Search Results (87)

Historic structures that possess cultural heritage value are important documents that convey the architectural understanding, material technology, and construction techniques of past civilizations to the present day. However, these structures are exposed over time to physical, chemical, and mechanical deterioration due to environmental effects, climatic conditions, the natural aging processes of materials, and human interventions. The conservation and faithful restoration of historic structures necessitate the scientific determination of the properties of original building materials. In this study, we aimed to determine the physical, chemical, mineralogical, thermal, and mechanical properties of the original building materials used in the Old Armenian Church located in the city of Çanakkale. In order to reveal the chemical and mineralogical compositions of the samples, XRD, SEM, Raman, and FTIR analyses were applied. The thermal behaviors of the materials were examined through TGA. To determine the physical properties, tests for unit volume weight, specific gravity, compactness, porosity, and water absorption capacity were carried out. For the determination of mechanical properties, compressive strength tests—as well as non-destructive testing methods such as the Schmidt hammer and UPV measurements—were employed. The analysis results indicate that the materials used in the structure have a carbonate-based mineralogical composition and that calcite-bonded systems are dominant. While the physical and mechanical data reveal that the materials possess a compact internal structure, they also indicate that microcracks and weathering processes may be effective in certain areas. These findings emphasize the importance of using lime-based mortars and stones compatible with the original materials in restoration works. Full article

Glass artworks represent a significant component of cultural heritage, yet their surfaces are highly vulnerable to physicochemical weathering resulting from composition-dependent interactions with environmental factors. Understanding the complex and nonlinear relationships between glass composition and deterioration remains challenging using conventional, often invasive, analytical techniques. To address this issue, this study proposes an interpretable and non-destructive computational framework to analyze weathering patterns in historical glass based on oxide composition data. The framework combines statistical hypothesis testing (Chi-squared analysis), metric-based machine learning (Prototypical Networks), probabilistic modeling (Gaussian Mixture Models), multivariate statistical analysis (orthogonal partial least squares discriminant analysis), and information-theoretic methods (mutual information analysis) to identify key compositional features and inter-elemental relationships associated with surface degradation. The results show that lead-barium glass exhibits a higher susceptibility to weathering compared with high-potassium glass, with PbO, BaO, and SiO₂ identified as the most discriminative components. The Prototypical Network achieved 100% accuracy on most specific data partitions within the analyzed dataset, demonstrating its effectiveness in small-sample compositional classification. Meanwhile, mutual information network analysis revealed the complex interrelationships among chemical components involved in surface weathering behavior. These findings indicate that interpretable machine learning and statistical modeling can provide meaningful insights into composition-dependent patterns and support reproducible analysis for the sustainable conservation of cultural heritage glass. Full article

Background: This study deeply explores the influence of different dextrose equivalents (DE) values on room-temperature phosphorescence (RTP) properties of maltodextrin (MD) and its luminescence mechanism. The potential applications of MD tablets in non-destructive detection for afterglow visualizing are also explored. Methods: MD tablets with different DE values were prepared to investigate their RTP properties and afterglow effects. MD tablets were validated for afterglow signals and phosphorescence lifetimes under varying environmental conditions. Additionally, the unique afterglow effect of MD was used to detect the uniformity of tablets. Theoretical calculations of MD monomers and dimers were performed using time-dependent density functional theory. Results: The results demonstrated that MD with different DE values exhibited RTP properties, with phosphorescence lifetimes from 186.91 to 618.85 ms. The afterglow signals and phosphorescence lifetimes of MD tablets were influenced by multiple environmental conditions, i.e., relative humidity, temperature, oxygen, ultraviolet light, etc. Based on the afterglow effect of the MD, it is possible to non-destructively detect the uniform tablet. MD is an RTP material regulated by its DE value. Its phosphorescence mechanism is governed by a clustering-triggered emission mechanism, which is dominated by the rich hydrogen bond network. The material’s stimuli-responsive properties and pronounced afterglow effect make it a potential application for non-destructive detection. Conclusions: This study not only investigates the stimulus-responsive behavior of MD but also discovers a common, safe, and edible stimulus-responsive RTP material. These findings provide a new method for non-destructive detection of drugs and reducing the potential pharmacological risks during production, storage, and transportation. Full article

Turkey, located on one of the world’s most active fault lines, frequently experiences major earthquakes. The 2023 Kahramanmaraş earthquakes (Mw 7.6 and 7.7) caused significant destruction and housing shortages. Post-disaster shelters are often provided using containers, which require flat and solid ground. This typically involves pouring concrete foundations, but high demand for materials and labor hinders rapid installation. This study investigates screw piles as an alternative foundation system for container settlements. Screw piles can eliminate the need for concrete, offering a faster, cost-effective, and environmentally friendly solution. Finite element analyses using Abaqus were conducted to assess the structural behavior of container foundations with screw piles under real earthquake records. Additionally, a decision-making analysis based on the Analytic Hierarchy Process compares screw piles and concrete foundations in terms of cost, time, sustainability, and safety. Results show that screw piles reduce structural responses and are a more feasible post-disaster foundation solution. Full article

Estuaries are dynamic environments that influence the transport of metals and nutrients from land to sea, with suspended particulate matter (SPM) serving as a key vehicle for them. Laser-Induced Breakdown Spectroscopy (LIBS) offers a rapid, versatile, and non-destructive approach for multi-element analysis of SPM, allowing their direct measurement on collected filters without complex sample preparation. In this study, LIBS was applied to evaluate the spatio-temporal variability of major and trace elements (Si, Fe, Al, Ti, Na, Li, K, Rb, Ca, and Mg) along the Pacoti River estuary, Brazil, during rainy and dry seasons. Elemental patterns generally reflected the salinity gradient and tidal dynamics, highlighting element-specific behaviors with most elements showing inverse correlations with salinity, while Ca and Mg displayed positive correlations. These findings confirm the potential of LIBS as a powerful tool for environmental monitoring, providing rapid, high-throughput characterization of SPM and enabling an improved understanding of biogeochemical processes in estuarine systems. Full article

Steel wire ropes are key load-bearing components in systems such as mine hoisting, bridge cableways, elevators, and cranes, and frictional wear is among the earliest occurring and most easily accumulated form of damage. Under actual working conditions, micro-relative sliding occurs both along the internal wires of the rope and at the contact surfaces with sheaves and ropes, leading to frictional wear, crack propagation, and fatigue failure. Frictional wear, a complex phenomenon influenced by structural layout, contact load, vibration conditions, lubrication, and environmental corrosion, critically determines the service life and load-bearing capacity of steel wire ropes. Recent experimental and numerical studies have significantly clarified the fundamental mechanisms and patterns of internal and external frictional wear in steel wire ropes, offering theoretical support for the distribution of wear, fatigue evolution, and fracture behavior. Meanwhile, non-destructive testing techniques have emerged as a vital tool for the real-time monitoring of wear conditions in steel wire ropes. This review summarizes the research progress on the generation, characteristics, effects, and protection of frictional wear in steel wire ropes, and proposes future directions for tribology and service safety research of steel wire ropes. Full article

This study characterizes the chemical defense system of the invasive longhorn beetle Aromia bungii, a destructive pest of Prunus trees, addressing the limited understanding of chemical defensive mechanisms in Cerambycidae. High-speed cameras, environmental scanning electron microscopy (ESEM), dissection, and micro-CT imaging were used to investigate defensive behavior, and the structure of the defense system, in this beetle. Both sexes of A. bungii possess a pair of triangular, sac-like defensive glands symmetrically located in the metathorax, attached to the metasternum. Upon mechanical stimulation, white liquid defensive substances are rapidly ejected through a pair of slit-shaped openings (~200 µm) at the metasternum corners, without gland eversion, reaching over 50 cm. The average weight of substances ejected in first sprays was 7.95 ± 0.79 mg for females and 8.62 ± 2.13 mg for males (mean ± se), with no significant difference between sexes. However, the weight in second sprays after 10 days was significantly lower, at 2.93 ± 0.54 mg for females and 2.22 ± 0.40 mg for males (mean ± se), suggesting that the beetles cannot re-synthesize the substances soon after spray. The weight of ejected substances had no correlation with beetle body weight. Our findings represent the first detailed morphological and functional description of a chemical defense system in Cerambycidae, revealing a specialized metasternal gland and spray mechanism. The substantial but likely non-renewable defensive substances reflect an adaptive trade-off in energy allocation between reproduction and defense in this species that exhibits high fecundity but a short lifespan at the adult stage. Full article

This study investigated the effects of pH (3, 5, 7, 9, 11) on the structure–activity relationship and stability mechanism of Pickering emulsions stabilized by the gorgon euryale starch–quinoa protein complex. Analyses were performed using reverse compression test, rheology, thermal stability assessment, atomic force microscopy (AFM), and low-field nuclear magnetic resonance (LF-NMR) measurements. Reverse compression test showed that the emulsion at pH 3 exhibited the highest hardness and consistency, but the weakest cohesiveness. Rheological measurements revealed that all emulsions displayed shear-thinning behavior, the emulsion at pH 3 had the highest shear stress and apparent viscosity, while that at pH 11 showed the lowest viscosity due to the destruction of macromolecular structures. Thermal stability assessment indicated that the emulsion at pH 3 did not undergo significant stratification even at 60 °C, whereas the stability of emulsions decreased between pH 5–9. Microscopic analyses (optical microscopy, AFM, and LF-NMR) further confirmed that the emulsion at pH 3 had fine, uniform droplets, strong water-binding capacity, and an interfacial film with a “dense protrusion” structure. This study provides a basis for the environmental adaptability design of functional emulsions and contributes to the high-value utilization of gorgon euryale and quinoa resources. Full article

Resistance against water penetration is one of the key indicators of concrete durability in humid and pressurized environments. An intelligent model based on the XGBoost machine-learning algorithm was developed to predict the water penetration depth, using 1512 independent experimental measurements. The influential variables included water pressure, pressure duration, thermal cycles, fiber content, curing, and compressive strength. The investigated concrete specimens and field-tested structures in this study were exposed to arid and hot climatic conditions, and the proposed model was developed within this environmental context. To accurately simulate the water transport behavior, a cylindrical-chamber test was employed, enabling non-destructive and in-situ evaluation of structures. Correlation analysis revealed that compressive strength had the strongest negative influence (r = −0.598), while free curing exhibited the strongest positive influence (r = +0.654) on penetration depth. After hyperparameter optimization, the XGBoost model achieved the best performance (R² = 0.956, RMSE = 1.08 mm, MAE = 0.81 mm). Feature importance analysis indicated that penetration volume, pressure, and curing were the most significant predictors. According to the partial dependence analysis, both pressure and duration exhibited an approximately linear increase in penetration depth, while a W/C ratio below 0.45 and curing markedly reduced permeability. Microstructural interpretation using MIP, XRD, and SEM tests supported the physical interpretation of the trends identified by the machine-learning model. The results demonstrate that machine-learning-models can serve as fast and accurate tools for assessing durability and predicting permeability under severe environmental conditions. Finally, the permeability of several real structures was evaluated using the machine-learning approach, showing excellent prediction accuracy. Full article

In recent years, awareness of environmental issues has grown significantly. This awareness is evident in the increase in academic research on this topic, social initiatives that focus on environmental issues, and programs promoting environmental literacy. At the same time, there is growing recognition of the accumulating environmental damage caused by individuals’ choices and habits and the threat this poses to ecosystems and sustainability. Numerous studies have explored various facets of environmental literacy to promote pro-environmental behavior, which is essential for tackling the environmental challenges of the 21st century. Over the past few decades, research in the social sciences has investigated the influence of war on crime and delinquency rates. Additionally, studies have measured the impacts of war, terrorism, and stress on mental health and social relationships. Ecological research has also examined the relationship between war and environmental degradation, highlighting the impact on ecosystems, infrastructure destruction, and the long-term environmental consequences. To the best of our knowledge, however, no research has examined how stress and war influence individuals’ sense of environmental responsibility. The aim of this qualitative research was to examine the influence of stress and war on both environmentally engaged individuals and those indifferent to the environment, focusing on their sense of environmental responsibility and its practical expressions. Twenty-four participants were categorized into two groups: environmentally engaged and environmentally indifferent. The findings indicate that the commitment of environmentally engaged individuals to environmental protection decreased during periods of stress and war. This decline can be attributed to more immediate concerns for survival. The participants reported that this change was temporary; as calm returned, their level of commitment reverted to its previous state. Among the environmentally indifferent, no change occurred in their level of commitment to environmental protection, which was consistently low before, during, and after situations of stress and war. Additional findings indicate that the social environment plays a crucial role in fostering environmental responsibility and protection. A supportive social environment has a positive influence on individuals, while indifference or opposition can harm their sense of environmental responsibility. Our research findings also suggest that both environmentally oriented and environmentally indifferent individuals primarily focus on recycling and waste separation when they refer to pro-environmental behavior. Full article

Green organic coatings are developed to be deposited on and protect metallic cultural heritage artefacts from environmental degradation. This research work is carried out through a comparative study of under-development green organic and commercial coatings for indoor and outdoor applications against an artificial ageing environment. Non-destructive techniques, such as Colorimetry, Glossimetry, Eddy-current thickness measurements, and SEM-EDS investigation, are employed to assess the studied bronze substrate-coating mock-up systems’ behavior. The results showed some correlations among the studied parameters, such as the thickness–colour (namely ΔΕ parameter) relationship, while comparative conclusions provide consultant suggestions for cultural heritage conservation applications. Full article

Ground-penetrating radar (GPR) is widely used for thickness or compaction degree detection of asphalt pavement layers, where the dielectric properties of asphalt mixtures serve as a key parameter influencing detection accuracy. These properties are closely related to the composition of the mixture and are susceptible to environmental factors such as water or ice. To clarify the influence of various factors on the dielectric behavior of asphalt mixtures, an experimental study was conducted under controlled environmental conditions. Asphalt mixture specimens with different air void contents (5.49~10.29%) were prepared, and variables such as void fraction, moisture, and ice presence were systematically controlled. Air-coupled GPR was employed to measure the specimens, and the relative permittivity was calculated using both the reflection coefficient method (RCM) and the thickness inversion algorithm (TIA). Discrepancies between the two methods were compared and analyzed. Results indicate that the RCM is significantly influenced by surface water or ice and is only suitable for dielectric characterization under dry pavement conditions. In contrast, the TIA yields more reliable results across varying surface environments. A unified model (the optimized shape factor u = −4.5 and interaction coefficient v = 5.1) was established to describe the relationship between the dielectric properties of asphalt mixtures and their volumetric parameters (bulk specific density, air void content, voids in mineral aggregate, and voids filled with asphalt). This study enables quantitative analysis of the effects of water, ice, and mixture composition on the dielectric properties of asphalt mixtures, providing a scientific basis for non-destructive and accurate GPR-based evaluation of asphalt pavements. Full article

This work presents the non-destructive assessment of polymeric composites based on synthetic matrices low-density polyethylene (LDPE) and polystyrene (PS) enhanced with chitosan (CS) biopolymer for use in active packaging systems for moisture control. Composites were prepared by incorporating CS at different contents (1, 3 and 5 phr) into LDPE and PS matrices. To evaluate the structural and thermal alterations induced by biopolymer loading, the materials were characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), and differential scanning calorimetry (DSC). The composites’ water-regulating properties—specifically, moisture absorption, retention, diffusion, and water vapor transmission rate—were quantitively tracked. Furthermore, the mechanical integrity of both dried and water-exposed systems was assessed via Shore D hardness testing. The results reveal a direct correlation between CS concentrations and enhanced hydrophilic behavior and water absorption, primarily attributed to the polar hydroxyl and amine groups within its molecular structure. The composites maintained adequate mechanical strength even after water exposure, confirming their structural stability for practical applications. This study demonstrates that the incorporation of CS into non-polar synthetic matrices significantly improves water affinity without requiring chemical compatibilizers, representing a cost-effective route to develop responsive packaging. The promise of these composites as responsive materials for real-time environmental interaction is highlighted by the successful non-destructive monitoring of their performance. This research establishes the feasibility and efficacy of non-destructive monitoring techniques in developing active packaging technologies, accelerating the progress of polymer-based systems with integrated and tunable moisture regulation capabilities. Full article

This study presents an advanced signal analysis model for internal defect identification in bridge decks using impact echo field testing data designed to mitigate signal noise and the variability encountered during real-world inspections. Field tests were conducted on a concrete bridge deck utilizing an automated inspection system, systematically capturing impact-echo signals across multiple scanning paths. The large volume of field-acquired data poses significant challenges, particularly in identifying defects and isolating clean signals and suppressing noise under variable environmental conditions. To enhance the accuracy of defect detection, a deep learning framework was designed to refine critical signal parameters, such as signal duration and the starting point in relation to the zero-crossing. A convolutional neural network (CNN)-based classification model was developed to categorize signals into delamination, non-delamination, and insignificant classes. Through systematic parameter tuning, optimal values of 1 ms signal duration and 0.1 ms starting time were identified, resulting in a classification accuracy of 88.8%. Laboratory test results were used to validate the signal behavior trends observed during the parameter optimization process. Comparison of defect maps generated before and after applying the CNN-optimized signal parameters revealed significant enhancements in detection accuracy. The findings highlight the effectiveness of integrating advanced signal analysis and deep learning techniques with impact-echo testing, offering a robust non-destructive evaluation approach for large-scaled infrastructures such as bridge deck condition assessment. Full article

This paper presents a comprehensive analysis of the thermal stability and decomposition mechanisms of IPN hydrogels based on polyvinyl alcohol (PVA) and a copolymer network of poly(ethylene glycol) diacrylate–poly(ethylene glycol) methacrylate (PEGDA–PEGMA). Using thermogravimetric analysis (TGA/DTG) and multi-approach kinetic analysis (Friedman and Ozawa–Flynn–Wall isoconversion methods, nonparametric kinetics, Shestaka-Berggren model), the influence of composition on the processes of dehydration, thermal destruction, and the distribution of activation energy by degrees of conversion was investigated. The constructed three-dimensional kinetic “landscapes” made it possible to identify characteristic features of the behavior of various samples, including differences in the rate and mechanisms of destruction. It was found that an increase in the content of PVA enhances moisture binding and shifts the T_max of dehydration to higher temperatures, while an increase in the concentration of PEGDA forms a denser network that limits moisture retention and accelerates thermal decomposition. Calculation of diffusion coefficients using the Fick model showed a decrease in D with an increase in network density, which reflects an increase in resistance to moisture mass transfer. The combination of the data obtained demonstrates the multistage nature of thermal destruction and allows for the targeted selection of hydrogel compositions for biomedical, environmental, and materials science applications, including drug delivery systems, sorbents and heat-resistant coatings. Full article