Search Results (176)

This paper presents the results of a comprehensive technological study of three bronze sculptures from the Jin Empire period (1115–1234 AD) from the collection of the Museum of Archaeology and Ethnography at the Institute of History, Archaeology and Ethnography of the Peoples of the Far East, Far Eastern Branch of the Russian Academy of Sciences (IHAE FEB RAS). Using photon-counting computed tomography (PCCT) and energy-dispersive X-ray spectroscopy (EDS), the production techniques were reconstructed, differences in alloy composition were identified, and specific features of the casting processes were determined. Tomographic analysis revealed two fundamentally different manufacturing approaches: a multi-stage technology involving the use of different alloys and the assembly of separately cast elements, and a single-cast technology with a homogeneous structure. Elemental analysis of the three sculptures using EDS demonstrated significant compositional variability—from 21% to 67% copper and from 9% to 69% tin in different parts of the objects—confirming the complexity of the technological processes. An expanded study of 20 bronze sculptures using portable X-ray fluorescence analysis (pXRF) allowed for the identification of four typological alloy groups: classic balanced lead–tin bronzes (Cu 30–58%, Sn 16–23%, Pb 16–28%), high-lead bronzes (Pb up to 52%), high-tin bronzes (Sn up to 30%), and low-tin alloys (Sn less than 11%). The morphological features of the sculptures suggest one of their possible interpretations as ancestor spirits used in ritual practices. The research findings contribute to the study of Jurchen metallurgical traditions and demonstrate the potential of interdisciplinary, non-destructive analytical methods for reconstructing the technological, social, and cultural aspects of medieval Far Eastern societies. Full article

The tight sandstone reservoir of the Fuyu Oil Layer in the Quantou Formation of the Cretaceous in the Bayan Chagan area displays intricate microscopic pore structures and pronounced heterogeneity, limiting hydrocarbon exploration and development efficiency. Utilizing core CT scanning digital core technology integrated with field emission scanning electron microscopy (FE–SEM) and whole-rock/clay mineral X-ray diffraction (XRD) analysis, this research performs multi-scale quantitative characterization on 15 representative rock samples from the study area, systematically elucidating reservoir pore structure diversity and its formation mechanisms. The study demonstrates that reservoirs in the study area can be categorized into three types: A, B, and C, exhibiting progressively declining reservoir performance. Type A reservoirs are characterized primarily by dissolution-formed large to medium pores, where macropores (radius > 5 μm) account for more than 92% of storage capacity, average coordination numbers reach 0.27~0.45, and connectivity is optimal. Type B reservoirs are influenced by siliceous cementation, featuring developed residual intergranular pores, macropore volume share declining to 88%, and coordination numbers decreasing to 0.11~0.20. Type C reservoirs experience intense compaction and illite cementation modification, where micropores (radius < 1 μm) constitute 5.6% numerically, yet macropore volume share is merely 76%, coordination numbers drop to 0.02–0.03, and connectivity is minimal. Mineralogical analysis reveals that quartz content exhibits a positive correlation with reservoir properties, as its rigid grain framework effectively resists compaction. Illite content rises with increasing burial depth, and plastic illite occupies pores and segment throats, resulting in Type C reservoir permeability reduction to 0.01~0.25 mD. Dissolution intensity (Type A > Type B > Type C) and cementation types (quartz cementation prevailing in Type B, illite cementation prevailing in Type C) represent crucial factors governing reservoir quality differentiation. This research confirms the reliability of digital core technology for tight reservoir classification and assessment, developing a discrimination model founded on “pore structure-mineral composition-diagenesis”. It provides a geological basis for sweet spot prediction and efficient development in the study area. Full article

Selective Laser Sintering (SLS) is an Additive Manufacturing (AM) technology that is receiving considerable attention in the scientific and industrial communities due to its great ability to efficiently produce functional and complex parts. The present work aims to fabricate a real prototype via SLS, such as a hose reel for industrial applications, using polyamide 11 (PA11) as a starting material. Characterization of the PA11 powder properties was first carried out from a thermal and morphological viewpoint to determine the powder’s thermal stability by TGA, the sintering window and degree of crystallinity by DSC, and the microstructure by SEM, PSD, and XRD analyses. The results revealed that PA11 has a 45-micron average particle size, circularity close to 1, and a Hausner ratio of 1.17. Together, these parameters ensure that PA11 powder flows smoothly, packs uniformly, and forms dense and defect-free layers during the SLS process, directly contributing to high part quality, dimensional precision, and stable process performance. The printability of the PA11 was optimized for the realization of 3D-printed parts for industrial applications. Finally, the quality of the printed samples and the mechanical and thermal performance were investigated. Several PA11-based parts were fabricated via SLS, showing a high level of complexity and definition, ideal for industrial applications, as confirmed by the predominantly green areas of the colored maps of X-CT. A complete prototypal case for a hose reel was assembled by using the parts realized, and it was chosen as a technological demonstrator to verify the feasibility of PA11 powder in the production of industrial professional components. Full article

X-ray micro-computed tomography (Micro-CT) is an advanced technique capable of non-destructive detection of internal defects in materials. Fiber-reinforced polymer (FRP) laminates are prone to forming defects such as pores during the manufacturing process, which significantly affect their mechanical properties. In this study, Micro-CT technology was employed to conduct non-destructive testing on carbon fiber (CFRP), glass fiber (GFRP) and carbon/glass hybrid (C/G) laminates. Combined with the U-Net++ deep learning model, precise segmentation and three-dimensional reconstruction of pores were achieved. A systematic quantitative analysis was carried out on the distribution, size, volume and porosity of pores in six specimens with two layup angles (0/90 and ±45). The research results show that the pores in CFRP are mainly dispersed micro-pores and are relatively evenly distributed; the porosity of GFRP is the highest, and large interlaminar pores are prone to forming. The porosity fluctuates sharply in the thickness direction, revealing that the interlaminar interface is a defect-sensitive area. This provides a reliable quantitative basis and theoretical support for optimization and defect assessment. Full article

The aramid honeycomb composite material plays an important role in industry. Defects of this material seriously influence its performance. However, conventional detecting tools such as X-ray or computer tomography (CT) imaging, ultrasonic testing, and visual inspection are not able to meet the requirements of fast, safe, and high resolution at the same time. In this study, we numerically use rapid terahertz time−domain spectroscopy (THz-TDS) to identify defects in the aramid paper composite structure effectively. Simulation results demonstrate that THz-TDS technology enables the non-destructive reflection imaging of layered defects in glass fiber covering and glue layers as supporting components within the composite structure, with a spatial resolution of 0.5 mm and a depth range exceeding 10 mm. During the study, the finite difference time domain (FDTD) simulation with a real pulse waveform is achieved, and the defect position can be recognized by the anomaly in the reflection profile when compared with the waveform reflected by non-defect samples. At the same time, it is found that the defect identification ability is obviously affected by the incident position. The numerical research illustrates that the detectable defect is as thick as 0.1 mm and has a diameter of 1 mm. The results will offer valuable guides to the real application of THz-TDS systems in the detection of a similar structure. Full article

Three-dimensional medical images, such as those obtained from MRI scans, offer a comprehensive view that aids in understanding complex shapes and abnormalities better than 2D images, such as X-ray, mammogram, ultrasound, and 2D CT slices. However, MRI machines are often inaccessible in certain regions due to their high cost, space and infrastructure requirements, a lack of skilled technicians, and safety concerns regarding metal implants. A viable alternative is generating 3D images from 2D scans, which can enhance medical analysis and diagnosis and also offer earlier detection of tumors and other abnormalities. This systematic review is focused on Generative Adversarial Networks (GANs) for 3D medical image analysis over the last three years, due to their dominant role in 3D medical imaging, offering unparalleled flexibility and adaptability for volumetric medical data, as compared to other generative models. GANs offer a promising solution by generating high-quality synthetic medical images, even with limited data, improving disease detection and classification. The existing surveys do not offer an up-to-date overview of the use of GANs in 3D medical imaging. This systematic review focuses on advancements in GAN technology for 3D medical imaging, analyzing studies, particularly from the recent years 2022–2025, and exploring applications, datasets, methods, algorithms, challenges, and outcomes. It affords particular focus to the modern GAN architectures, datasets, and codes that can be used for 3D medical imaging tasks, so readers looking to use GANs in their research could use this review to help them design their study. Based on PRISMA standards, five scientific databases were searched, including IEEE, Scopus, PubMed, Google Scholar, and Science Direct. A total of 1530 papers were retrieved on the basis of the inclusion criteria. The exclusion criteria were then applied, and after screening the title, abstract, and full-text volume, a total of 56 papers were extracted from these, which were then carefully studied. An overview of the various datasets that are used in 3D medical imaging is also presented. This paper concludes with a discussion of possible future work in this area. Full article

Intraoperative radiotherapy (IORT) is a radiation technique that allows for the delivery of a high radiation dose to the target while preserving the surrounding structures, which can be displaced during the surgical procedure. An important limitation of this technique is the lack of real-time image guidance, which is one of the main achievements of modern radiation therapy because it allows for treatment optimization. IORT can be delivered by low-energy X-rays or by accelerated electrons. The present review describes the most relevant clinical applications for IORT and discusses the potential advantages of using artificial intelligence (AI) to overcome some of the current limitations of IORT. In recent decades, IORT has proven to be an effective treatment in several cancer types. In breast cancer, IORT can be used to deliver a single dose of radiation (partial breast irradiation) or as a boost in high-risk patients. In locally advanced rectal cancer, a single dose to the tumor bed can improve local control and prevent pelvic relapse in primary and recurrent tumors. In sarcomas, IORT enables the delivery of high doses, achieving good functional outcomes with low toxicity in tumors located in the retroperitoneum and extremities. In pancreatic cancer, IORT shows promising results in borderline resectable and unresectable cases. Ongoing technological advances are addressing current challenges in imaging and radiation planning, paving the way for personalized, image-guided IORT. Recent innovations such as CT- and MRI-equipped hybrid operating theaters allow for real-time imaging, which could be used for AI-assisted segmentation and planning. Moreover, the implementation of AI in terms of machine learning, deep learning, and radiomics can improve the interpretation of imaging, predict treatment outcomes, and optimize workflow efficiency. Full article

Background and Clinical Significance: Bladder neoplasms often present with coexisting thrombi and hematuria, appearing as complex intraluminal masses on imaging, and posing a key diagnostic challenge in distinguishing neoplastic tissue from thrombus, to prevent harmful overstaging. Case Presentation: An 82-year-old man with recurrent gross hematuria and urinary disturbances was evaluated by ultrasound, which identified a large endoluminal lesion in the anterior bladder wall. The patient subsequently underwent contrast-enhanced CT using a second-generation dual-layer spectral CT system, which utilizes a dual-layer detector to simultaneously acquire high- and low-energy X-ray data. Conventional CT images confirmed a multifocal, bulky hyperdense lesion along the bladder wall, protruding into the lumen and raising suspicion for a heterogeneous mass, though further characterization was not possible. Spectral imaging enabled the reconstruction of additional maps—such as iodine density, effective atomic number (Z-effective), and electron density—which were used to further characterize these findings. The combination of these techniques clearly demonstrated differences in iodine uptake and tissue composition within the parietal lesions, allowing for a reliable differentiation between neoplastic tissue and intraluminal thrombus. Conclusions: The integration of conventional CT imaging with spectral-derived maps generated in post-processing allowed for accurate and reliable tissue differentiation between bladder neoplasm and thrombus. Spectral imaging holds the potential to prevent tumor overstaging, thereby supporting more appropriate clinical management. The dual-layer technology enables the generation of these maps from every acquisition without altering the scan protocol, thereby having minimal impact on the daily clinical workflow. Full article

Leopold Blaschka (1822–1895) and his son Rudolf (1857–1939) created scientifically accurate glass models of marine invertebrates that reshaped natural history education in the 19th century. Their work overcame the limitations of traditional preservation techniques, allowing for detailed and lifelike representations of soft-bodied sea creatures and botanic species. Today, their models are preserved in prestigious collections worldwide. This paper examines not only the historical and artistic significance of the Blaschka models but also presents the findings of recent material analyses, including computed tomography (CT), scanning electron microscopy combined with energy dispersive X-ray analysis (SEM-EDS), visible ultraviolet fluorescence (UVF), and Fourier-transform infrared spectroscopy (FTIR). The multi-analytical approach allowed for the characterization of the chemical composition of the glass and adhesives used, shedding light on the Blaschkas’ unique manufacturing processes and material choices. Data from this study demonstrate how the combination of a multi-analytical approach with knowledge of historical glassmaking practices can provide a solid foundation for both conservation efforts and further academic investigation into these composite objects. The study underscores the models’ value not only as artistic masterpieces but also as technological artifacts, offering insights into 19th-century scientific craftsmanship at the intersection of art and biology. Furthermore, the study presents a conservation intervention based on scientific evidence and a skilfully tailored solution, chosen piece-by-piece, part-by-part of the intricate glass models. Full article

Objective: This study investigated associations between physical activity (PA) during late adolescence and emerging adulthood and bone strength in emerging adulthood by utilizing advanced finite element analysis of computed tomography (CT/FEA) technology beyond the traditional dual-energy X-ray absorptiometry (DXA) method. Methods: This study included 266 participants (152 females) from the Iowa Bone Development Study. PA volume (average acceleration) and intensity (intensity gradient) metrics were calculated from ActiGraph accelerometer data collected at ages 17, 19, 21, and 23 years. Compressive modulus and compressive stiffness of the tibia were estimated at age 23 via CT/FEA of the tibia. Sex-specific linear regression models were used to evaluate associations between PA metrics and bone outcomes, adjusting for age, height, weight, musculoskeletal fitness, and calcium intake. Results: Intensity gradient averaged over 17–23 years of age was positively associated with compressive stiffness at age 23 years in both females and males (p < 0.01). Intensity gradient was positively associated with compressive modulus in females (p < 0.01), but not in males. No significant associations were found between average acceleration and either compressive stiffness or modulus in either sex (p > 0.05). Conclusions: Using a state-of-the-art CT/FEA method, this study suggests that high-intensity PA during late adolescence and emerging adulthood improves bone strength. Full article

Latent heat thermal energy storage (LHTES) based on phase change materials (PCMs) is receiving increasing interest since it offers high energy storage density while enabling the integration of variable renewable energies, hence boosting the transition towards a climate-neutral future. Despite the advantages that PCMs offer in providing a nearly isothermal solid–liquid phase transition, they still face some challenges that limit their deployment in real applications such as low thermal conductivity, phase separation, and supercooling, which affect charging and discharging rates. X-ray computed tomography (XCT) is a non-destructive imaging technique widely used in materials science for both qualitative and quantitative analysis of material microstructures and their evolution. Recent advances in laboratory-XCT instrumentation enabled short acquisition times on the order of tens of seconds which allows the investigation of dynamic processes in situ by time-lapse XCT measurements. These advances open new opportunities for revealing information on the morphology of solid–liquid PCMs. Despite the fact that XCT imaging has significant potential for energy research, its application in the field of PCMs is fairly new. A key enabler of applications of XCT to PCMs is the density difference between solid and liquid PCMs, which was found to be higher than 7% for all investigated PCMs. This enabled solid and liquid phases to be distinguished one from the other and properly quantified over time. The present work reviews the principles of laboratory-based XCT and the recent applications of XCT technology in the characterisation of PCMs, with emphasis on the study of the solid–liquid phase transition and validation of numerical PCM models by addressing the potentialities and challenges of XCT in PCM research. Full article

Beyond its renowned gemological value, diamond serves as a vital economic mineral and a unique messenger from Earth’s deep interior, preserving invaluable geological information. Since the Mengyin region is the source of China’s greatest diamond deposits, research on the diamonds there not only adds to our understanding of their origins but also offers an essential glimpse into the development of the North China Craton’s mantle lithosphere. In this article, 50 diamond samples from Mengyin were investigated using gemological microscopy, Fourier-transform infrared (FTIR) spectroscopy, Raman spectroscopy, DiamondView™, and X-ray micro-computed tomography (CT) scanning technologies. The types of Mengyin diamonds are mainly Type IaAB, Type IaB, and Type IIa, and the impurity elements are N and H. Inclusions in diamonds serve as direct indicators of mantle-derived components, providing crucial constraints on the pressure–temperature (P–T) conditions during their crystallization. Mengyin diamonds have both eclogite-type and peridotite-type inclusions. It formed at depths ranging from 147 to 176 km, which corresponds to source pressures of approximately 4.45–5.35 GPa, as determined by the Raman shifts of olivine inclusions. The discovery of coesite provides key mineralogical evidence for subduction of an ancient oceanic plate in the source region. The surface morphology of diamonds varies when they are reabsorbed by melts from the mantle, reflecting distinctive features that record subsequent geological events. Distinctive surface features observed on Mengyin diamonds include fusion pits, tile-like etch patterns, and growth steps. Specifically, regular flat-bottomed negative trigons are mainly formed during diamond resorption in kimberlite melts with a low CO₂ (X_CO2 < ~0.5) and high H₂O content. The samples exhibit varying fluorescence under DiamondView™, displaying blue, green, and a combination of blue and green colors. This diversity indicates that the diamonds have undergone a complex process of non-uniform growth. The nitrogen content of the melt composition also varies significantly throughout the different growth stages. The N3 center is responsible for the blue fluorescence, suggesting that it originated in a long-term, hot, high-nitrogen craton, and the varied ring band structure reveals localized, episodic environmental variations. Radiation and medium-temperature annealing produce H3 centers, which depict stagnation throughout the ascent of kimberlite magma and are responsible for the green fluorescence. Full article

MRI is a non-invasive imaging technique employed today in modern diagnostic medicine due to the fact it is capable of generating tissue architecture and function information with high image resolution without the use of ionizing radiation, unlike x-ray or CT scans. The advantages of MRI discussed in this review include better soft tissue contrast, the opportunity to perform imaging in different planes, and the ability to detect small changes in tissues, which helps to use MRI in many specialties, including cancer diagnosis and staging, as well as neurological and cardiovascular diseases. More particularly, this review aims to assess the contribution of MRI to the detection of liver cancer, especially HCC and ICC—the most frequent and aggressive types of pathology. Because of its high-resolution, MRI provides clear visualization of the small hepatic lesion and vascular mapping, which is crucial for early diagnosis and staging. It also reveals higher sensitivity and specificity than ultrasound and CT in identifying liver cancer dimensions and relations with system vasculature and a safer technique for patients who need many follow-up images. This is in addition to newer techniques that have been developed from MRI, which include the DWI, DCE-MRI, and MRE, all of which yield functional information concerning the perfusion of the tumor and the stiffness of the tissue, respectively, thus improving the diagnosis. Moreover, the application of artificial intelligence to MRI is improving lesion identification and cancer assessment, as well as patient outcome prediction, while relieving the burden of radiologists. Suggested improvements for future work include the combination of MRI with other diagnostic approaches, including circulating cell analysis and molecular imaging in managing liver cancer. Still, there is a limitation in MRI’s access globally, because scanners are expensive and unavailable in some parts of the world. Technological improvements and greater availability will extend MRI more as a valuable modality in the treatment of liver malignancies, more so for diagnosis and staging. Full article

Non-destructive testing (NDT) methods are critical for evaluating the structural integrity of and detecting defects in composite materials across industries such as aerospace and renewable energy. This review examines the recent trends and successful implementations of NDT approaches for composite materials, focusing on articles published between 2015 and 2025. A systematic literature review identified 120 relevant articles, highlighting techniques such as ultrasonic testing (UT), acoustic emission testing (AET), thermography (TR), radiographic testing (RT), eddy current testing (ECT), infrared thermography (IRT), X-ray computed tomography (XCT), and digital radiography testing (DRT). These methods effectively detect defects such as debonding, delamination, and voids in fiber-reinforced polymer (FRP) composites. The selection of NDT approaches depends on the material properties, defect types, and testing conditions. Although each technique has advantages and limitations, combining multiple NDT methods enhances the quality assessment of composite materials. This review provides insights into the capabilities and limitations of various NDT techniques and suggests future research directions for combining NDT methods to improve quality control in composite material manufacturing. Future trends include adopting multimodal NDT systems, integrating digital twin and Industry 4.0 technologies, utilizing embedded and wireless structural health monitoring, and applying artificial intelligence for automated defect interpretation. These advancements are promising for transforming NDT into an intelligent, predictive, and integrated quality assurance system. Full article

Composite insulators are deployed globally for outdoor insulation owing to their light weight, excellent pollution resistance, good mechanical strength, ease of installation, and low maintenance costs. The core rod in composite long-rod insulators plays a critical role in both mechanical load-bearing and internal insulation for overhead transmission lines, and its performance directly affects the overall operational condition of the insulator. However, it remains susceptible to failures induced by complex actions of mechanical, electrical, thermal, and environmental stresses. This paper systematically reviews the major failure modes of core rods, including mechanical failures (normal fracture, brittle fracture, and decay-like fracture) and electrical failures (flashunder and abnormal heating of the core rod). Through analysis of extensive field data and research findings, key failure mechanisms are identified. Preventive strategies encompassing material modification (such as superhydrophobic coatings, self-diagnostic materials, and self-healing epoxy resin), structural optimization (like the optimization of grading rings), and advanced inspection methods (such as IRT detection, Terahertz (THz) detection, X-ray computed tomography (XCT)) are proposed. Furthermore, the limitations of current technologies are discussed, emphasizing the need for in-depth studies on deterioration mechanisms, materials innovation, and defect detection technologies to enhance the long-term reliability of composite insulators in transmission networks. Full article