Fine-grained Regions Research Articles

Effects of the microstructure and texture characteristics on mechanical properties of the Al–Ni–Cu–Fe alloy manufactured by laser powder bed fusion

In this study, the Al–Ni–Cu–Fe alloy was fabricated using laser powder bed fusion (LPBF), with controlled Fe content, to investigate its metallurgical effects. Furthermore, the microstructural differences between the coarse-grained (CG), fine-grained (FG) regions, and the melt pool boundary were compared. The results showed that the FG region exhibited grain-boundary and precipitation strengthening effects. The grain orientation in the FG region was randomly distributed, leading to the randomly oriented columnar grains with a small ratio of low-angle misorientations in the CG region. This prevented the CG region from developing a temperature gradient texture and provided a solid foundation for the high strength. Both high (Al–4Ni–2Cu–1.4Fe) and low (Al–4Ni–2Cu–0.7Fe) Fe-addition alloys exhibited strengths of over 600 MPa. The FG region of the 1.4Fe contained more strengthening phases, contributing to its higher strength. However, the presence of more incoherent interfaces between Al9FeNi and the α-Al lattice resulted in reduced ductility. On the other hand, the 0.7Fe alloy exhibited lower brittleness and improved ductility. Overall, the LPBF Al–Ni–Cu–Fe alloy shows promising potential for aerospace applications, and a comprehensive understanding of the strengthening mechanisms and microstructure can expand its application scope.

Effect of process modes on microstructure and mechanical properties of CMT wire arc additive manufactured WE43 magnesium alloy

The traditional WE43 magnesium alloy (WE43-Mg) manufacturing process faces challenges in producing large and complex structures. The cold metal transfer wire arc additive manufacturing (CMT-WAAM) offers a promising solution due to its flexibility, high deposition efficiency and low heat put. However, energy transfer and mass transfer are highly coupled in the CMT additive manufacturing process. Under different working modes, the local thermal processes are quite different for the same transition metals, which can produce different microstructures and mechanical properties. Therefore, it is necessary to study the effect of working modes on microstructure and mechanical properties. This study successfully deposited single-pass multi-layer WE43-Mg components using four CMT processes: CMT, CMT-Pulse, CMT-Advance, and CMT-Pulse + Advance. The microstructure and mechanical properties of these deposited samples were compared. Results revealed equiaxed grains with uniform sizes in the top and middle regions, with fine-grain regions between layers in the four CMT modes. Compare the microstructure characterization results, the higher the line energy, the narrower the width of the remelted fine grain zone. Four CMT modes deposited components exhibited superior mechanical properties compared to as-cast WE43-Mg. The CMT pulse mode shows the best results due to its low porosity. The average yield strength is 149.0 MPa, tensile strength is 222.9 MPa, and elongation is 6.4 %.

Effect of harmonic structure on the wear behavior of high entropy Cantor alloy

This study discusses the wear behavior of high entropy Cantor alloy when its microstructure is modified to a harmonic structure. Mechanical milling of the initial powder, followed by spark plasma sintering, is performed to obtain the harmonic structure. The developed harmonic structure shows a continuous fine-grained shell region with an average grain size of 2.8 ± 1.2 μm, covering ∼11% of the total surface area. The discreet core regions consist of larger grains with an average grain size of 22 ± 12 μm. Using the ball on disc method, the dry sliding wear of this material is performed with SiC ball as the counter body at 10 N, 15 N, and 20 N loads, and compared with the uniform grain-sized Cantor alloy, as-received 304 L stainless steel and maraging steel. Scanning electron micrographs of the wear tracks confirm the occurrence of adhesive, abrasive, and oxidative wear. Both the Cantor alloys show better wear resistance than 304 L stainless steel and maraging steel at 10 N and 15 N loads. However, the harmonic structured Cantor alloy shows the minimum wear resistance at 20 N load. The cross-sectional study reveals that the preferential wear of the grains in the core regions, followed by the chipping off the shell region, is responsible for the deterioration of the wear resistance of this material at 20 N load.

Transformer-based descriptors with fine-grained region supervisions for visual place recognition

Visual place recognition is a fundamental component in autonomous systems and robotics, which is easily limited in the real world with different viewpoints and changes in appearance. Existing approaches to tackle this problem mainly rely on dominant CNN-based architectures, which are difficult to model global correlation. Most recently, there has emerged little work that focuses on the effectiveness of the Transformer in modeling long-range dependencies, but this strategy ignores local interactions thus fails to localize the really important regions. To address the above issue, this paper proposes an effective Transformer-based architecture that takes full advantages of the strengths of Transformer related to global context modeling and local specific region capturing. We first design a dual-level Transformer descriptor encoder to successively perform self-attention within local windows and global extent of the CNN feature map to obtain multi-scale spatial context, which combines local interaction and global information. Specifically, multi-layer classification tokens from the Transformer encoder are integrated to form the global image representation. Moreover, a Transformer-guided geometric verification module is introduced to leverage the strengths of the hierarchical Transformer’s inherent self-attention mechanism for fusing multi-level attention, which is employed to filter the output token to obtain key patches and associated attention weights for achieving spatial matching. Finally, we propose a descriptor refinement strategy that employs fine-grained region-level supervisions to further enhance the capability of the network to learn local discriminative features, which effectively alleviates the confusion caused from weak image-level labels. Extensive experiments on benchmark datasets show that our approach outperforms state-of-the-art methods with promising performance.

Heterostructure microstructure and laves phase evolution mechanisms during inter-layer hammering hybrid directed energy deposition (DED) process

Directed energy deposition (DED) is suitable for fabrication of large Inconel 718 components, however, large columnar dendrites and several laves phase impair the mechanical properties. In this work, the formation mechanism of heterostructure microstructure with coarse grain (CG) and fine grain (FG) alternating distribution was explored, and the evolution process of Laves phase during inter-layer hammering hybrid directed energy deposition (HDED) was revealed. The results show that the heterostructure microstructure composed of CG region and FG region with a ratio of 1:1 was obtained due to the work hardening and recrystallization mechanisms, and the average grain size of CG region and FG region are 68.9 μm and 12.0 μm, respectively. The Laves phase was first fractured into small pieces by hammering and then resolved into the matrix during the subsequent heat input process, which promotes the precipitation of γ″ phase from the matrix. The strength and plasticity of the specimens fabricated by HDED are synchronously improved. The dislocation strengthening and solid solution strengthening are the mainly contributions to the strength improvement, and the grain refinement and heterostructure microstructure increased the plasticity of the hybrid manufactured specimens.

Transition of low and high-angle grain boundaries during strain rate-induced dislocation storage and annihilation

This work explores the characteristics of dislocation storage and annihilation behavior in heterogeneous metal welded joints under different strain rates. It forms the micro-strain gradient alternating between the strain and strain-free zones due to the annihilation of dislocations and transition of substructure in welded joints. This gradient structure keeps the strain values at a lower level by limiting the slip of geometrically necessary dislocations (GNDs) in the fine-grained region, while most of the plastic strain is accommodated in the coarse-grained region, thus promoting the storage of GNDs and low-angle grain boundaries (LAGBs). The strain rate enhances the degree of transition among GNDs, LAGBs, and high-angle grain boundaries (HAGBs) by promoting the transition from LAGBs to HAGBs in the fine-grained region, which accelerates the annihilation of GNDs. More importantly, the formation of micro-strain gradient improves the strength and strain hardening ability of welded joints. This work will provide a better understanding of the substructure transition behaviors of heterogeneous metals under different strain rates.

Hybrid DAER Based Cross-Modal Retrieval Exploiting Deep Representation Learning.

Information retrieval across multiple modes has attracted much attention from academics and practitioners. One key challenge of cross-modal retrieval is to eliminate the heterogeneous gap between different patterns. Most of the existing methods tend to jointly construct a common subspace. However, very little attention has been given to the study of the importance of different fine-grained regions of various modalities. This lack of consideration significantly influences the utilization of the extracted information of multiple modalities. Therefore, this study proposes a novel text-image cross-modal retrieval approach that constructs a dual attention network and an enhanced relation network (DAER). More specifically, the dual attention network tends to precisely extract fine-grained weight information from text and images, while the enhanced relation network is used to expand the differences between different categories of data in order to improve the computational accuracy of similarity. The comprehensive experimental results on three widely-used major datasets (i.e., Wikipedia, Pascal Sentence, and XMediaNet) show that our proposed approach is effective and superior to existing cross-modal retrieval methods.

Trim Regions for Online Computation of From-Region Potentially Visible Sets

Visibility computation is a key element in computer graphics applications. More specifically, a from-region potentially visible set (PVS) is an established tool in rendering acceleration, but its high computational cost means a from-region PVS is almost always precomputed. Precomputation restricts the use of PVS to static scenes and leads to high storage cost, in particular, if we need fine-grained regions. For dynamic applications, such as streaming content over a variable-bandwidth network, online PVS computation with configurable region size is required. We address this need with trim regions, a new method for generating from-region PVS for arbitrary scenes in real time. Trim regions perform controlled erosion of object silhouettes in image space, implicitly applying the shrinking theorem known from previous work. Our algorithm is the first that applies automatic shrinking to unconstrained 3D scenes, including non-manifold meshes, and does so in real time using an efficient GPU execution model. We demonstrate that our algorithm generates a tight PVS for complex scenes and outperforms previous online methods for from-viewpoint and from-region PVS. It runs at 60 Hz for realistic game scenes consisting of millions of triangles and computes PVS with a tightness matching or surpassing existing approaches.

Semantic 3D-Aware Portrait Synthesis and Manipulation Based on Compositional Neural Radiance Field

Recently 3D-aware GAN methods with neural radiance field have developed rapidly. However, current methods model the whole image as an overall neural radiance field, which limits the partial semantic editability of synthetic results. Since NeRF renders an image pixel by pixel, it is possible to split NeRF in the spatial dimension. We propose a Compositional Neural Radiance Field (CNeRF) for semantic 3D-aware portrait synthesis and manipulation. CNeRF divides the image by semantic regions and learns an independent neural radiance field for each region, and finally fuses them and renders the complete image. Thus we can manipulate the synthesized semantic regions independently, while fixing the other parts unchanged. Furthermore, CNeRF is also designed to decouple shape and texture within each semantic region. Compared to state-of-the-art 3D-aware GAN methods, our approach enables fine-grained semantic region manipulation, while maintaining high-quality 3D-consistent synthesis. The ablation studies show the effectiveness of the structure and loss function used by our method. In addition real image inversion and cartoon portrait 3D editing experiments demonstrate the application potential of our method.

MNER-QG: An End-to-End MRC Framework for Multimodal Named Entity Recognition with Query Grounding

Multimodal named entity recognition (MNER) is a critical step in information extraction, which aims to detect entity spans and classify them to corresponding entity types given a sentence-image pair. Existing methods either (1) obtain named entities with coarse-grained visual clues from attention mechanisms, or (2) first detect fine-grained visual regions with toolkits and then recognize named entities. However, they suffer from improper alignment between entity types and visual regions or error propagation in the two-stage manner, which finally imports irrelevant visual information into texts. In this paper, we propose a novel end-to-end framework named MNER-QG that can simultaneously perform MRC-based multimodal named entity recognition and query grounding. Specifically, with the assistance of queries, MNER-QG can provide prior knowledge of entity types and visual regions, and further enhance representations of both text and image. To conduct the query grounding task, we provide manual annotations and weak supervisions that are obtained via training a highly flexible visual grounding model with transfer learning. We conduct extensive experiments on two public MNER datasets, Twitter2015 and Twitter2017. Experimental results show that MNER-QG outperforms the current state-of-the-art models on the MNER task, and also improves the query grounding performance.

Ductility enhancement mechanism of AZ31 magnesium alloy with through-thickness symmetrical gradient structure prepared by hard plate rolling

The optimal configuration of strength and ductility was the first choice in Mg-alloys plate forming. A rolling method with adding the hard plate and unique component structure design was proposed to achieve a symmetrical gradient structure from two upmost surfaces to the center of the AZ31 Mg-alloys plate during a single rolling pass. The microstructure evolution and mechanical properties of symmetrical gradient structure plates were studied. The results indicate that Mg-alloy plates' strength and tensile ductility reached 267 MPa and 26.1%, respectively. In the fine-grain region, the proportion of high-angle grain boundary was 56.4%, and the recrystallization structure was 57.3%. In the coarse-grain region, high-grain boundaries and recrystallization decreased to 42.9% and 42.1%, respectively. Both prismatic slip and pyramidal slip in the CG region were easier to initiate, which leads the interaction of multidirectional twins. The geometrically necessary dislocations mainly accumulate at the boundary of the different region. The fracture morphology showed a gradient distribution of dimples. The crack was deflected in the process of extension, which also leads high ductility of Mg-alloy. The design strategy provides a new idea for producing the high-performance plate with through-thickness symmetrical gradient structure.

Improvement on high-temperature tensile strength and ductility of selective electron beam melting TiAl alloys via small-strain forging

In the present work, a Ti–48Al–2Cr–2Nb alloy prepared by selective electron beam melting (SEBM) and post-treated by forging at a small strain was investigated. The results show that the microstructure of the as-built TiAl alloys exhibited an alternating layer of coarse single γ grains and fine γ+α2 grains configuration along the building direction. After forging at a small strain, the fraction of the coarsely grained region decreases, and substantial fine sub-grains form in the fine-grained region. Additionally, fractions of the α2 phase and α2/γ lamellar colonies increase. These factors lead to an increase in the tensile strength of alloys. Meanwhile, the low-angle grain boundaries (LAGBs) in fine sub-grains and the substantial mobile dislocations in coarse γ grains are favorable for improving the ductility of alloys. The formation of deformation twins in the γ grains facilitates the simultaneous improvement of strength and ductility. In addition, the anisotropy of tensile properties is reduced after small-strain forging, which can be attributed to the reduction in fraction of the coarse γ grains, and the increase in the fractions of the α2 phase and α2/γ lamellar structure. Therefore, small-strain forging was verified as an effective post-treatment method for the improvement of tensile strength and ductility of SEBM prepared TiAl alloys at high temperatures.

Fatigue crack propagation behavior of the grain size transition zone in a dual microstructure turbine disc

Constant load amplitude andΔK fatigue crack propagation (FCP) tests have been carried out to investigateFCP behavior of grain size transition zone in a dual microstructure turbine disc. The results show grain size exerts more significant influence in the time-dependent FCP regime, but the effect of grain size is relatively limited in the cycle-dependent FCP regime.Larger local plastic deformation zone is found in fine-grained region,which is believed to be the reason that causes more significant grain boundary oxidation along with contribution from more grain boundaries acting as short-circuit diffusion paths of oxide-forming elements, resulting in accelerated FCP.

Influence of heat treatment on corrosion behavior of Al–Mn–Mg–Sc–Zr alloy produced by laser powder bed fusion

Effect of heat treatments on the microstructure and corrosion behavior of Al–Mn–Mg–Sc–Zr alloy fabricated by laser powder bed fusion (LPBF) were systematically investigated. The results demonstrate that the 300 °C/5 h heat-treatment doesn't alter the typical bimodal grain distribution of LPBF-fabricated alloy. However, the grains at molten pool boundaries experience a significant growth after a 500 °C/5 h heat treatment, narrowing the gap of grain size between fine-grain (FG) region and coarse-grain (CG) region. It is also found that the heat treatments have an impact on Al3(Sc, Zr) and Al6(Mn, Fe) precipitates. Detailedly, the Al3(Sc, Zr) precipitates undergo a slight growth in size and obvious increase in quantity after heat treatment whilst the Al6(Mn, Fe) particles go through a rapid increase both in amount and size, especially for the alloy after being subject to a higher temperature heat treatment. As consequence, the heat-treated LPBF aluminum alloys exhibit worse corrosion resistance compared with their original state. The Al3(Sc, Zr) precipitates acting as micro-cathodes at molten pool boundaries accelerate the preferential corrosion of fine grain regions of 300 °C/5 h heat-treated alloy (HT-300). In contrast, the 500 °C/5 h heat-treated alloy (HT-500) tends to promote a more uniform corrosion due to the dissolution of the homogeneously distributed Al6(Mn, Fe) anodes on the alloy surface.

The influence of rotation angle between layers in laser-based powder bed fusion on the hydrogen embrittlement of Ni

This work investigated the relation between hydrogen embrittlement and the scanning rotation angle between adjacent layers in laser-based powder bed fusion (L-PBF) fabricated Ni. The microstructure analysis indicated that all samples failed with an intergranular mode, and all intergranular facets were propagated along the fine-grain region. However, the rotation angle during manufacturing changed the grain shape and size distribution in Ni, which in turn modified the pathway for hydrogen-induced cracking. The sensitivity of LPBFed Ni to hydrogen embrittlement is influenced by the scanning strategy, and the samples with a rotation angle of 0° present the highest resistance to hydrogen embrittlement.

Effects of TiB2 additions on microstructure and mechnical properties of Al–Mg–Sc alloy fabricated by selective laser melting

In this paper, the effect of TB2 additions on a noval Al–Mg–Sc alloy was studied, and the microstructure and mechanical properties of SLM-fabricated TiB2/Al–Mg–Sc alloys were investigated. The results showed that molten pool width increased and molten pool depth slightly decreased with TiB2 increase, due to the laser absorptivity of the TiB2/Al–Mg–Sc alloys higher than that of Al–Mg–Sc alloy under the same process parameters. The microstructure of SLM-fabricated TiB2Al–Mg–Sc alloys were composed of fine-grained, coarse-grained and columnar-grained regions, and the fine-grained region increased with the increase of TiB2 content. The recrystallization regions in SLM-fabricated TiB2/Al–Mg–Sc alloy decreased with the increase of TiB2 content, and TiB2 additions used as heterogeneous nucleation to refine grains, which can pin grain boundaries and prevent recrystallization during SLM process. TiB2/Al–Mg–Sc alloy with 1% TiB2 additions showed a relatively higher comprehensive mechanical properties, and the tensile strength is 483 MPa, the elongation is 15.8%. Tensile strength of 1%TiB2/Al–Mg–Sc alloy was increased by 37 MPa and the elongation is also increased by 2.1% compared with 0%TiB2/Al–Mg–Sc alloy, and 2%TiB2/Al–Mg–Sc alloy shown a relatively lower comprehensive mechanical properties due to its lower density and TB2 agglomerated.

Effect of casting methods on magnetic properties of Sm(CoFeCuZr)z magnet

The effect of casting method on the magnetic properties of Sm(Co0.63Fe0.28Cu0.07Zr0.02)7.6 magnet has been investigated. The results show that the plate-mold ingot (PM) and strip-casting flake (SC) have the same phase composition. Compared with PM, the SC has a smaller grain size and larger fine-grain region due to its larger degree of undercooling. The magnetic properties of the PM magnet are Br = 11.63 kG, Hcj = 25.65 kOe, (BH)max = 30.97 MGOe, while the magnetic properties of SC magnet are Br = 11.45 kG, Hcj = 24.00 kOe, (BH)max = 30.03 MGOe. The reason for the low remanence of the SC magnet is revealed by the XRD and EBSD results. It shows that the PM magnet has a better easy-axis orientation than the SC magnet, due to the existence of fine grains in SC that are unfavorable for the alignment under a magnetic field.

Saturation evaluation for fine-grained sediments

Accurate quantification of the gas hydrate content in the deep sea is useful for assessing the resource potential and understanding the role of gas hydrates in the global carbon cycle. Resistivity logging data combined with Archie's equation are often used to calculate gas hydrate saturation, but the reliability is dependent on the rationality of the empirical parameter cementation factor and saturation index. At present, an increasing number of fine-grained hydrate-rich sediment regions have been discovered worldwide through drilling efforts, and the reservoir types and hydrate distribution are diverse, which differs greatly from that of coarse-grained reservoirs of hydrate-bearing sediment. This results in vertical variations in m and n through stratigraphy. At present, the saturation evaluation effect of these reservoirs cannot be improved. In this work, a theory for the determination of the cementation factor and saturation index was first proposed to obtain reliable and variable values of the empirical parameters. Then, a hydrate saturation evaluation technique with variables m and n was formed based on the well logging data. This technique was used to evaluate complex fine-grained hydrate-bearing reservoirs in several regions worldwide. It was found that the highest n could be 16, and the log calculation results were more consistent with the core hydrate saturation. Additionally, the cause of the excessively high n values was explained from physical principles, and the result was verified with actually well log data. In future evaluations of the amount of hydrate resources in fine-grained sediment reservoirs worldwide, new saturation estimation methods should be taken into account to advance hydrate research.

Scene Classification of Remote Sensing Images Guided by Fine-Grained Salient Region

Scene Classification of Remote Sensing Images Guided by Fine-Grained Salient Region

Fine-Grained Features for Image Captioning

Image captioning involves two different major modalities (image and sentence) that convert a given image into a language that adheres to visual semantics. Almost all methods first extract image features to reduce the difficulty of visual semantic embedding and then use the caption model to generate fluent sentences. The Convolutional Neural Network (CNN) is often used to extract image features in image captioning, and the use of object detection networks to extract region features has achieved great success. However, the region features retrieved by this method are object-level and do not pay attention to fine-grained details because of the detection model’s limitation. We offer an approach to address this issue that more properly generates captions by fusing fine-grained features and region features. First, we extract fine-grained features using a panoramic segmentation algorithm. Second, we suggest two fusion methods and contrast their fusion outcomes. An X-linear Attention Network (X-LAN) serves as the foundation for both fusion methods. According to experimental findings on the COCO dataset, the two-branch fusion approach is superior. It is important to note that on the COCO Karpathy test split, CIDEr is increased up to 134.3% in comparison to the baseline, highlighting the potency and viability of our method.