viruses. However, the specific neutralization mechanism is poorly understood. In this study, we elucidated the high-resolution structure of the SFTSV Gn head domain in complex with mAb 40C10, confirming that the binding epitope in the domain I region of SFTSV Gn, and it represented that a novel binding epitope of SFTSV Gn was identified. Through in-depth structural and sequence analyses, we found that the binding sites of mAb 40C10 are relatively conserved among different genotypes of SFTSV and SFTSV-related Heartland virus and Guertu virus, elucidating the molecular mechanism underlying the broad-spectrum neutralizing activity of mAb 40C10. Furthermore, we humanized of mAb 40C10, which is originally of murine origin, to reduce its immunogenicity. The resulting nine humanized antibodies maintained potent affinity and neutralizing activity. One of the humanized antibodies exhibited neutralizing activity at picomolar IC50 values and demonstrated effective therapeutic and protective effects in a mouse infection model. These findings provide a novel target for the future development of SFTSV vaccines or drugs and establish a foundation for the research and development of antibody therapeutics for clinical applications.

Factorization for J/ψ leptoproduction at small transverse momentum

Nonrelativistic Quantum Chromodynamics (NRQCD) breaks down in the region of low transverse momentum, where the transverse momentum of the produced quarkonium state is sensitive to multiple scattering with the incoming hadron and to soft gluon radiation. In this kinematic regime, the transverse-momentum-dependent (TMD) factorization framework is required, promoting the long-distance matrix elements (LDMEs) of NRQCD to the so-called TMD shape functions (TMDShFs), which encode both the soft gluon radiation and the formation of the heavy-quark bound state. In this work, we apply an effective-field theory approach (combining NRQCD and SCET) to the photon-gluon fusion process in inclusive J/ψ leptoproduction. We derive a factorization theorem for the cross section in terms of TMDShFs, compute these quantities at next-to-leading order, establish their evolution, and study their matching onto the corresponding LDMEs in the high-transverse-momentum region. Our results are particularly relevant to the Electron-Ion Collider, where J/ψ leptoproduction can be used to probe gluon transverse-momentum-dependent parton distribution functions (gluon TMDPDFs).

Fusion-driven fault diagnosis based on adaptive tuning feature mode decomposition and synergy graph enhanced transformer for bearings under noisy conditions

Bearing fault diagnosis is critical for maintaining the reliability of health monitoring in electromechanical systems. However, traditional feature extraction methods often struggle to accurately capture fault information in complex environments. This paper proposes an adaptive tuning feature mode decomposition (ATFMD) method, based on the intrinsic signal characteristics, to effectively extract robust features. ATFMD dynamically adjusts to complex fault signals, providing more representative feature inputs and pruning redundant features induced by noise. Additionally, given the limitations of single-dimensional feature domains in fully revealing fault information, this study constructs feature topology graphs by mapping spatial phase and time–frequency characteristics, offering a comprehensive representation of fault information. To achieve complementary fusion of fault information within the feature topological graph, this paper proposes the synergy graph enhanced transformer (SGET). SGET optimizes the fusion process by reinforcing feature interactions through its synergy graph representation module. Additionally, a hierarchical cross-attention mechanism is employed to modulate attention distribution across feature dimensions, enhancing the sensitivity to critical features during fusion. Experimental validation was conducted on two distinct rotating machinery transmission systems. The results demonstrate that the proposed method maintains exceptional robustness and generalization, even in the presence of severe noise and complex fault conditions. Compared to the leading methods, including MS-DGCNs, CapsFormer, TFT, and ConvFormer, the proposed method achieves notable accuracy improvements of 8.13 %, 8.71 %, 11.94 %, and 6.25 %, respectively, under challenging conditions.

A Defect Detection Method for Grading Rings of Transmission Lines Based on Improved YOLOv8

Detecting defects in aerial images of grading rings collected by drones poses challenges due to the structural similarity between normal and defective samples. The small visual differences make it hard to distinguish defects and extract key features. Additionally, critical defect features often become lost during feature fusion. To address these issues, this paper uses YOLOv8 as the baseline model and proposes an improved YOLOv8-based method for detecting grading ring defects in transmission lines. Our approach first integrates the CloAttention and C2f modules into the feature extraction network, enhancing the model’s ability to capture and identify defect features in grading rings. Additionally, we incorporate CARAFE into the feature fusion network to replace the original upsampling module, effectively reducing the loss of critical defect information during the fusion process. Experimental results demonstrate that our method achieves an average detection accuracy of 67.6% for grading ring defects, marking a 6.8% improvement over the baseline model. This improvement significantly enhances the effectiveness of defect detection in transmission line grading rings.

SDAM: A dual attention mechanism for high-quality fusion of infrared and visible images.

Image fusion of infrared and visible images to obtain high-quality fusion images with prominent infrared targets has important applications in various engineering fields. However, current fusion processes encounter problems such as unclear texture details and imbalanced infrared targets and texture detailed information, which lead to information loss. To address these issues, this paper proposes a method for infrared and visible image fusion based on a specific dual-attention mechanism (SDAM). This method employs an end-to-end network structure, which includes the design of channel attention and spatial attention mechanisms. Through these mechanisms, the method can fully exploit the texture details in the visible images while preserving the salient information in the infrared images. Additionally, an optimized loss function is designed to combine content loss, edge loss, and structure loss to achieve better fusion effects. This approach can fully utilize the texture detailed information of visible images and prominent information in infrared images, while maintaining better brightness and contrast, which improves the visual effect of fusion images. Through conducted ablation experiments and comparative evaluations on public datasets, our research findings demonstrate that the SDAM method exhibits superior performance in both subjective and objective assessments compared to the current state-of-the-art fusion methods.

Growth defect of domain III glycoprotein B mutants of human cytomegalovirus reverted by compensatory mutations co-localizing in post-fusion conformation.

Cell entry is a crucial step for a virus to infect a host cell. Human cytomegalovirus utilizes glycoprotein B (gB) to fuse the viral and host cell membranes upon receptor binding of gH/gL-containing complexes. Fusion is mediated by major conformational changes of gB from a metastable pre-fusion to a stable post-fusion state whereby the central trimeric coiled-coils, formed by domain (Dom)III α helices, remain structurally nearly unchanged. To better understand the role of the stable core, we individually introduced three potentially helix-breaking or one disulfide bond-breaking mutation in the DIII α3 to study different aspects of the viral behavior upon long-term culturing. Two of the three helix-breaking mutations, gB_Y494P and gB_I495P, were lethal for the virus in either fibroblasts or epithelial cells. The third substitution, gB_G493P, on the other hand, displayed a delayed replication and spread, which was more pronounced in epithelial cells, hinting at an impaired fusion. Interestingly, the disulfide bond-breaker mutation, gB_C507S, performed strikingly differently in the two cell types - lethal in epithelial cells and an atypical phenotype in fibroblasts, respectively. Replication curve analyses paired with the infection efficiency, the spread morphology, and the cell-cell fusogenicity suggest a dysregulated fusion process, which could be reverted by second-site mutations mapping predominantly to gB DomV. Our findings underline the functional importance of a stable DomIII core for a well-regulated DomV rearrangement during fusion.IMPORTANCEHuman cytomegalovirus (HCMV) can establish a lifelong infection. In most people, the infection follows an asymptomatic course; however, it is a major cause of morbidity and mortality in immunocompromised patients or neonates. HCMV has a very broad cell tropism, ranging from fibroblasts to epi- and endothelial cells. The virus uses different entry pathways utilizing the core fusion machinery consisting of glycoprotein complexes gH/gL and glycoprotein B (gB). The fusion protein gB undergoes fundamental rearrangements from a metastable pre-fusion to a stable post-fusion conformation. Here, we characterized the viral behavior after the introduction of four single-point mutations in the gB central core. These led to various cell type-specific atypical phenotypes and the emergence of compensatory mutations, demonstrating an important interaction between domains III and V. We provide a new basis for the development of a structurally and functionally altered gB, which can further serve as a tool for drug and vaccine development.

Synergistic impact of scan strategy and scan angles in laser powder bed fusion process on mechanical, tribological and cell viability properties of porous 316L SS structure

Poor load bearing ability and concentrated stress within cross-linked porous structures was found to be the major cause for the mechanical and wear failure of SS (Stainless Steel) 316L implants. Therefore, the present study introduces a novel scan pattern to enhance the mechanical and wear properties. Importantly, the role of porous structures on the constituents and formation of Tribo-film regimes under the simulated body fluid (SBF) condition were assessed using the X-ray photoelectron spectroscopy (XPS). Furthermore, the impact of the surface roughness of porous structures on the cell adhesion and cytotoxicity were explored. Various cross-linked porous structures are produced at three different scanning rotation angles (0°, 45°, and 90°) using the Laser powder bed fusion (LPBF) process. Morphology analysis reveals balling and stair-case effects at 0°, controlled for structures built at 45° and 90°. Porous-90° structure exhibits negative skewness and a platykurtic surface with low peaks and more valleys. It demonstrates higher strength with low density due to better particle fusion, net-like structure, and uniform element distribution. X-ray photoelectron spectroscopy (XPS) evaluates the impact of porous structures on Tribo-film regimes in simulated body fluid. Surface roughness effects on cell adhesion and cytotoxicity are also investigated. Cross linked porous structures presented two major compression failure modes include wrinkling and diagonal shearing. The densified structure of Porous-45° reduces contamination and cell death, facilitating stable cell growth. Tribo-film formation and load bearing ability of Porous-90° structure was better than the other structures, due to the cross-linked netlike structure and further more detailed in the XPS study.

On the Creation of a Material Bond between L-PBF-Manufactured AZ91 and Ti-6Al-4V Components in the Context of Medical Applications.

Within the scope of these investigations, the feasibility of a material bond between Ti-6Al-4V and the magnesium alloy AZ91 is analyzed. Ti-6Al-4V is frequently used for implants due to its biocompatibility, corrosion resistance, and specific strength. However, depending on the surface quality, the attachment behavior of the bone to the implant varies. Magnesium implants promote the regeneration of bone tissue and biodegrade as the bone tissue heals. Combining the properties of both materials in one implant enables a reduced implant volume and increased stability. For this reason, this study aims to demonstrate the feasibility of creating a material bond between the materials Ti-6Al-4V and AZ91. For this purpose, Ti-6Al-4V truncated cones and AZ91 sleeves were produced using the additive manufacturing process of laser powder bed fusion (L-PBF). The as-built sleeves were then pressed onto machined truncated cones. Since zinc serves as a lubricant and has good diffusion properties with the materials used as a result of heat treatment, a comparison was made between zinc-coated and the as-built Ti-6Al-4V samples. This showed that a bond was created after hot isostatic pressing and that the push-out force could be increased by more than 4.5 times. Consequently, a proof of feasibility was demonstrated, and a high potential for applications in medical technology was shown.

On the effect of the processing parameters in microstructure and thermomechanical properties of LPBF NiTi shape memory alloys

Recent studies have shown that variations in the parameters of the laser powder bed fusion (LPBF) process significantly impact the microstructure and thermomechanical properties of NiTi shape memory alloys (SMAs). Understanding how parameter selection influences the final NiTi SMA properties enables the strategic design of additively manufactured (AM) components with tailored mechanical and transformation behavior, suitable for specific applications in a plethora of scientific fields. However, the connection between processing and thermomechanical properties of NiTi SMAs is still not completely understood. This study investigates the effects of AM parameters laser power (72–185 W), scanning speed (668-1739 mm/s), and hatch spacing (28–85 μm) on a near equiatomic NiTi powder. Low porosity levels are found in the samples additively manufactured (AM) with the different LPBF parameter combinations. The findings also reveal that transformation temperatures and nickel evaporation trends correlate directly with volumetric energy density (VED). Additionally, the amount of Ti2Ni precipitates increases with higher VED. Thermal cycles under constant stress, training, and two-way shape memory effect tests have been performed; the results demonstrate a strain recovery ratio of 2–3.5% for most of the samples. The results arising from this study pave the way for the engineering of customized materials with tailored properties from the same alloy metal powder.

Diverse soliton wave profile analysis in ion-acoustic wave through an improved analytical approach

In engineering and applied sciences, several physical phenomena can be more precisely characterized by employing nonlinear fractional partial differential equations. The primary goal of this research is to examine the traveling wave solution in closed form for the nonlinear acoustic wave propagation model known as the time fractional simplified modified Camassa–Holm equation, which is used to explain the unidirectional propagation of shallow-water waves with non-hydrostatic pressure and explains the dispersion properties of numerous phenomena like fluid flow, control theory, liquid drop patterning in plasma, acoustics, fusion, and fission processes, etc. The utmost potential approach, namely the new auxiliary equation technique, is applied for analyzing the time nonlinear fractional simplified modified Camassa-Holm equation in the logic of the newest established truncated M-fractional derivative. The fractional partial differential equations have been transformed to the ordinary differential equation using the complex wave transformation in the sense of truncated M-fractional derivative. A variety of soliton solutions, including anti-kink, single soliton, anti-bell, bell, kink, multiple soliton, double soliton, singular-kink, compacton shape, periodic shape, and so many, are displayed in the diagram of 3D and contour plots by taking into account a number of various parameters. It is essential to point out that all derived outcomes are directly compared to the original solutions to certify their exactness. Results show that the used scheme is capable, simple, and straightforward and can be useful to a variety of complex phenomena. The acquired results are unique for the model equation and could be applied to the analysis of several nonlinear study fields.

STK40 inhibits trophoblast fusion by mediating COP1 ubiquitination to degrade P57Kip2

BackgroundThe syncytiotrophoblast (SCT) layer in the placenta serves as a crucial physical barrier separating maternal-fetal circulation, facilitating essential signal and substance exchange between the mother and fetus. Any abnormalities in its formation or function can result in various maternal syndromes, such as preeclampsia. The transition of proliferative villous cytotrophoblasts (VCT) from the mitotic cell cycle to the G0 phase is a prerequisite for VCT differentiation and their fusion into SCT. The imprinting gene P57Kip2, specifically expressed in intermediate VCT capable of fusion, plays a pivotal role in driving this key event. Moreover, aberrant expression of P57Kip2 has been linked to pathological placental conditions and adverse fetal outcomes.MethodsValidation of STK40 interaction with P57Kip2 using rigid molecular simulation docking and co-immunoprecipitation. STK40 expression was modulated by lentivirus in BeWo cells, and the effect of STK40 on trophoblast fusion was assessed by real-time quantitative PCR, western blot, immunofluorescence, and cell viability and proliferation assays. Co-immunoprecipitation, transcriptome sequencing, and western blot were used to determine the potential mechanisms by which STK40 regulates P57Kip2.ResultsIn this study, STK40 has been identified as a novel interacting protein with P57Kip2, and its expression is down-regulated during the fusion process of trophoblast cells. Overexpressing STK40 inhibited cell fusion in BeWo cells while stimulating mitotic cell cycle activity. Further experiments indicated that this effect is attributed to its specific binding to the CDK-binding and the Cyclin-binding domains of P57Kip2, mediating the E3 ubiquitin ligase COP1-mediated ubiquitination and degradation of P57Kip2. Moreover, abnormally high expression of STK40 might significantly contribute to the occurrence of preeclampsia.ConclusionsThis study offers new insights into the role of STK40 in regulating the protein-level homeostasis of P57Kip2 during placental development.

High accuracy patient-specific 3D coronary reconstruction from angiography and intravascular optical coherence tomography.

The integration of digital subtraction angiography (DSA) with intravascular optical coherence tomography (IVOCT) offers a comprehensive 3D arterial model, which is invaluable for the analysis of vascular anatomy and biomechanics. However, the process of image fusion is often hindered by the challenge of accurately orienting IVOCT images. This paper introduces a novel, to our knowledge, dual-path 3D reconstruction method that leverages the guidewire and the vessel's centerline to establish cross sectional direction vectors within the IVOCT images and spatial direction vectors along the guidewire's trajectory. This approach minimizes the accumulation of reconstruction errors by ensuring the precise orientation of each vascular cross section. The efficacy of the proposed method is validated through vascular phantom experiments and the reconstruction of patient-specific 3D coronary models.