Random Texture Research Articles

Precipitate characteristics and their effects on the mechanical properties of as-extruded Mg-Gd-Li-Y-Zn alloy

In this work, a high-performance Mg-8.4Gd-4.4Li-3.5Y-1.4Zn (wt%) alloy was successfully prepared by low-temperature hot extrusion. The studied alloy has a TYS of 295 ± 1 MPa and an EL of 2.5 %±0.2 % at room temperature, 159 ± 8 MPa and 15.9 %±1.4 % at 150 °C, and 143 ± 4 MPa and 19.8 %±1.8 % at 200 °C. The high performance at temperatures up to 200 °C is attributed to the dispersion strengthening of three Mg3RE phase variants, the solid solution strengthening of alloying elements and the bimodal structure consisting of fine DRXed grains with random texture and coarse un-DRXed grains with basal texture. A novel island shaped β1R phase (FCC, a = 0.78 nm) with a size of 30 nm–100 nm is observed in the studied alloy. The β1R phase precipitates on the {11¯00}α prismatic planes. The strain-induced, dislocation-assisted dynamic precipitation during low-temperature hot extrusion is responsible for the formation of the β1R phase. The growth of the β1R phase is owing to the aid of the formation and transformation of zig-zag structures. The basal slip of <a> dislocations is the dominate deformation mechanism of the studied alloy in the early stage of tensile deformation at room temperature, while non-basal slip of <a> and <c+a> dislocations at 200 °C. Due to the strong interaction between β1R precipitates and dislocations, the densely distributed β1R precipitates significantly improve the mechanical properties via the Orowan strengthening both at room temperature and elevated temperatures.

Comparative observer effects in 2D and 3D localization tasks.

.Purpose: Three-dimensional “volumetric” imaging methods are now a common component of medical imaging across many imaging modalities. Relatively little is known about how human observers localize targets masked by noise and clutter as they scroll through a 3D image and how it compares to a similar task confined to a single 2D slice.Approach: Gaussian random textures were used to represent noisy volumetric medical images. Subjects were able to freely inspect the images, including scrolling through 3D images as part of their search process. A total of eight experimental conditions were evaluated (2D versus 3D images, large versus small targets, power-law versus white noise). We analyze performance in these experiments using task efficiency and the classification image technique.Results: In 3D tasks, median response times were roughly nine times longer than 2D, with larger relative differences for incorrect trials. The efficiency data show a dissociation in which subjects perform with higher statistical efficiency in 2D tasks for large targets and higher efficiency in 3D tasks with small targets. The classification images suggest that a critical mechanism behind this dissociation is an inability to integrate across multiple slices to form a 3D localization response. The central slices of 3D classification images are remarkably similar to the corresponding 2D classification images.Conclusions: 2D and 3D tasks show similar weighting patterns between 2D images and the central slice of 3D images. There is relatively little weighting across slices in the 3D tasks, leading to lower task efficiency with respect to the ideal observer.

Crystallographic texture influences on the thermal stability of nanocrystalline materials

The influence of crystallographic texture on the total amount of solute segregated at the grain boundaries (Xgb,tot) and consequently the weighted grain boundary energy (γw) of a nanocrystalline material is investigated. Toward this end, two different 3D nanostructures, one with random crystallographic texture and the other with {111} texture, were generated. The grain boundary misorientation distribution was obtained from both the 3D nanostructures and converted into an equivalent grain boundary energy distribution using the data from Olmstead et al. It was found that both Xgb,tot and γw are higher for the nanostructure bearing random texture vis-a-vis the {111} texture. This has implications in the development of thermally stable nanocrystalline materials. The effect of texture is also discussed through a case study on the Ni–W system by invoking the nanocrystalline stability criterion proposed by Kalidindi and Schuh.

3D simulation of texture evolution induced grain coarsening in FCC polycrystals during severe plastic deformation

In the present work, results obtained in 3D polycrystal simulations are reported on the coalescence effect of neighbouring grains due to texture evolution. A 3D cellular automaton model was developed for this purpose, which permits to take into account the effect of topology on coalescence. The grains constituting the polycrystal were divided into voxels to have realistic representations of grain shapes. The Taylor polycrystal plasticity approach was applied to calculate the orientation change for each voxel. When the disorientation angle between neighbour voxels belonging to different grains was less than 5°, the voxel volume was reallocated to the neighbouring grain. For a random initial texture, after a shear strain of 6, the relative volume that was re-assigned between neighbours was 29.7%, which is not negligible. The effect of initial texture and topology was also investigated. The 3D morphologies of some typical coarsening grains were monitored to illustrate the simulation results.

Interface development and microstructure evolution during double-sided friction stir spot welding of magnesium alloy by adjustable probes and their effects on mechanical properties of the joint

The flat friction stir spot welding using double side adjustable tools (Flat DSAT FSSW) was successfully applied to the joining of magnesium alloys in our previous research. In this study, the in-situ X-ray radiography observations using a high-intensity X-ray transmission device were carried out to investigate the interface development. In addition, the microstructure evolution at different welding stages was also studied. The mechanical properties of the welded joints were significantly affected by the minimum plate thickness of the joint, which was the distance from the tip of the unwelded interface to the bottom of the lower plate. The welding interface was well welded during the stage of the holding of probes, and the minimum plate thickness was eventually determined by the stage of raising the lower probe, which is the key stage affecting the joint properties. The in-situ X-ray radiography technique shows a significant advantage to reveal the welding process. In the tip area of the unwelded interface at low rotation speed welding condition, the grain growth was suppressed due to the limited heat generation, giving rise to refined microstructure. Moreover, a randomized texture was obtained owing to the weak material flow during the welding process and the introduced mechanical twins during the stage of raising the lower probe. The refined microstructure resulting from limited heat generation and randomized texture resulting from weak material flow contributed to the high strength welded joint.

Plausibility and redundancy analysis to select FDG-PET textural features in non-small cell lung cancer.

BackgroundRadiomics refers to the extraction of a large number of image biomarker describing the tumor phenotype displayed in a medical image. Extracted from positron emission tomography (PET) images, radiomics showed diagnostic and prognostic value for several cancer types. However, a large number of radiomic features are nonreproducible or highly correlated with conventional PET metrics. Moreover, radiomic features used in the clinic should yield relevant information about tumor texture. In this study, we propose a framework to identify technical and clinical meaningful features and exemplify our results using a PET non‐small cell lung cancer (NSCLC) dataset.Materials and methodsThe proposed selection procedure consists of several steps. A priori, we only include features that were found to be reproducible in a multicenter setting. Next, we apply a voxel randomization step to identify features that reflect actual textural information, that is, that yield in 90% of the patient scans a value significantly different from random texture. Finally, the remaining features were correlated with standard PET metrics to further remove redundancy with common PET metrics. The selection procedure was performed for different volume ranges, that is, excluding lesions with smaller volumes in order to assess the effect of tumor size on the results. To exemplify our procedure, the selected features were used to predict 1‐yr survival in a dataset of 150 NSCLC patients. A predictive model was built using volume as predictive factor for smaller, and one of the selected features as predictive factor for bigger lesions. The prediction accuracy of the both models were compared with the prediction accuracy of volume.ResultsThe number of selected features depended on the lesion size included in the analysis. When including the whole dataset, from 19 features reflecting actual texture only two were found to be not strongly correlated with conventional PET metrics. When excluding lesions smaller than 11.49 and 33.10 mL (25 and 50 percentile of the dataset), four out of 27 features and 13 out of 29 features remained after eliminating features highly correlated with standard PET metrics. When excluding lesions smaller than 103.9 mL (75 percentile), 33 out of 53 features remained. For larger lesions, some of these features outperformed volume in terms of classification accuracy (increase of 4–10%). The combination of using volume as predictor for smaller and one of the selected features for larger lesions also improved the accuracy when compared with volume only (increase from 72% to 76%).ConclusionWhen performing radiomic analysis for smaller lesions, it should be first carefully investigated if a textural feature reflects actual heterogeneity information. Next, verification of the absence of correlation with all conventional PET metrics is essential in order to assess the additional value of radiomic features. Radiomic analysis with lesions larger than 11.4 mL might give additional information to conventional metrics while at the same time reflecting actual tumor texture. Using a combination of volume and one of the selected features for prediction yields promise to increase accuracy and reliability of a radiomic model.

Activation of &lt;c+a&gt; slip and enhanced ductility in as-extruded Mg-Gd-Y-Nd alloys through Si addition

Low-cost Si was added to Mg-8Gd-4Y-1Nd alloys to improve their ductility. With the Si increased from 0 to 1.0 wt %, the elongation increased from 8.7% to 17.1% for as-extruded Mg-8Gd-4Y-1Nd alloys. Microstructures results indicated that the formation of GdSi and Y 5 Si 3 intermetallic phases increased significantly with the Si addition, which was shown to promote the random orientation of grain structures. As Si works as substitutional atoms in Mg alloys can decrease the first intrinsic stacking faults (I 1 SF) energy, the pyramidal <c+a> dislocation was activated during deformation, thus the {0001} Mg basal plane deviate from the extrusion direction and alter to random textures. Activating both the pyramidal <c+a> and basal <a> slip provided more independent slip systems during deformation and caused more stress accumulation, which exceeded the critical shear stress (CRSS) for tensile twinning. The simultaneous activation of the pyramidal <c+a> slip and tensile induced twinning improved the ductility of the Mg-8Gd-4Y-1Nd-1.0Si alloy.

Affective analysis of visual scenes using face pareidolia and scene-context

This study presents a new computer vision approach to perform affective analysis of a scene or object. The approach utilises a simulation of the phenomenon of face pareidolia that can be described as the perception of non-existent faces, for example, in random textures, clouds or rock formations. The emergence of face pareidolia in product designs and natural scenes can modulate affective perception of our everyday experiences without our conscious awareness. We propose a new deep learning method to simulate the face pareidolia ability of humans and predict associated emotional responses in two-dimensional valence and arousal space. Starting from a face detector that was trained on images of human faces, we propose a novel cross-domain weakly supervised three-step progressive domain adaptation approach to simulate face pareidolia by fine-tuning the human face detector on three types of synthetically generated sample images. Our approach fuses two deep network models, one model for predicting valence and arousal from abstract and minimal face-like patterns producing face pareidolia, and a second for recognising overall moods and context associated with the scene. To evaluate our approach, we constructed a new dataset containing instance-level annotations of face pareidolia occurrences as well as valence and arousal emotional values associated with the overall scene. The quantitative and qualitative experimental results of the present study demonstrate that our approach can outperform other state-of-the-art methods in face pareidolia detection as well as in predicting associated emotions.

Analysis of the Strain Distribution and Texture Measurements in Asymmetric Rolling (AR) and Asymmetric Accumulative Roll Bonding (AARB)

Severe plastic deformation (SPD) with strong shear component is required to promote both grain refinement and texture randomization. When Asymmetric rolling (AR) is applied as asymmetric accumulative roll bonding (AARB), it enables the production of architectured microstructures and metallic composites. Finite element (FE) simulations of AR and AARB were employed to understand the influence of pass thickness reduction (PTR) on the through thickness variation of the velocity gradient. The influence of the PTR up to a total thickness reduction of 50% and the effect of a single 50% reduction step in a bi-layer bonding condition was analyzed. The influence of these process parameters on the strain and rigid body rotation components was compared with the experimental data obtained on an AA1050 aluminum. A better shear to compression ratio across the sheet thickness is achieved by PTRs lower than 30%; at a PTR of 50% the texture is dominated by the frictional shear generated at the roll-sheet interface and the process has a stronger compressive character. This indicates that simple ARB followed by AR with smaller PTRs should generate a better shear distribution than AARB alone.

Global and Local Texture Randomization for Synthetic-to-Real Semantic Segmentation.

Semantic segmentation is a crucial image understanding task, where each pixel of image is categorized into a corresponding label. Since the pixel-wise labeling for ground-truth is tedious and labor intensive, in practical applications, many works exploit the synthetic images to train the model for real-word image semantic segmentation, i.e., Synthetic-to-Real Semantic Segmentation (SRSS). However, Deep Convolutional Neural Networks (CNNs) trained on the source synthetic data may not generalize well to the target real-world data. To address this problem, there has been rapidly growing interest in Domain Adaption technique to mitigate the domain mismatch between the synthetic and real-world images. Besides, Domain Generalization technique is another solution to handle SRSS. In contrast to Domain Adaption, Domain Generalization seeks to address SRSS without accessing any data of the target domain during training. In this work, we propose two simple yet effective texture randomization mechanisms, Global Texture Randomization (GTR) and Local Texture Randomization (LTR), for Domain Generalization based SRSS. GTR is proposed to randomize the texture of source images into diverse unreal texture styles. It aims to alleviate the reliance of the network on texture while promoting the learning of the domain-invariant cues. In addition, we find the texture difference is not always occurred in entire image and may only appear in some local areas. Therefore, we further propose a LTR mechanism to generate diverse local regions for partially stylizing the source images. Finally, we implement a regularization of Consistency between GTR and LTR (CGL) aiming to harmonize the two proposed mechanisms during training. Extensive experiments on five publicly available datasets (i.e., GTA5, SYNTHIA, Cityscapes, BDDS and Mapillary) with various SRSS settings (i.e., GTA5/SYNTHIA to Cityscapes/BDDS/Mapillary) demonstrate that the proposed method is superior to the state-of-the-art methods for domain generalization based SRSS.

Development of thin-gauge low iron loss non-oriented silicon steel

Microstructure, texture, inclusions and precipitates in Fe-2.97wt%Si non-oriented silicon steel during manufacture were investigated using Scanning Electron Microscopy (SEM), Organic Solvent Electrolysis and Electron Backscattered Diffraction(EBSD)techniques. The P10/400, P15/50 and B50 of thin-gauge non-oriented silicon steel with 0.3 mm in thickness were 13.85 W/kg, 2.38 W/kg and 1.66 T, respectively. Due to annealing of hot rolled band, the size of precipitates increased. The precipitates are mostly located at the grain boundaries in the annealed sheet, the main and average size of the grain-boundary precipitates were in the range of 30 ∼ 500 nm and 63.2 nm, respectively. The pinning force caused by 100 ∼ 300 nm particles at the grain boundaries was the largest, 70 ∼ 100 nm was second. During annealing of hot rolled band, the α*-fiber texture significantly developed and γ-fiber dropped dramatically. The γ-fiber texture and α*-fiber texture composed the main textures of annealed sheet. The texture randomization would give rise to better magnetic properties compared to the γ-fiber.

Polycrystal Simulation of Texture-Induced Grain Coarsening during Severe Plastic Deformation.

During severe plastic deformation (SPD), there is usually extended grain fragmentation, associated with the formation of a crystallographic texture. The effect of texture evolution is, however, coarsening in grain size, as neighbor grains might coalesce into one grain by approaching the same ideal orientation. This work investigates the texture-induced grain coarsening effect in face-centered cubic polycrystals during simple shear, in 3D topology. The 3D polycrystal aggregate was constructed using a cellular automaton model with periodic boundary conditions. The grains constituting the polycrystal were assigned to orientations, which were updated using the Taylor polycrystal plasticity approach. At the end of plastic straining, a grain detection procedure (similar to the one in electron backscatter diffraction, but in 3D) was applied to detect if the orientation difference between neighboring grains decreased below a small critical value (5°). Three types of initial textures were considered in the simulations: shear texture, random texture, and cube-type texture. The most affected case was the further shearing of an initially already shear texture: nearly 40% of the initial volume was concerned by the coalescence effect at a shear strain of 4. The coarsening was less in the initial random texture (~30%) and the smallest in the cube-type texture (~20%). The number of neighboring grains coalescing into one grain went up to 12. It is concluded that the texture-induced coarsening effect in SPD processing cannot be ignored and should be taken into account in the grain fragmentation process.

Plastically-Induced Volume Deformation of Nanocrystalline α-Fe with a &lt;110&gt; Columnar Structure

Volume changes accompanying the plastic deformation at 300 K of nanocrystalline samples of α-Fe with a columnar grain structure possessing a ⟨11¯0⟩ random fiber texture has been obtained from molecular dynamics (MD) simulations. The samples were strained in tension along the common axial direction of the columnar grains. After removal of the elastic volume change, the evolution of plastic volume strain was obtained. Small but non-negligible volume dilations or contractions are observed depending on size (samples of very small grain size show volume contraction). The rate of volume change is high during the first 10% plastic deformation and continues at a low pace thereafter; the first 10% deformation represents a transient in the stress–strain behavior too. The complex behavior observed is reasonably explained by the superposition of contributions from different plastically-induced structural changes to the mass density change: Mainly from changes of grain size, grain boundary structure, dislocation density and density of point-defects. The results are of interest for the development of crystal plasticity theories not restricted by the volume conserving assumption.

Challenging Ultra Grain Refinement of Ferrite in Low-C Steel Only by Heat Treatment

It is well-known that grain refinement is one of the most effective ways to improve strength of metals without addition of alloying elements. In order to obtain bulky metals having ultrafine grained (UFG) microstructures with average grain sizes smaller than 1 μm, severe plastic deformation (SPD) processes have made a great success. However, there are still big barriers to realize UFG metallic materials, especially UFG steels, in large scale industries, since severe plastic deformation processes usually need special techniques and equipment, and large deformation forces are required for heavy plastic deformations. Cyclic heat treatments to repeat martensitic transformation and austenitization have been known as a simple way to fabricate fine-grained austenitic structures in steels. In the present study, we tried to make final ferrite microstructures ultrafine in a low-C steel by means of the cyclic heat treatment. Evolution of microstructures during the cyclic heat treatment was systematically investigated, putting stress on the change of grain sizes of austenite and ferrite. The austenite grain size decreased with increasing the number of heat treatment cycles, and the minimum average austenite grain size obtained was 11 μm. By having furnace-cooling from austenite states with various grain sizes, ferrite microstructures with different mean grain sizes were fabricated. We could successfully obtain a fine-grained ferrite structure with a mean grain size of 4.5 μm and nearly a random texture through the heat treatment without deformation. Microstructural features and mechanical properties of the obtained fine-grained ferritic structures were investigated by scanning electron microscope/electron back-scattering diffraction measurements and a tensile test at room temperature. The specimens with ferrite + pearlite microstructure with the smallest average ferrite grain size of 4.5 μm managed both high strength (yield strength of 375 MPa and tensile strength of 500 MPa) and large tensile ductility (uniform elongation of 20% and total elongation of 39%) in the simple 2Mn-0.1C steel.

Influence of topographical features on the surface appearance measurement of injection moulded components

Adding textures to surfaces is known to improve the external appearance of injection moulded components. However, when high surface quality is required, normally a paint coating is applied on top of the moulded textured surface. In this work, an alternative to painting for obtaining high quality surfaces is proposed, following an environmental-friendly process and having low production cost. Three different surface textures obtained by injection moulding have been characterized and compared with a painted one. Alternative topographical parameters such as the absolute functional height (AFH), the functional height distribution (FHD), texture slope (TS) or texture aperture angle (TAA) besides to the traditional roughness parameters such as the arithmetical mean height (Sa) and the root mean square height (Sq) have been utilized to characterize the random surface textures. The relationships between these parameters and the surface quality appearance represented by gloss and reflectivity contrast have been established using a new total appearance measurement (TAM) apparatus. It was found that by applying secondary operation on the textured mould cavity, such as adding micro roughness features or coatings, equal apparent quality to the ones obtained by painting can be reached.

Experimental and numerical analysis of cyclic deformation and fatigue behavior of a Mg-RE alloy

Strain-controlled fatigue of Mg–1Mn-0.5Nd (wt.%) alloy were studied by experiment and simulation. The microstructure was made up of a dispersion of strongly texture grains (13%) embedded in a matrix of grains with a random texture. The cyclic stress-strain curves showed limited tension-compression anisotropy because of the limited texture. Cyclic hardening under compression and cyclic softening under tension occurred due to the presence of twinning. Moreover, the twin volume fraction of the broken samples depended on whether the sample was broken in tension or compression, indicating that twining-detwinning occurs during the whole fatigue life. The mechanical response of the polycrystalline alloy was simulated by means of computational homogenization. The behavior of the Mg grains was modeled using a phenomenological crystal plasticity model that accounted for basal, prismatic and pyramidal slip (including isotropic and kinematic hardening) as well as twining and detwinning. The model parameters were calibrated from the cyclic stress-strain curves at different cyclic strain amplitudes. Numerical simulations were used to understand the dominant deformation mechanisms and to predict the fatigue life by means of a fatigue indicator parameter based on the accumulated plastic shear strain in each fatigue cycle.

The interplay between emitter conformality and field‐effect passivation in pyramid structured silicon solar devices

AbstractLight management in crystalline silicon solar cells has conventionally been achieved by random micropyramid texturing but other non‐conventional surface texturing methods, such as diffraction gratings, have also attracted attention with the objective of attaining near‐ideal light trapping. Unlike previous investigations on the subject in which the focus was predominantly to minimize optical losses, we report on surface passivation difference between the micron and nanoscale pyramid textures. From simulations, we find that the conformality of thermally diffused emitters is impacted by downsizing the pyramid texture to the light wavelength scale, which, in turn, affects the field‐effect passivation of the resulting homojunction. The investigation reveals that, for a conformal junction, the field‐effect passivation is diminished due to the formation of weak electrical field zones beneath the pyramid vertices, which is usually the case when homojunction emitters are formed by thermal diffusion on micropyramid textured surfaces. In contrast, thermal diffusion in nanoscale pyramid textured surfaces typically leads to non‐conformal dopant profiles, resulting in flatter junctions and yielding stronger field passivation effect by preventing the formation of these weak electrical field zones. Experimentally, enhanced field‐effect passivation is indirectly observed in terms of improvement in the effective minority‐carrier lifetimes when substituting the standard micropyramid texturing by nanoscale pyramid gratings. At the device level, we demonstrate that the enhancement in the field‐effect passivation increases the open‐circuit voltage with respect to the micropyramid texture under the conditions of comparable chemical passivation and surface‐area increase.

Reservoir Computing with Random Skyrmion Textures

The Reservoir Computing (RC) paradigm posits that sufficiently complex physical systems can be used to massively simplify pattern recognition tasks and nonlinear signal prediction. This work demonstrates how random topological magnetic textures present sufficiently complex resistance responses for the implementation of RC as applied to A/C current pulses. In doing so, we stress how the applicability of this paradigm hinges on very general dynamical properties which are satisfied by a large class of physical systems where complexity can be put to computational use. By harnessing the complex resistance response exhibited by random magnetic skyrmion textures and using it to demonstrate pattern recognition, we explain how spintronically accessible magnetic systems offer an advantage in the search for an ideal reservoir computer. The low-power properties of compact skyrmion fabrics, coupled with their CMOS integrability operating on similar length and timescales, open the door for their RC employment geared towards industrial application.

Reduce the Planar Anisotropy of AA6016 Aluminum Sheets by Texture and Microstructure Control

In order to produce a more isotropic Al-Mg-Si alloy sheet in the T4 temper, pre-annealed AA6016 hot rolled strips were cold rolled by conventional rolling, transverse rolling and an alternative rolling schedule. In this work, a weak and random texture was obtained in the alternative rolling sample, which was treated by solution treatment, as well as a fine and homogeneous recrystallized grain structure that reduced the earing percentage from 8.2% to 2.7%. An earing test was used to characterize the planar anisotropy of the AA6016 alloy. The crystallographic texture and microstructure of the AA6016 aluminum sheet were analyzed by X-ray diffraction and electron back scatter diffraction (EBSD) techniques. The earing percentage was reduced and eight-fold ears were produced in unidirectional rolled samples with strong β-fiber textures. Conversely, a higher earing percentage and four-fold ears were obtained for the alternative rolled sample, which was characterized by an appropriate combination of the Cube {001}&lt;100&gt; and stabilized BND {011}&lt;3`22&gt; [(φ1,¢,φ2) = (42°,45°,0°)] orientations. The main reason for the distinct earing profiles was the grain spatial distribution of textures formed during the cold rolling process. The dynamic recovery of the AA6016 alloy was promoted and both the nucleation and subsequent growth of the Cube orientation were suppressed by alternative rolling.

A Study of the Microstructure, Texture and Tensile Properties of 1060/Al-TiC/1060 Sandwich Composites Prepared by Hot-Roll Bonding

Microstructure and texture development in Al/AMCs sandwich composites and the connection between the tensile properties and microstructure/texture have not been fully understood. In this study, the AA 1060 aluminum alloy and spark plasma sintering (SPS) processed Al-TiC composite were prepared into the 1060/Al-TiC/1060 sandwich composites by hot-roll bonding (HRB). The influence of rolling reduction on the microstructure, texture and tensile properties was studied. An inhomogeneity of microstructure through the thickness of Al layer was observed after the HRB process. The grains at the surface Al layer were tilted to 19 deg with respect to the rolling direction after 34.8 pct reduction, and the tilted grains were developed to a deeper region with increasing rolling reduction. The degree of grain-subdivision and number of high-angle boundaries decreased as the observed area moved from the surface to the interface. The cube texture at the surface of the Al layer transformed into the rotated-cube shear texture during HRB process. The strength of the rotated-cube texture at the interface layer was lower than at the surface layer. The initial random texture in the Al-TiC layer was changed to the α-fiber and β-fiber rolling textures after the HRB process. The yield strength and ultimate tensile strength of the sandwich composites increased with increasing rolling reduction, and the sandwich composites showed a high elongation with 43.0 pct reduction.