Materials Science Research Articles

Degradation induced superlubricity on the rough surface of black phosphorus composite

A rough surface composed of asperities was considered as the obstacle for achieving superlubricity in traditional friction theory. Here, microscale superlubricity with the friction coefficient of 0.0086 was observed on a relatively rougher soft surface of black phosphorus (BP) composite due to the degradation of BP with oxygen and moisture via the atomic force microscopy (AFM) experiment equipped with diamond-like carbon (DLC) microsphere probe. Comparative analyses corroborated that the produced phosphorus oxides (oBP) with abundant P=O and P−OH bonds and the local graphitized amorphous carbon film at the sliding interface decreased the possibility of direct contact between original rough peaks and provided an ultra-low shear strength for achieving superlubricity. Furthermore, a certain nanoscale roughness structure on the composite surface facilitated a more reliable superlubricity state, which supplied the larger contact area and locking capillary force to hold and retain the lubricating liquid film formed by the water absorption of oBP. These findings provided fundamental insights into the nature of tribological mechanisms and suggested a new method to achieve ultra-low friction of polymer composite materials in engineering.

Chemically recyclable rosin-based polymers

The pursuit of next-generation sustainable polymers with chemical recyclability and resource renewability has become a priority in materials science. Rosin, a widely available renewable natural biomass, holds promise in this regard. In this study, dehydroabietic acid was incorporated into a cyclooctene monomer structure as pendant groups. This tailored monomer with low ring strain possesses the ability to efficiently undergo ring-opening metathesis polymerization (ROMP), resulting in the synthesis of rosin-based unsaturated polymers with a fully hydrocarbon backbone. The molecular weight of these polymers, ranging from 50 kDa to 160 kDa, can be easily modulated by varying the monomer-to-catalyst feeding ratio. Remarkably, these amorphous polymers exhibit exceptional thermostability, with a decomposition temperature exceeding 400 °C. This type of polymer exhibits excellent acid and alkali resistance within a pH range of 3 to 11. Upon exposure to Grubbs II catalyst under mild conditions, these polymers undergo depolymerization back to the native monomer in a highly efficient manner, achieving a remarkable recovery ratio of approximately 95 %. It is evident that this innovative approach is not only relevant for the development of rosin-based polymers but also holds promise for informing the design of other renewable polymers with superior thermostability and enhanced chemical recyclability.

Gold-catalyzed Reactions of Substituted 1,5-diynes: Recent Advances and their Chemistry

Abstract: Diynes are identified as exceptionally potent and superior substrates in gold-catalyzed organic transformations. Gold (I) and gold (III) complexes exhibit unique activity towards diynes, encouraging the nucleophilic addition of different functional groups both inter and intra- molecularly. In this review, particularly, we focused on recent advances in gold-catalyzed reactions of 1,5-diynes along with their mechanistic aspects. These reactions are interesting for constructing molecular complexity, medicinal chemistry, and material science.

Synthesis of Methyl N-phenylcarbamate Derivatives by Xphos Pd G2 Catalyzed Intermolecular Amidation Reaction

Abstract: The utilization of palladium catalysts in cross-coupling reactions has emerged as a highly promising method for the facile formation of aryl C-N bonds, operating under mild conditions. In this study, we present an efficient approach for the synthesis of methyl N-phenyl carbamate derivatives through the intermolecular amidation of aryl chlorides, catalyzed by Xphos Pd G2. The developed protocol has demonstrated remarkable efficacy, offering several advantages. Notably, the intermolecular amidation reaction exhibited good chemoselectivity, allowing for the precise targeting of desired C-N bond formations while maintaining the integrity of other functional groups. Additionally, this methodology showcases exceptional functional group compatibility, accommodating a diverse array of moieties, including sensitive groups that are traditionally challenging to handle. The Xphos Pd G2 catalyst has proven to be instrumental in orchestrating this transformation, exhibiting high catalytic activity and selectivity. Furthermore, this protocol stands out for its operational simplicity, making it a practical choice for synthetic chemists seeking a straightforward and reliable route to access methyl N-phenyl carbamate derivatives. Overall, this study not only expands the synthetic toolbox for C-N bond formations, but also underscores the significance of palladium-catalyzed methodologies in modern organic synthesis. The reported findings hold substantial promise for applications in medicinal chemistry and material science, where the facile construction of aryl C-N bonds is of paramount importance.

Data analysis of non-linear radiative electro-periodic MHD flow past a stretching sheet with activation energy impact

Electro-periodic Magneto-hydrodynamics (EPMHD), activation energy, and non-linear radiation are pivotal elements in engineering and industry also contribute to advancements in fields like heat transfer, materials science, and chemical engineering. Through similarity transformation, governing partial differential equations simplify into ordinary differential equations. Precise computational solutions are derived using the Nachtsheim-Swigert shooting iteration method (NSSIM) and the reliable 6th-order Runge-Kutta integration algorithm (RKIA). The profiles of velocities, temperatures, concentrations, skin friction, heat and mass transfer rate are presented by graphically. The novel aspect of this research is that thermal performance is enhanced by non-linear radiation by around 2.28%, whereas linear radiation only produces a 0.28% improvement in thermal performance. Also the mass transfer rate experiences a decrease of about 25.76% with increasing chemical reactions in the presence of activation energy and a more substantial 62.22% reduction in its absence, notably showing a comparatively milder decline of 36.46% in the presence of activation energy than in its absence. Furthermore, this study yields three novel linear regression equations, skillfully derived from the numerical and graphical results. This research have practical applications in understanding and optimizing processes involving fluid dynamics, such as the behavior of certain materials or substances subjected to stretching or deformation.

Analysis of causes and factors of the spread of takfirism in Kazakhstan

The purpose of this research is to analyse the emergence of takfirism, its spread and its evolution in contemporary Kazakh society. The methodological foundation of the study was provided by general theoretical methods of scientific cognition, and various methods of collecting and systematising information. Among the general scientific methods are the method of theoretical analysis; the historical method of comparing individual religious movements of different periods in Kazakhstan, and the specific scientific and philosophical-religious methods of research. The results have suggested that unfounded takfirism poses a threat to the sustainability of diverse communities in Kazakhstan. The religious, ideological and theological preconditions for takfirism in Kazakhstan were analysed. Noted the diversity of approaches by Muslim scholars to understanding and interpreting the ayats of the Qur'an. Presented aspects of distortion in interpreting the essence of Shariah texts. Noted that the influence of political and social factors is significant. Focuses on some of the socio- psychological aspects of the development of radical attitudes among young people. The qualities inherent in young people that enable them to resist external non-ideological attacks are identified. Illiteracy, poor quality of education and the low culture of some people in Muslim countries are among the key elements. It was noted that the main factor in takfirism in Kazakhstan is the influence of the Salafi-Wahhabi movement. The practical significance of the study is that its content is of interest in developing the worldview of contemporary young people in the Republic of Kazakhstan. The results can be used as a teaching and practical material for students and researchers on contemporary history and religion in Kazakhstan.

Stimulus-responsive room-temperature phosphorescence with tunable color for time-resolved advanced dynamic anti-counterfeiting

Multi-stimuli responsive multicolored room-temperature phosphorescent (RTP) carbon quantum dots (CQDs) have recently attracted considerable attention, owing to their potential applications in advanced dynamic anti-counterfeiting. The design and development of carbon dots that exhibit both stimulus response characteristics and multicolor RTP emission remains a significant challenge in the field. In this work, we present a novel approach to control the dynamic phosphorescence color and stimulus response properties of CQDs coated on paper by fine-tuning the surface functional groups of the CQDs. Specifically, histidine and 2,4,6-triaminopyrimidine was separately used to prepare N, O co-doped CQDs (NOCQDs) and N-doped CQDs (NCQDs), respectively. These CQDs were further coated on filter paper substrates to achieve water and heating cascade stimulus–response RTP. These stimuli-responsive properties of NOCQDs can be modulated by deprotonating their surface oxygen-containing groups. Eventually, we achieved time-resolved multicolor dynamic anti-counterfeiting by exploiting the stimuli-response properties and lifetimes differences between NOCQDs and NCQDs, realizing the 5D information encryption in all five stimulus-, pattern-, time-, and color-dependent codes. These findings highlight the potential of NOCQDs as advanced anti-counterfeiting materials and lay a foundation for further exploration into the synthesis and properties of CQDs with tunable stimuli-response features and RTP emission.

The Influence of Shakarim Kudaiberdiev’s Work on the Economic, Cultural, and Spiritual Development of Kazakhstan in the Late 19th Century and Early 20th Century

The significance and relevance of the issues are predetermined by the fact, that, by the time of Shakarim Kudaiberdiev’s activity, the political and social situation of Kazakhstan in the early 20th century was on the verge of collapse. The main factor that influenced this situation was the policy of spreading illiteracy, people alienated from religion language, and writing. From the late 19th and early 20th centuries, Kazakhstan suffered from the colonial policies of the Russian Empire. Currently Kudaiberdiev writes a work “Catechism of Muslims”. The main purpose of the study is to analyze the consequences of the creative work on the economic and spiritual and cultural development of Kazakhstan. During the analysis, several scientific sources and materials were analyzed, and the following scientific methods were used: structural-functional and dialectical methods, the method of synthesis, logical and comparative analysis, and the method of generalization. During the research, it was proved that in the works of Shakarim Kudaiberdiev the calls to fight against the policy of tsarist Russia and to revive their language, customs, religion, and history were present. The main result of this research is proof that the works of Shakarim Kudaiberdiev had a tremendous impact on the social status, culture, religion, and language of the Kazakh people. His works acted in opposition to Russian policy and encouraged people who were tired of colonial oppression. The research on this issue is actively developed, therefore this work is of practical value for the definition of the role of Shakarim’s creativity during the economic, cultural, social, and political development of Kazakhstan at the end of 19 – the beginning of 20 century.

Decision tree-based approach to extrapolate life cycle inventory data of manufacturing processes

Life cycle assessment (LCA) plays a crucial role in green manufacturing to uncover the critical aspects for alleviating the environmental burdens due to manufacturing processes. However, the scarcity of life cycle inventory (LCI) data for the manufacturing processes is a considerable challenge. This paper proposes a novel approach to extrapolate LCI data of manufacturing processes. Taking advantage of LCI data in the Ecoinvent datasets, decision tree-based supervised machine learning models, namely decision tree, random forest, gradient boosting, and adaptive boosting, have been developed to extrapolate the data of GHG emissions, i.e., carbon dioxide, nitrous oxide, methane, and water vapor. Initially, a correlation analysis was conducted to derive the most influential factors on GHG quantities resulting from manufacturing activities. First, the collected data have been preprocessed and split into train and test sets (70% and 30%, respectively). Second, a five-fold cross-validation method was applied to tune the hyperparameters of the models. Then, the models were re-trained using the best hyperparameters and evaluated using the test set. The results reveal that the Gradient Boosting model has a superior predictive performance for extrapolating the GHG emission data, with average coefficients of determination (R2) on the test set <0.95. Moreover, the model predictions involve relatively low values of the average root mean squared error and an average mean percentage of error on the test set. The correlation and feature importance analyses emphasized that the workpiece material and manufacturing technology have a considerable effect on natural resource consumption, i.e., energy, material, and water inflows into the process. Meanwhile, energy consumption, water usage, and raw aluminum depletion were the most influential factors in GHG emissions. Eventually, a case study to extrapolate the inflows and the outflows for new manufacturing activities has been conducted using the validated models. The proposed GraBoost model provides a computational supplementary approach to estimate and extrapolate the GHG emissions for different manufacturing processes when LCI data are incomplete or don't exist within LCI databases.

An integrated computation framework for predicting mechanical performance of single-phase alloys manufactured using laser powder bed fusion: A case study of CoCrFeMnNi high-entropy alloy

Establishing a process-structure-property (PSP) relationship is crucial for understanding and optimizing the mechanical properties of components via laser powder bed fusion (L-PBF) additive manufacturing (AM). However, the parameters pertinent to the PSP relationship are encapsulated in a “black box” with a high dimension, resulting in relying on trial-and-error approaches to elucidate hidden associations becoming impracticable, while the acquisition of microscopic data proves financially burdensome. Thus this paper presents an integrated computation framework based on machine learning (ML) for predicting the tensile yield strengths and post-yield hardening rates of single-phase alloys fabricated through L-PBF, for efficient process optimization purposes. Research herein focuses on single-phase alloys to be built via L-PBF, taking CoCrFeMnNi high-entropy alloy as a study case, and provide an efficient integrated computation solution. The methodology proposed in this paper generates as-built microstructures associated with the varying L-PBF process parameters via cellular automata (CA). Subsequently, the mechanical responses of these microstructures are estimated by employing crystal plasticity finite element (CPFE) simulations. In addition, the approach raised in the paper leverages particle-level microstructure descriptors instead of average feature descriptors for the entire representative volume element (RVE) structure in an ML framework to predict the characteristics of the newly randomly growing grains. This research demonstrate the practicality and instructiveness of the methodology for modeling realistic grains. Then, trained ML model exhibits promising accuracy for the prediction of mechanical properties. This work showcases an integrated computation framework combining advanced materials science and ML techniques for enhancing understanding of the L-PBF process and offering valuable insights into process optimization for L-PBF-built diverse materials.

Investigation of agricultural waste and ZrB2 nanoparticles with reinforcement in aluminum alloy matrix

Agricultural waste has the potential to serve several purposes, such as reinforcement. In recent times, researchers have incorporated agricultural waste into various materials with the aim of enhancing their qualities. By acting as a kind of reinforcement, it has the potential to decrease the quantity of agricultural waste that needs further processing. This work enhances the area of advanced materials by examining the characteristics of Al 7175 alloy reinforced with zirconium diboride (ZrB2) nanoparticles and rice husk ash, which is a byproduct of agriculture. Understanding and improving the wear resistance of composites is crucial in several industrial applications. This study involves the incorporation of ZrB2 nanoparticles into the Al 7175 alloy at three distinct concentrations, with the addition of 2.5 % rice husk. This study examines the correlation between wear parameters and responses (Cf), including friction force (FF), wear rate (Sf), and friction coefficient. Sliding distance, load, composition, and speed are among the wear parameters. The aforementioned combinations result in a load of 25.2 N, a rotational speed of 400 rpm, a sliding distance of 71.2 m, and a composition of 5 %. Taguchi signal-to-noise ratio (SNR) analysis is used to identify optimal combinations for minimizing Cf, Sf, and FF. Confirmation tests are conducted in order to ensure that the results align with the expected optimal combinations. Data scientists may also use an Artificial Neural Network (ANN) model as a valuable tool. It utilizes input data to forecast replies. The ANN model demonstrates strong performance throughout testing, validation, and training, with an overall prediction rate of 87.873 %. The study's results indicate that reducing the load and speed, while increasing the concentration of ZrB2 nanoparticles, may effectively decrease the wear rate. In addition, the use of rice husk enhances the wear resistance of the base alloy by 28 %. The alloy Al 7175 may experience a reduction in wear rate and friction coefficients by the incorporation of 2.5 % rice husk and 5 % ZrB2 nanoparticles.

Jewellery Development in Right-Bank Ukraine and Galicia (XVI-XIX Centuries): Insights from Precious Ecclesiastical Artifacts

This article examines the development of jewellery in Right-Bank Ukraine and Galicia from the XVI to XIX centuries, focusing on precious ecclesiastical artifacts as evidence of the flourishing of Ukrainian goldsmithing. The relevance of the research stems from its detailed exploration of ecclesiastical jewellery in Right-Bank Ukraine and Galicia, providing a unique perspective on the region's artistic heritage and European cultural integration. The purpose is studying the artistic techniques used by Lviv and Kyiv jewellers in creating church artifacts like domes, icon covers, and other ecclesiastical items. The historical-genetic method enabled comprehensively analysing the evolution of Right-Bank Ukrainian jewellery in the example of church artifacts. Periodization identified three stages of Ukrainian goldsmithing's development in the XVI-XIX centuries. The system- structural method emphasized Western European cultural influence on overall Ukrainian jewellery. The typological approach reflected empirical reality of Right-Bank Ukrainian jewellery development as evidence of flourishing culture. Narrative described and explained the significance of jewellery artifacts at each stage of the formation of Ukrainian goldsmithing. Research materials included art organizations' experience, archaeological documentation, and museum exhibits. As a result of the research, the article presents the work of such Kyiv masters as: Iyeremiya Biletskyy, Ivan Ravych, and Matviy Narunovych. Detailed descriptions of works of art by Lviv and Kyiv masters of the XVI- XIX centuries are provided. And information about the Kyiv goldsmith shop is displayed. Conclusions confirm that Right-Bank Ukraine and Galicia were a stronghold of European jewellery styles in the 16th-19th centuries. The study of church artefacts by Ukrainian craftsmen shows a special cultural mentality shaped by centuries-old traditions and the multidenominational nature of Christian faiths. Thus, the materials of the article represent a practical value for historians, ethnographers, and architects who are interested in the construction of Orthodox churches; and jewellers engaged in artistic blacksmithing.

Design and Optimization of Disc Oil Skimmer

Abstract: Oil Spills are a common phenomenon in the oceans and seas causing economic loss as well as loss of aquatic life. Oil skimmers are devices used to separate the oil from water and recover it to the maximum extent possible. This project focuses on material selection for oil skimmer discs, considering corrosion resistance, wear characteristics, cost-efficiency, and environmental impact. It explores common materials such as polyurethane, oleophilic materials, stainless steel, PVC, and aluminum, emphasizing their unique properties and environmental implications. By conducting a thorough literature review and establishing stringent material selection criteria, the project aims to inform a material choice that balances technical requirements with environmental responsibility. The exploration of advanced materials and optimization of material design are also discussed. The project anticipates enhancing oil skimmer efficiency, reducing maintenance needs, and promoting sustainable practices in environmental protection. The project further includes building a prototype of a single disc oil skimmer and find an ideal diameter for efficient oil skimming taking into consideration the mass of the disc as well as the overall oil skimmer.

Photo-Healable Fabrics: Achieving Structural Control via Photochemical Solid-Liquid Transitions of Polystyrene/Azobenzene-Containing Polymer Blends.

While polymer fabrics are integral to a wide range of applications, their vulnerability to mechanical damage limits their sustainability and practicality. Addressing this challenge, our study introduces a versatile strategy to develop photohealable fabrics, utilizing a composite of polystyrene (PS) and an azobenzene-containing polymer (PAzo). This combination leverages the structural stability of PS to compensate for the mechanical weaknesses of PAzo, forming the fiber structures. Key to our approach is the reversible trans-cis photoisomerization of azobenzene groups within the PAzo under UV light exposure, enabling controlled morphological alterations in the PS/PAzo blend fibers. The transition of PAzo sections from a solid to a liquid state at a low glass transition temperature (Tg ∼ 13.7 °C) is followed by solidification under visible light, thus stabilizing the altered fiber structures. In this study, we explore various PS/PAzo blend ratios to optimize surface roughness and mechanical properties. Additionally, we demonstrate the capability of these fibers for photoinduced self-healing. When damaged fabrics are clamped and subjected to UV irradiation for 20 min and pressed for 24 h, the mobility of the cis-form PAzo sections facilitates healing while retaining the overall fabric structure. This innovative approach not only addresses the critical issue of durability in polymer fabrics but also offers a sustainable and practical solution, paving the way for its application in smart clothing and advanced fabric-based materials.

Statistical Mechanics Approaches for Studying Temperature and Rate Effects in Multistable Systems

Systems with a multistable energy landscape are widespread in physics, biophysics, technology, and materials science. They are strongly influenced by thermal fluctuations and external mechanical actions that can be applied at different rates, moving the system from equilibrium to non-equilibrium regimes. In this paper, we focus on a simple system involving a single breaking phenomenon to describe the various theoretical approaches used to study these problems. To begin with, we propose the exact solution at thermodynamic equilibrium based on the calculation of the partition function without approximations. We then introduce the technique of spin variables, which is able to simplify the treatment even for systems with a large number of coordinates. We then analyze the energy balance of the system to better understand its underlying physics. Finally, we introduce a technique based on transition state theory useful for studying the non-equilibrium dynamical regimes of these systems. This method is appropriate for the evaluation of rate effects and hysteresis loops. These approaches are developed for both the Helmholtz ensemble (prescribed extension) and the Gibbs ensemble (applied force) of statistical mechanics. The symmetry and duality of these two ensembles is discussed in depth. While these techniques are used here for a simple system with theoretical purposes, they can be applied to complex systems of interest for several physical, biophysical, and technological applications.

Artificial Intelligence and Privacy

Modern Artificial Intelligence (AI) technologies have a rapidly growing impact on a wide range of human activities. AI methods are being used in varied domains such as healthcare, material science, infrastructure engineering, social media, surveillance technologies, and even artistic expression. They have been used for the purposes of drug discovery via protein folding prediction, power usage optimization through reinforcement learning, and facial recognition by means of image segmentation. Their effectiveness and wide-scale, unregulated deployment within our societies pose significant risks to our fundamental rights. Multiple existing AI methods have the potential to profoundly undermine our ability to safeguard our privacy. The societal impact of such AI models can be investigated through six concentric Heuristic Zones of privacy. These AI models can perform inferences regarding highly sensitive, personal information such as race, gender, and intelligence from seemingly innocuous data sources beyond the capabilities of human experts. They are capable of generating increasingly accurate text and image recreations of our thoughts from non-invasive brain activity recordings such as magnetoencephalography and functional magnetic resonance imaging. Furthermore, prospective AI technologies pose concerns about the existential risk to our civilization which extend beyond the erosion of privacy and other fundamental human rights.

A review on the biological and bioactive components of Cyperus esculentus L.: insight on food, health and nutrition.

Tiger nut (Cyperus esculentus L.) is a small, tuberous root vegetable that has gained increasing attention in recent years due to its potential health benefits. This review article provides an elaborate overview of tiger nut, including its botany, historical uses, nutritional composition, potential health benefits and traditional medicinal uses. This review article comprehensively discusses the nutritional profile of tiger nut, providing a detailed understanding of its nutrient content. Furthermore, the potential health benefits of tiger nut are thoroughly reviewed, including its effects on digestive health, cardiovascular health, blood sugar control, immune function and other potential therapeutic uses. Scientific articles used for this review were retrieved from ScienceDirect, Google Scholar, PubMed and SciELO databases. Only articles published between 1997 and 2022 were used for research. This review contributes to a better understanding of tiger nut and its prospective uses in functional foods and medicine by combining the available scientific material. © 2024 Society of Chemical Industry.

Effects of void geometry on two-dimensional monolithic porous phononic crystals

Phononic crystals are renowned for their distinctive wave propagation characteristics, notably bandgaps that offer precise control over vibration phenomena, positioning them as a critical material in advanced vibro-elastic engineering and design. We investigate how pore shapes influence the bandgap in continuum two-dimensional phononic crystals made from a single material. Using the square lattice and unit cells with fourfold symmetry, our numerical analyses reveal that the normalized gap size is highly dependent on the minimum ligament width in the structure. Additionally, we find that fine geometric features represented by higher-order Fourier coefficients decrease the gap size. This study offers insight into the design of phononic crystals and vibro-elastic metamaterials for precise wave control through void patterning.

Strength characteristics and energy evolution of cement stone under true-triaxial loading conditions

Oil well cement is a commonly used cementing material in oil and gas extraction engineering. Due to the change of stress conditions, it is prone to microcracks or micro annular gaps, leading safety concerns. To study the strength characteristics and energy evolution of oil well cement stone under three-dimensional stress states, a series of true-triaxial compression tests were carried out. Based on the experimental results, the mechanical properties and energy evolution mechanisms during the true-triaxial compression process of cement stone under different stress states were explored. The research results indicate that there is an intermediate principal stress effect on the true-triaxial compressive strength of cement stone specimens. When the minimum principal stress remains constant, the strength of cement stone first increases and then decreases with the increase of intermediate principal stress. When the minimum principal stress is 5MPa, the specimen exhibits brittle failure, with ε1 at peak stress approximately 0.015. As the minimum principal stress increases to 20MPa, the specimen gradually transits to plastic failure, with ε1 at failure exceeding 0.04. The type of failure is determined by the energy ratio at the time of failure; when there is more elastic energy, it results in brittle failure, otherwise it leads to ductile failure. Due to the high porosity of cement stone samples, most of the input energy is converted into dissipated energy. At minimum principal stresses of 5MPa, 10MPa and 20MPa, the ratio of peak dissipated energy to total input energy fluctuates around 0.55, 0.73 and 0.85, respectively. There is a strong linear relationship between the peak elastic energy, peak dissipated energy, and total input energy, with fitting correlation coefficients of 0.847 and 0.996, indicating that the cement stone sample also follows the linear energy storage law. A strength criterion for cement stone was established based on the modified Lade criterion, which is more suitable for describing the strength of high porosity materials compared to traditional strength criteria. Finally, based on the interaction mechanism between energy accumulation and energy dissipation, a nonlinear model of energy evolution in cement stone was established. The results of the theoretical model are in good agreement with the experimental data.

Quantitative Detection for Fatigue Natural Crack in Aero-Aluminum Alloy Based on Pulsed Eddy Current Technique

Aero-space aluminum alloys, as vital materials in aerospace engineering, find extensive application in various aerospace components. However, prolonged usage often leads to the emergence of fatigue natural cracks, posing significant safety risks. Therefore, research on accurate quantitative detection techniques for the cracks in aerospace-aluminum alloys is of vital importance. Firstly, based on the three-points bending experimental model, this paper prepared the fatigue natural crack specimen, and the depth of the natural crack is calibrated. Then, given the complexity of geometric characteristics inherent in natural cracks, the pulsed eddy current signal under the different natural crack depth is acquired and analyzed using an experimental study. Finally, to better exhibit the non-linearity between PEC signal and crack depth, a GA-based BPNN algorithm is proposed. The Latin Hypercube method is considered to optimize the population distribution in the genetic algorithm. The results indicate that the characterization accuracy reaches 2.19% for the natural crack.