Tomography of Materials and Structures最新文献

{"title":"Photo-oxidation of semicrystalline polymers: Effect of stress triaxiality on ductility","authors":"K.N. Cundiff ,&nbsp;T.F. Morgeneyer ,&nbsp;A.A. Benzerga","doi":"10.1016/j.tmater.2025.100048","DOIUrl":"10.1016/j.tmater.2025.100048","url":null,"abstract":"<div><div>The effect of stress triaxiality on the strain-to-fracture of as-received and photo-oxidized polyamide-6 (PA-6) was investigated using mechanical testing, synchrotron X-ray tomography, and finite element analyses. Mechanical tests were conducted on cylindrical and round notched specimens, where different notch radii were used to vary the stress triaxiality. The specimens were aged by exposure to ultra-violet (UV) radiation at 60^∘, causing photo-oxidation. As-received and so-aged specimens were loaded to failure (complete loss of load carrying capacity). For both unaged and aged specimens, a higher triaxiality led to a lower strain-to-fracture. To elucidate the micromechanical damage that mediates fracture in both conditions, specimens with an intermediate notch sharpness were loaded to the peak load, unloaded, and scanned <em>ex situ</em> using synchrotron X-ray tomography. Damage in the unaged bar was found to occur by cavitation and was concentrated at the center of the specimen, where the triaxiality is highest. In the UV-aged bar, a network of inter-connected chemical cracks were found on the notch surface, where the triaxiality is lowest. Finite element analyses were deployed to approximate the local triaxiality at damaged regions in the unaged and UV-aged specimens using a constitutive relation for semicrystalline polymers. From these analyses, the relationship between local triaxiality and strain-to-fracture was quantified for both unaged and photo-oxidized PA-6. Both unaged and photo-oxidized PA-6 showed similar decreases in ductility with triaxiality, hinting at common ductile fracture processes.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100048"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geo-SegNet: A contrastive learning enhanced U-net for geomaterial segmentation","authors":"Qinyi Tian ,&nbsp;Sara Goodhue ,&nbsp;Hou Xiong ,&nbsp;Laura E. Dalton","doi":"10.1016/j.tmater.2025.100049","DOIUrl":"10.1016/j.tmater.2025.100049","url":null,"abstract":"<div><div>X-ray micro-computed tomography scanning and tomographic image processing is a robust method to quantify various features in geomaterials. The accuracy of the segmented results can be affected by factors including scan resolution, scanning artifacts, and human bias. To overcome these limitations, deep learning techniques are being explored to address these challenges. In the present study, a novel deep learning model called Geo-SegNet was developed to enhance segmentation accuracy over traditional U-Net models. Geo-SegNet employs contrastive learning for feature extraction by integrating this extractor as the encoder in a U-Net architecture. The model is tested using 10 feet of sandstone cores containing significant changes in porosity and pore geometries and the segmentation results are compared to common segmentation methods and U-Net. Compared to a U-Net-only model, Geo-SegNet demonstrates a 2.0 % increase in segmentation accuracy, indicating the potential of the model to improve the segmentation porosity which can also improve subsequent metrics such as permeability.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100049"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synchrotron computed tomography of 5000 years old faience beads from Southeastern Anatolia (Türkiye)","authors":"Gonca Dardeniz ,&nbsp;Gülistan Büyükgedik ,&nbsp;Onur Kaya ,&nbsp;Suat Özkorucuklu ,&nbsp;Fareeha Hameed ,&nbsp;Gianluca Iori","doi":"10.1016/j.tmater.2025.100056","DOIUrl":"10.1016/j.tmater.2025.100056","url":null,"abstract":"<div><div>This article highlights the use of synchrotron X-ray computed tomography (SXCT) in examining the production technology of two faience beads dating to 3000 BCE (5000 BP). Through one blue and one green colored sample, we discuss the competence of the ID10-BEATS beamline at SESAME (Jordan) for non-invasive analysis of archaeological objects. We present different protocols for the examination of silica-based objects with sub-cm size using SXCT. The results validate the cementation technique for the production of tiny beads (≤ 1 cm). The application of high-resolution 3D imaging, in combination with X-ray phase-contrast enhancement, allows for the non-invasive characterization of faience production, which opens a venue for broader discussions on ancient technology and technological knowledge transfer among ancient communities in Southwest Asia.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100056"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143474768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trajectory optimization for few-view robot-based CT: Transitioning from static to object-specific acquisition geometries","authors":"Maximilian Linde ,&nbsp;Wolfram Wiest ,&nbsp;Anna Trauth ,&nbsp;Markus G.R. Sause","doi":"10.1016/j.tmater.2025.100058","DOIUrl":"10.1016/j.tmater.2025.100058","url":null,"abstract":"<div><div>The advent of robot-based computed tomography systems accelerated the development of trajectory optimization methodologies, with the objective of achieving superior image quality compared to standard trajectories while maintaining the same or even fewer number of required projections. The application of standard trajectories is not only inefficient due to the lack of integration of available prior knowledge about the object under investigation but also suboptimal because of limited accessibility issues during scans of large components, which are common in robot-based computed tomography. In this work, we introduce an object-specific trajectory optimization technique for few-view applications, based on a 3D Radon space analysis using a <em>RANSAC</em> algorithm. In contrast to existing methods, this approach allows for object geometry specific projection views, which are no longer constrained by discretized initial view sets on predefined acquisition geometries. In addition to eliminating the effects of discretized initial sets, this technique offers a distinct advantage in scenarios of limited accessibility by enabling the avoidance of collision elements, unlike trajectory optimizations on predefined acquisition geometries and standard trajectories. Our results show that the presented technology outperforms standard trajectories of evenly distributed projection views on predefined geometries in both ideal accessibility and limited accessibility scenarios. According to the employed geometry-based image quality metrics, our approach allows for reductions of more than 50 % in the number of projection views while maintaining equivalent image quality.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100058"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143550149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Visualizing pulp fibers using X-ray tomography: Enhancing the contrast by labeling with iron oxide nanoparticles and the use of immersion oil","authors":"Anderson T.V. Veiga ,&nbsp;Elisa S. Ferreira ,&nbsp;James Drummond ,&nbsp;Lewis Mason ,&nbsp;Samuel N.M. Brown ,&nbsp;André Phillion ,&nbsp;D. Mark Martinez ,&nbsp;Emily D. Cranston","doi":"10.1016/j.tmater.2025.100051","DOIUrl":"10.1016/j.tmater.2025.100051","url":null,"abstract":"<div><div>In this study, we present a protocol to visualize the architecture of tracer fibers in paper using X-ray tomography. We prepared tracer fibers by depositing iron oxide nanoparticles on the surface of select papermaking fibers, through a multicycle labeling technique that achieved 14 wt% of iron. Labeled and unlabeled fibers on their own, as well as laboratory-formed paper containing a small fraction of the tracer fibers, were imaged in air and after immersion in a non-polar oil. We found that labeled fibers could be segmented from the background through simple binarization when in the immersed state whereas segmentation failed when the samples were imaged in air. We propose that the oil served as a mask, created through compositional and density matching of the unlabeled fibers to the saturated void volume. This new labeling and immersion protocol opens avenues to enhance the contrast of tracers for improved characterization of cellulosic materials via X-ray tomographic imaging in an approach that does not require advanced image processing methods for segmentation.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100051"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of AI crack segmentation models for additive manufacturing","authors":"Tebogo Ledwaba ,&nbsp;Christine Steenkamp ,&nbsp;Agnieszka Chmielewska-Wysocka ,&nbsp;Bartlomiej Wysocki ,&nbsp;Anton du Plessis","doi":"10.1016/j.tmater.2025.100053","DOIUrl":"10.1016/j.tmater.2025.100053","url":null,"abstract":"<div><div>The use of X-ray computed tomography (XCT) has seen significant growth over a broad range of disciplines including biology, earth science, engineering, and many more. It is now increasingly used in additive manufacturing (AM) since its benefits are being appreciated more widely. This is due to the method being non-destructive and comprehensive, providing external and internal information of tested parts. Data processing and segmentation of XCT data is important to get as much information as possible so that a clear picture of features can be obtained and analyzed. Porosity analysis has been the most successful and widely used XCT analysis type in all fields so far, partly due to simple manual segmentation methods such as the Otsu global threshold. However, segmentation of small and narrow features such as cracks are challenging with conventional thresholding methods. Since automated conventional methods fail, manual segmentation is often used but this can be subjective, tedious, and prone to segmentation errors. The present work employs neural networks, specifically the U-Net architecture and thoroughly investigates possible solutions to a robust crack segmentation model. Intensity scale calibration, bias training weights and data augmentations were investigated in detail to find the best possible performance of trained models, when employed on new data. The results demonstrate the performance and improvement gained by each of the above factors, as well as the successful AI segmentation for various additively manufactured sample types with different cracks. This method enables clear visualization and presentation of cracks, as well as their quantification. The model strives toward a generic crack segmentation model for all AM parts that could be used directly by others. This generalizability of the model is discussed together with its limitations.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100053"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning-supported visual analytics for high resolution X-ray inspection of metal matrix composites","authors":"Thomas Lang ,&nbsp;Anja Heim ,&nbsp;Christoph Heinzl","doi":"10.1016/j.tmater.2024.100047","DOIUrl":"10.1016/j.tmater.2024.100047","url":null,"abstract":"<div><div>Metal matrix composites are utilized in a multitude of applications due to their mechanical and thermodynamical properties, which are highly dependent on the microstructure. A detailed characterization is thus vital for a sound understanding of the material’s properties. X-ray computed tomography, in particular high resolution synchrotron imaging, presents a promising inspection method for this purpose. However, a high-resolution inspection of medium-sized samples produces very large volumetric datasets, which prevents a proper data analysis with commonly available tools and software. We propose a workflow for analyzing large volumetric datasets of particle-reinforced metal matrix composites, from 3D renderings of the datasets to qualitative and quantitative characterizations of the material regarding shape and spatial distribution of the contained particles. Each step in this workflow is designed to be applicable to arbitrarily large volumetric datasets. Application-dependent visualizations facilitate derived secondary information to become accessible, generating in-depth insights despite the large number of particles. The workflow is demonstrated on a large high-resolution dataset in qualitative and quantitative evaluations, whose visual representations confirm that the distribution of particles within the sample is quite homogeneous albeit the presence of minor agglomerations.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100047"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental method for rubber deformation analysis using in situ X-ray tomography and digital volume correlation with FEM validation","authors":"J. Lachambre ,&nbsp;A. Sibellas ,&nbsp;J. Adrien ,&nbsp;J. Papillon ,&nbsp;R. Bruant ,&nbsp;G. Maurel ,&nbsp;E. Maire","doi":"10.1016/j.tmater.2024.100045","DOIUrl":"10.1016/j.tmater.2024.100045","url":null,"abstract":"<div><div>The grip and rolling resistance of car wheel tires on a road surface is strongly influenced by the mechanical properties of the rubber and especially by the deformation of this rubber during indentation by the road asperities. This paper presents the results of a simplified indentation experiment. A cylindrical block of rubber containing microstructural markers is indented by a sphere in situ inside an X-ray Computed Tomograph. The presence of markers intentionally added to the rubber gum allows us, after suitable image processing for contrast improvement, to measure with a very good precision the displacement field inside the rubber during the indentation using Digital Volume Correlation. The measured displacement is compared with the result of an axisymmetric finite element modeling calculation reproducing the experimental configuration. The close correlation between measured displacements and finite element modeling shows that the proposed method is suitable for studying rubber/road contact.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100045"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New watershed methods for isolating and characterizing discrete objects in 3D data sets","authors":"Richard A. Ketcham","doi":"10.1016/j.tmater.2024.100043","DOIUrl":"10.1016/j.tmater.2024.100043","url":null,"abstract":"<div><div>This paper introduces new algorithms for conducting and improving watershed analysis, implemented with the particular goal of improving the ability to measure the shapes of mineral grains to be subsequently be analyzed by mass spectrometry. This application requires a high degree of accuracy and fidelity in terms of both separating all touching grains and preserving their shapes. The algorithms are designed to take advantage of a vector-based programming environment. A new implementation of the Euclidean distance transform utilizes the fact that the distance from any adjacent pair of voxels to the nearest boundary must be within one voxel of each other. In practice, however, this algorithm is outperformed by a smoothed approximate distance transform that is faster to compute and results in less irregular watershed boundaries. A one-pass rainfall-based watershed algorithm is introduced that runs in linear time with the number of segmented voxels, and requires no priority queue. Unlike marker-based watershed algorithms based on the basin-filling approach, the rainfall approach finds watersheds associated with all local maxima in the distance map, even if a marking algorithm is used. A post-watershed smoothing algorithm improves watershed boundaries and eliminates small spurious watersheds. The one-pass watershed and post-watershed smoothing algorithms run in times superior or comparable to basin-fill watershed algorithms implemented in other environments, and offers excellent ability to separate touching objects efficiently while placing watershed boundaries that maximize the preservation of details of particle shape. Further time improvement could come from implementing them in a vector-based environment that allows explicit multi-threading.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100043"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Screening staining agents for contrast-enhanced microCT of vascular tissues: Assessing the effect on microstructural and mechanical properties","authors":"M. Pétré ,&nbsp;T. Balcaen ,&nbsp;P. Schneidewind ,&nbsp;L. Mazy ,&nbsp;G. Pyka ,&nbsp;H. Fehervary ,&nbsp;N. Famaey ,&nbsp;G. Kerckhofs","doi":"10.1016/j.tmater.2024.100038","DOIUrl":"https://doi.org/10.1016/j.tmater.2024.100038","url":null,"abstract":"<div><p>Cardiovascular tissues possess a complex microstructure, which remodel and adapt due to ageing and diseases. This complex and evolving microstructure is intrinsically linked to the tissue’s mechanical properties. To better understand how changes in the microstructure can impact the mechanical behavior, 4D-contrast-enhanced microCT (4D-CECT) can be used (i.e. in situ mechanical loading combined with 3D microstructural visualization). Since absorption-based CECT requires the use of contrast-enhancing staining agents (CESAs), we investigated six different CESAs for their suitability for 4D-CECT imaging of arterial tissue, considering their ability to provide good microstructural visualization and segmentation while ensuring the preservation of the mechanical properties. For this purpose, the penetration speed, contrast-enhancement, volume change, and stiffness change of porcine arterial tissue stained with the different CESA solutions were studied. Based on our results, we selected 1:2 Hafnium-substituted Wells-Dawson Polyoxometalate as the most suited CESA for 4D-CECT of arterial tissue. Phosphotungstic acid (PTA) and Lugol iodine with Sorensen’s buffer (Lugol), despite being the reference in the state-of-the-art as CESA and having excellent contrast-enhancement properties, were the only ones that significantly affected the mechanical properties of porcine arterial tissue. Additionally, for these two solutions, tissue shrinkage was observed, resulting in a volume reduction of approximately − 12 % for PTA and − 17 % for Lugol. Finally, it was observed that the penetration speed of all CESA solutions exhibited a ratio of 60–40 % from the intimal side to the adventitial side, which is likely due to the denser packing of elastic lamellae towards the adventitia. Overall, our study offers valuable new insights for selecting and comparing various CESA solutions for (4D-)CECT.</p></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"6 ","pages":"Article 100038"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949673X24000159/pdfft?md5=d84ff581b2d4237b266e6598bde3236a&pid=1-s2.0-S2949673X24000159-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141582162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}