Tomography of Materials and Structures最新文献

{"title":"MicroCT-based vascular imaging in bone and peri-implant tissues","authors":"David Haberthür ,&nbsp;Oleksiy-Zakhar Khoma ,&nbsp;Tim Hoessly ,&nbsp;Eugenio Zoni ,&nbsp;Marianna Kruithof-de Julio ,&nbsp;Stewart D. Ryan ,&nbsp;Myriam Grunewald ,&nbsp;Benjamin Bellón ,&nbsp;Rebecca Sandgren ,&nbsp;Stephan Handschuh ,&nbsp;Benjamin E. Pippenger ,&nbsp;Dieter Bosshardt ,&nbsp;Valentin Djonov ,&nbsp;Ruslan Hlushchuk","doi":"10.1016/j.tmater.2025.100074","DOIUrl":"10.1016/j.tmater.2025.100074","url":null,"abstract":"<div><div>Angiogenesis is essential for skeletal development, bone healing, and regeneration. Improved non-destructive, three-dimensional (3D) imaging of the vasculature within bone tissue benefits many research areas, especially implantology and tissue engineering. X-ray microcomputed tomography (microCT) is a well-suited non-destructive 3D imaging technique for bone morphology. For microCT-based detection of vessels, it is paramount to use contrast enhancement. Limited differences in radiopacity between perfusion agents and mineralized bone make their distinct segmentation problematic and have been a major drawback of this approach. A decalcification step resolves this issue but inhibits the simultaneous assessment of bone microstructure and vascular morphology. The problem of contrasting becomes further complicated in samples with metal implants. This study describes contrast-enhanced microCT-based visualization of vasculature within bone tissue in small and large animal models, also in the vicinity of the metal implants. We present simultaneous microvascular and bone imaging in murine tibia, a murine bone metastatic model, the pulp chamber, gingiva, and periodontal ligaments. In a large animal model (minipig), we performed visualization and segmentation of different tissue types and vessels in the hemimandible containing metal implants. We further demonstrate the potential of dual-energy imaging in distinguishing bone tissue from the applied contrast agents. This work introduces a non-destructive approach for 3D imaging of vasculature within soft and hard tissues near metal implants in a large animal model.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"9 ","pages":"Article 100074"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144535098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Boosting Noise2Inverse via Enhanced Model Selection for Denoising Computed Tomography Data","authors":"Austin Yunker ,&nbsp;Peter Kenesei ,&nbsp;Hemant Sharma ,&nbsp;Jun-Sang Park ,&nbsp;Antonino Miceli ,&nbsp;Rajkumar Kettimuthu","doi":"10.1016/j.tmater.2025.100075","DOIUrl":"10.1016/j.tmater.2025.100075","url":null,"abstract":"<div><div>Synchrotron-based x-ray tomographic imaging enables the examination of the internal structure of materials at high spatial and temporal resolution. Experimental constraints can impose dose and time limits on the measurements, introducing a higher level of noise and artifacts in the reconstructed images. Deep learning has emerged as a powerful tool to remove noise from reconstructed images. Recently, the Noise2Inverse method was designed specifically for denoising reconstructed images without requiring paired noisy and clean images. This method creates multiple statistically independent reconstructions used to pair the data in which training involves transforming one reconstruction into the other, and vice versa. Originally designed to be used after a fixed number of epochs, we see in practice that this approach may not produce the optimal model and may unnecessarily waste computational resources. Therefore, we propose an alternative method of identifying the best model during training that aligns with the Noise2Inverse method. During validation, we compare the model output of the multiple reconstructions among each other. We hypothesize that the best model is the one that produces images with the highest similarity, implying a convergence in the predicted material properties and absorption values. To compare model outputs, we consider the absolute error, square error, structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and cosine similarity. We evaluate our method on two simulated tomography datasets and two, real-world, low-contrast, high-energy x-ray tomography datasets. We show our approach is more effective at determining the best model, up to an increase of 12.50% and 12.53% in SSIM and PSNR, respectively, while only requiring a fifth of the training time compared to the original approach.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"9 ","pages":"Article 100075"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144827475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correlative X-ray and electron tomography for scale-bridging, quantitative analysis of complex, hierarchical particle systems","authors":"Alexander Götz ,&nbsp;Fabian Lutter ,&nbsp;Dennis Simon Possart ,&nbsp;Daniel Augsburger ,&nbsp;Usman Arslan ,&nbsp;Sabrina Pechmann ,&nbsp;Carmen Rubach ,&nbsp;Moritz Buwen ,&nbsp;Umair Sultan ,&nbsp;Alexander Kichigin ,&nbsp;Johannes Böhmer ,&nbsp;Nora Vorlaufer ,&nbsp;Peter Suter ,&nbsp;Tor Hildebrand ,&nbsp;Matthias Thommes ,&nbsp;Peter Felfer ,&nbsp;Nicolas Vogel ,&nbsp;Katharina Breininger ,&nbsp;Silke Christiansen ,&nbsp;Benjamin Apeleo Zubiri ,&nbsp;Erdmann Spiecker","doi":"10.1016/j.tmater.2025.100069","DOIUrl":"10.1016/j.tmater.2025.100069","url":null,"abstract":"<div><div>This study presents a comprehensive workflow for investigating particulate materials through combined 360° electron tomography (ET), nano-computed X-ray tomography (nanoCT), and micro-computed X-ray tomography (microCT), alongside a versatile sample preparation routine. The workflow enables the investigation of size, morphology, and pore systems across multiple scales, from individual particles to large hierarchical structures. A customized tapered sample shape is created using focused ion beam milling to optimize the field of view for each imaging technique. This design enables high-resolution analysis of small volumes containing single particles using nanoCT and large-scale studies of thousands of particles for statistical significance using microCT. By correlating data from identical locations across different microCT and nanoCT imaging modalities - without any additional preparation that could affect the sample in between - the presented approach improves the precision of quantitative analyses. The study highlights the importance of cross-scale, correlative three-dimensional microscopy for a comprehensive understanding of complex hierarchical materials. Precise data registration, segmentation using machine learning, and multimodal imaging techniques are crucial for unlocking insights into process-structure-property relationships and thus to optimize functional, hierarchical materials.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"9 ","pages":"Article 100069"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144298110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced microscopy probes for geomaterials – Current state of the art and future perspectives","authors":"Joe Stickland ,&nbsp;Laurenz Schröer ,&nbsp;Florian Buyse ,&nbsp;Alexandra Guedes ,&nbsp;Håvard Haugen ,&nbsp;Ragnvald Mathiesen ,&nbsp;Dag W. Breiby ,&nbsp;Veerle Cnudde ,&nbsp;Basab Chattopadhyay","doi":"10.1016/j.tmater.2025.100073","DOIUrl":"10.1016/j.tmater.2025.100073","url":null,"abstract":"<div><div>Geomaterials form the basis of our planet. With structural features spanning from the nanometre- to the continental-scale, geomaterials possess a complex but fascinating hierarchical structure that allows us to investigate their formation’s associated physical, chemical, and biological processes. Geomaterials provide us insights into the formation and evolution of the Earth as well as the origin of life as preserved in fossilised remains of microorganisms. Microscopy is perhaps the most powerful tool that helps us to appreciate and understand geomaterials. With rapid advances in experimental science during the last several decades, we can now image internal structures and follow internal dynamic processes in real-time in three dimensions (3D). A wide range of current 3D imaging methodologies have emerged that help us understand and observe geomaterials’ relevant structural features. Attenuation-based 3D X-ray tomography is the most used micro-scale technique, which can be paired with complementary techniques to highlight more features and details within geomaterials. This review documents the relevant complementary microscopy modalities: phase contrast and diffraction contrast X-ray tomography, neutron tomography and electron tomography, and other methods like atom probe tomography and chemical- and structural-specific Raman imaging. This review article aims to provide an overview of a wide range of microscopy methodologies (for researchers) and the insight that can be garnered from their use with geomaterials.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"9 ","pages":"Article 100073"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144517526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review of in-situ mechanical testing combined with X-ray microfocus computed tomography: Application and current challenges for biological tissues","authors":"Lara Mazy ,&nbsp;Greet Kerckhofs","doi":"10.1016/j.tmater.2025.100062","DOIUrl":"10.1016/j.tmater.2025.100062","url":null,"abstract":"<div><div>Biological tissues undergo physiological mechanical loading during their functioning <em>in vivo</em>. To properly respond to these mechanical signals, tissues have a highly complex microstructural organization. However, there is not yet sufficient knowledge about the link between their microstructural organization and their mechanical behaviour. Therefore, there is a need for methods to dynamically assess how the microstructure of biological tissues changes during mechanical loading. 4D-µCT is an imaging technique combining mechanical testing with X-ray microfocus computed tomography (µCT) imaging. It has been extensively used to visualize, at the micro-scale and in full 3D, the deformation of the microstructure of non-biological materials during mechanical loading. Additionally, postprocessing of the 4D-µCT datasets allowed 3D strain field calculations. This review aims to provide an overview of the current state of the art of the use of 4D-µCT specifically for the assessment of the mechanical behavior of biological tissue, and this both for mineralized and unmineralized tissues. We highlighted the advancements as well as the current limitations and challenges to overcome, such as the need for complex loading modes, the effect of X-rays on the mechanical behavior and the need to keep the samples hydrated during testing. We finally conclude with some future perspectives.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"8 ","pages":"Article 100062"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143820723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing µCT resolution in tarsal bones: A comparative study of super-resolution models for trabecular bone analysis","authors":"Sascha Senck ,&nbsp;Patrick Weinberger ,&nbsp;Lukas Nepelius ,&nbsp;Andreas Haghofer ,&nbsp;Birgit Woegerer ,&nbsp;Jonathan Glinz ,&nbsp;Miroslav Yosifov ,&nbsp;Lukas Behammer ,&nbsp;Johann Kastner ,&nbsp;Klemens Trieb ,&nbsp;Elena Kranioti ,&nbsp;Stephan Winkler","doi":"10.1016/j.tmater.2025.100063","DOIUrl":"10.1016/j.tmater.2025.100063","url":null,"abstract":"<div><div>Microcomputed tomography (µCT) is an essential tool for analyzing trabecular bone microarchitecture, yet its resolution is constrained by object size and acquisition time. To overcome these limitations, we implement a deep-learning-based super-resolution (SR) approach that enhances µCT image resolution while significantly reducing scan durations. Dry isolated tarsal bones (intermediate cuneiform) from 20 specimens were scanned using µCT at two resolutions, 80 µm voxel size (low resolution, LowRes) and 20 µm voxel size (high resolution, HiRes). Aligned LowRes and HiRes µCT data served as training data for SR reconstruction. In this study, we compare five SR models: 2D U-Net+ +, 3D SRCNN, 3D FSRCNN, 3D U-Net and a modified 3D U-Net model trained with a combined learned perceptual image patch similarity (LPIPS) and structural similarity (SSIM) loss function. The focus of this contribution is the application of these models based on real µCT data, rather than synthetically degraded images. Models were trained to learn volumetric representations for accurate restoration of trabecular bone microstructure. To assess SR image quality, we computed three image quality metrics (peak signal-to-noise ratio, SSIM and LPIPS) and evaluated bone morphometric parameters, i.e. average trabecular thickness (Tb.Th.) and bone volume fraction (BV/TV), across 95 regions of interest (ROI). RMSE was calculated for LowRes data and each SR model relative to HiRes data to quantify prediction accuracy. The results demonstrate that the 3D U-Net (LPIPS &amp; SSIM) model achieves the highest reconstruction accuracy, yielding the lowest RMSE values (12.93 µm for Tb.Th. and 1.3 % for BV/TV), outperforming all other SR models in our evaluation. Compared to standard low-resolution µCT, our approach reduces scan time from 58 min to 7 min per sample while preserving trabecular morphology with high fidelity. These results demonstrate the effectiveness of perceptual loss-based SR to real µCT data for morphological analysis, ensuring accurate trabecular reconstruction and mitigating overestimation artifacts caused by LowRes imaging and partial volume effects. Integrating SR with real µCT scans offers a promising strategy to reduce scan time to improve throughput in bone imaging workflows. Future work will expand the training dataset to enhance model generalization across diverse bone structures and imaging conditions.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"8 ","pages":"Article 100063"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"WebCT – OpenSource web-based GUI for real-time X-ray simulation","authors":"Iwan T. Mitchell ,&nbsp;Jean Michel Létang ,&nbsp;Llion Marc Evans ,&nbsp;Franck P. Vidal","doi":"10.1016/j.tmater.2025.100057","DOIUrl":"10.1016/j.tmater.2025.100057","url":null,"abstract":"<div><div>Scan planning for X-ray CT systems can be difficult due to the large number of elements affecting scan quality. The use of X-ray simulation can answer feasibility questions, however existing methods are focused on experts who are familiar with XCT and programming knowledge. WebCT is a user-centric application for performing virtual XCT scans with the validated X-ray simulator gVirtualXray. Focused on accessibility, the interface allows changing all scanning parameters; from tube characteristics to detector energy response, while allowing full-scale simulation and reconstruction in minutes. WebCT is available as a free, open-source application, giving full control over a virtual lab-CT or synchrotron system. Configurations can be saved, shared, or even imported from many popular XCT dataset formats. We demonstrate in this paper the use of WebCT as a scan planning tool, using a simple CAD mockup to select filtration based on transmission before scanning.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"8 ","pages":"Article 100057"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143680562","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":"Coupling X-ray µCT, BSE, and QEMSCAN imaging to unravel details of water saturation and oil trapping in a Brazilian Pre-salt carbonate under oil-wet conditions","authors":"Ronaldo Herlinger Junior ,&nbsp;Mark Knackstedt ,&nbsp;Benjamin Young ,&nbsp;Lydia Knuefing ,&nbsp;Alexandre Campane Vidal","doi":"10.1016/j.tmater.2025.100061","DOIUrl":"10.1016/j.tmater.2025.100061","url":null,"abstract":"<div><div>The study of fluid saturation and oil entrapment in reservoirs is of great importance for understanding and characterizing multiphase flow, with economically significant implications. In this context, we examine the fluids configuration under oil-wet conditions in particulate carbonate reservoirs of the Brazilian Pre-salt, which host large quantities of oil. Hence, we conducted drainage and imbibition cycles on a grainstone carbonate sample from the Barra Velha Formation of Brazil’s Pre-salt integrating X-ray tomography, backscattered electrons (BSE), and QEMSCAN (quantitative evaluation of minerals by scanning electron microscopy) to understand fluid saturation and oil trapping under oil-wet conditions at pore-scale. The integration of µCT imaging with BSE and QEMSCAN significantly enhances our understanding of fluid saturation within the pore system, particularly in regions where X-ray imaging alone encounters limitations. QEMSCAN imaging, beyond resolving microporosity, provides critical insights into the mineralogical factors influencing fluid distribution, offering a deeper perspective on the saturation controls. Following the drainage and aging cycles, oil effectively displaced nearly all brine within the interparticle macropores, relegating the brine to small, isolated droplets formed through snap-off processes. Additionally, a significant proportion of intraparticle micro and macroporosity was occupied by oil after drainage, with further oil saturation occurring during aging, demonstrating the rock’s oil-wet affinity. Post-forced imbibition imaging revealed that nearly all the oil initially present in the interparticle macropores had been replaced by water, with only minor traces of oil remaining as thin films on mineral surfaces. Conversely, the intraparticle macro and micropores, which are typically less connected, retained most of the oil, highlighting the porous medium’s tendency to trap fluids in poorly connected regions. Finally, our experiments did not reveal any substantial effect of mineralogical variations on fluid saturation during any phase of the cycles. This suggests that the observed oil-wet condition is independent of relative mineralogical variations, particularly given the sample's dominance of calcite and dolomite. These results, although obtained from a facies type common in the Brazilian Pre-salt, elucidate the behavior in oil-wettable reservoirs, a common condition in various reservoirs around the world.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"8 ","pages":"Article 100061"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785785","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":"Spectral X-ray computed tomography for the chemical identification of critical minerals","authors":"Florian Buyse ,&nbsp;Matthieu N. Boone ,&nbsp;Frederic Van Assche ,&nbsp;Stéphane Faucher ,&nbsp;Peter Moonen ,&nbsp;Stijn Dewaele ,&nbsp;Veerle Cnudde","doi":"10.1016/j.tmater.2025.100059","DOIUrl":"10.1016/j.tmater.2025.100059","url":null,"abstract":"<div><div>Differentiating minerals using high-resolution X-ray tomography (µCT) relies on distinct differences in the attenuation coefficient <em>µ</em>. The <em>µ</em> value depends on an interplay between the material density <em>ρ</em> and the effective atomic number <em>Z</em>_<em>eff</em> of a mineral phase. Difficulties in identifying mineral phases arise when this interplay gives similar <em>µ</em> values and thus limited contrast within µCT images. Untangling these two dependencies is essential to improve the three-dimensional chemical identification of critical minerals. Lab-based methods and techniques often incorporate different measures, but only show a limited application potential on multiphase geological samples. Using high-<em>Z</em> spectral laboratory-based µCT we studied the potential of directly identifying chemical elements within the practical margins of high-<em>Z</em> spectral detectors. This paper compares the results from three mineral deposits using two spectral µCT setups. Chemical elements with a <em>Z</em> higher than molybdenum and a concentration of at least some weight percentage were correctly identified using K-edge imaging. The suitability of the different high-<em>Z</em> spectral detectors depends largely on the availability of prior knowledge of the sample composition. Quantifying elemental concentrations is element- and sample specific and currently does not allow for optimal automated mineralogy solutions. Improving the three-dimensional identification of minerals can be achieved with dedicated analyses of the energy-dependent <em>µ</em> curve and therefore will remain the focus of future work.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"8 ","pages":"Article 100059"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143591726","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":"Measuring thermal curing induced shrinkage of material extrusion based additive manufacturing silicone elastomer lattices by X-ray computed tomography","authors":"Massimiliano Ferrucci ,&nbsp;Anne-Françoise Obaton ,&nbsp;Robert Cerda ,&nbsp;Brian Au ,&nbsp;Nicholas Rodriguez ,&nbsp;Ziad Ammar ,&nbsp;Gabriel Balensiefer ,&nbsp;Chuck Divin ,&nbsp;Jeremy Lenhardt ,&nbsp;Brian Giera","doi":"10.1016/j.tmater.2025.100064","DOIUrl":"10.1016/j.tmater.2025.100064","url":null,"abstract":"<div><div>Thermal curing induces shrinkage in material extrusion based additive manufacturing silicone elastomer samples, resulting in discrepancies between as printed and final geometries. Knowing the extent to which the samples change in shape and size allows us to make appropriate modifications to the printing design to better control the geometry of the samples. We present an X-ray computed tomography (CT) based approach to determine filament-level shrinkage due to thermal curing of silicone elastomer samples printed with direct ink writing (DIW). The approach relies on custom-designed build plates that are resistant to the elevated curing temperatures and that have sufficiently distinct X-ray absorption characteristics from the silicone elastomer to ensure adequate segmentation of the latter in X-ray imaging data. We implement the approach to evaluate shrinkage in DIW ‘log pile’ samples with three distinct strand arrangements and demonstrate of how filament-level information can be extracted from the X-ray CT data.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"8 ","pages":"Article 100064"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143820724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}