Behavior Of Materials Research Articles

Study on self-healing performance of microcracks in SBS/waste rubber powder composite-modified asphalt based on molecular dynamics simulation

The internal microcracks in asphalt materials can heal spontaneously under suitable conditions, and understanding the characteristics of the self-healing behavior of asphalt materials is crucial for evaluating the fatigue life of asphalt pavements. In this paper, a molecular model of modified asphalt microcracks was created by introducing modifier molecules into the virgin asphalt model, and the self-healing process of the asphalt microcrack model under different healing conditions was investigated, which revealed the effects of modifier materials and healing temperatures on the healing performance of asphalt. The results show that the effect of healing temperature on asphalt healing performance is more significant than the modifier material, the relative concentration of molecules at the microcrack healing and the healing temperature is positively correlated; asphalt material healing free volume fraction with the increase in healing temperature gradually increases, the incorporation of modifiers can reduce the free volume fraction growth caused by high-temperature healing, improve the healing stability of modified asphalt. The asphalt ductility specimen crack healing test shows that when the healing temperature exceeds 45 ℃, there is a decreased increase in self-healing rate; taking into account the high-temperature healing is easy to make the asphalt material produce permanent deformation, this paper determines the optimal healing temperature in the vicinity of 48 ℃. The research results have certain reference and application values for asphalt pavement damage repair.

Synergistic ductility deformation and helical design of carbon nanotube fiber composites

Twisting attracts more attention in adjusting the mechanical behavior and failure mechanism of materials, which could be implemented to understand and design the deformation behavior of helical structures. Herein, we developed a general helical model to theoretically investigate the mechanical response and geometric evolution of twisted carbon nanotube (CNT) fiber. The in-situ experimental results of CNT fibers in scanning electron microscopy were used to verify the correctness of the theory. For the structure with a large helical angle, the interfacial force and uncoordinated interlayer deformation during elongation are the key factors determining its unique tensile-torsional coupled motion. By helical design, the elongation and deformation of brittle fiber in composite structure can be delayed to achieve synergistic fracture with ductile fiber. The breaking order of these two fibers under stretching can be further regulated by changing the degree of twisting. Based on these theory results, the outer brittle fibers could also be used to predict the tensile necking and fracture locations of inner ductile materials. This approach can be achieved by changing the helical geometry and failure strain, and this work would throw light on the mechanical design of multi-layer cables and fiber composites.

Analyzing the mechanical behavior of granular materials: A multi-morphological approach using spherical harmonics and LS-DEM

This paper investigates the micro-to-macro response of granular materials influenced by multi-scale morphological characteristics using spherical harmonics and LS-DEM. Our simulation results reveal that particle elongation plays the primary role in governing the shear strength and dilatancy, with surface roughness also affecting these macroscopic behaviors of non-elongated assemblies while marginally influencing elongated assemblies. At the microscale, more elongated particles with a higher degree of roughness present a stronger interlocking effect. Furthermore, we quantitatively establish a connection with the system stress ratio through the stress-fabric-force (SFF) relationship, enabling us to comprehend the shape-dependent macroscopic shear strength from microscopic anisotropy perspectives. Our results indicate that more elongated and rougher particles lead to a more significant fabric anisotropy at the critical state. Additionally, a mechanics-based shape parameter, known as rotational resistance angle, is found to correlate linearly with the critical shear strength of all explored assemblies, which can be explained by the microscopic linkage between all partitioned anisotropy components and the adopted shape parameter.

Revealing and predicting the mechanical and strain hardening behaviors of Cu-Al alloys based on microscopic mechanism

In order to reveal and predict the strain hardening behaviors of metallic materials, mechanical properties of Cu-Al alloys processed by rolling were investigated by tensile tests. The microstructure evolution of Cu-Al alloys processed by rolling were characterized. The true stress-strain curves were fitted by an exponential strain-hardening (ESH) model. Based on the microscopic mechanism of dislocation growth and annihilation, the true stress strain curves were predicted through macroscopic mechanical properties. The strengthening effects on Cu-Al alloys of different methods were analyzed quantitively by hardening exponent z and saturation strength σs which were derived from the ESH model. The fundamental assumptions and physical meaning of parameters have been validated by investigating strain hardening behaviors of Cu-Al alloys. The limited applicable materials and future research of ESH model are also proposed for the further development. This study could provide guidance to understand work-hardening behavior and predict tensile performance of Cu-Al alloys.

The determination of the curing induced, nonlinear elastic field of an inclusion in photo-cured materials

A wide variety of photo-cured materials have recently been developed with the rapid advancement of three-dimensional (3D) printing technology. However, most of these materials are designed as soft functional materials, and their failure mechanisms have received little attention. This work studies the mesoscale residual stress defects of photo-cured materials that are generated due to non-uniform curing and volume shrinkage during the manufacturing process. The defects are simplified as uncured inclusions embedded within a fully cured, infinite matrix which are then additionally cured. A large deformation model, validated against finite element analysis, is established to determine the nonlinear elastic field induced by the curing of inclusions with different Poisson’s ratio and shape (i.e., sphere and prolate spheroid), and is shown to outperform the infinitesimal strain model. This large deformation model, which includes a phase evolution constitutive model to describe the inclusion’s behavior and a compressible neo-Hookean model to describe the matrix’s behavior, is derived based on the same elastic field distribution as that in the infinitesimal strain solution and an ellipsoid-ellipsoid transformation kinematics assumption. The final solution is expressed in a discrete formulation and is exact for the spherical inclusion and approximate for the prolate spheroid inclusion. The prediction results of the theoretical model are compared with the finite element analysis, and reasonable agreement is obtained. This study may lay a foundation for investigating the effects of mesoscale residual stress defects on the mechanical behavior of 3D printing materials.

Machine learning approach to evaluating impact behavior in fabric-laminated composite materials

Fabric-layered composites play a crucial role in safety and surveillance applications, making it imperative to accurately predict their impact behavior. This research focuses on creating a machine-learning model to predict the impact behavior of fabric-stacked composites, specifically carbon and Kevlar fabrics. Low-velocity impact tests were performed with varying parameters, and the impact energy and laminate thickness information were used to train machine-learning models to predict impact properties such as impact force, displacement, and absorbed energy. It was observed that the impact force increased by 118.5 % in carbon-laminated fibers and 175.8 % in Kevlar-laminated fibers, while the hybrid layer showed a 101.4 % increase upon impact from 16J. Displacement can affect the stability of the layered structure; thus, a similar stacking sequence is less stable than the hybrid laminated structure. In terms of absorbed energy, as the laminated layers increase, carbon fiber laminate absorbs 4.8 times more energy, and Kevlar fiber and hybrid laminated structures absorb 3 times more energy at higher impact energy. Furthermore, four machine learning models were used to investigate the impact behavior of identical and mixed-layered laminated composites. The impact force and displacement were predicted with higher accuracy using the polynomial regression model, achieving 80 % and 89 % accuracy, respectively. The support vector machine predicted the absorbed energy with approximately 96 % accuracy. In continuing, the experimental results closely matched the predictions made by the other machine learning models utilized in this study. Additionally, the importance of distinctive features and their influence on the performance of the machine learning-based model were interpreted using transposed features of importance and dependency plots. Various failure modes in fabric laminated composites were also identified, providing insights to enhance the performance of stacked fiber materials.

Influence of real particle morphology on single particle crushing behavior of rockfill based on FDEM

Particle morphology is critical in affecting the crushing behavior of rockfill materials. In contrast, most current single particle simulations lack satisfactory morphology accuracy, and the resulting crushing modes deviate from observations to some extent. Therefore, we reconstruct the real particle morphology with the spherical harmonic (SH) method and employ the finite-discrete element method (FDEM) to simulate the one-dimensional (1D) compressive crushing process of basalt particles commonly used in rockfill. The influences of four main morphological parameters, i.e. sphericity, aspect ratio, roundness, and convexity, on the single particle strength and the crushing modes are discussed. The results show that with the SH degree set to 15 and a mesh number of 20,480, the FDEM models of reconstructed particles achieve sufficient morphology accuracy and high computational efficiency. Based on the model, the simulation results demonstrate that the aspect ratio has the most significant impact on single particle strength, followed by sphericity. In contrast, roundness and convexity have a weaker effect than the above two parameters. Also, it is revealed that single particle strength decreases with increasing aspect ratio and sphericity, while it increases with higher roundness and convexity. Furthermore, aspect ratio significantly changes the initial crushing position, sphericity dominates post-crushing fragment size and quantity, and roundness mainly affects post-crushing morphology. The model results have been employed in establishing a support vector regression (SVR)-based predicted model, exhibiting good predictive performance and advantages for the optimization of rockfill particles in engineering.

Mount for spectroscopic analysis of samples under sustained tensile stress.

Spectroscopic methods offer valuable insights into the molecular and structural changes induced by stress, but existing techniques are often unable to perform real-time measurements during deformation. A novel solid open mount design is presented that enables spectroscopic investigations of materials under sustained tensile stress while maintaining crucial alignment of the optical system. The mount design allows for sample movement in response to applied strain while maintaining the position of the sample plane, ensuring consistent and reliable spectroscopic measurements. The effectiveness of the mount design is demonstrated with vibrational sum-frequency generation measurements of an elastomer, cured hydroxyl-terminated polybutadiene, and a plastic, high-density polyethylene, taken before, during, and after tensile deformation. The application of this mount to other spectroscopic techniques is discussed. The ability to collect spectroscopic data during a stress event would provide valuable insights into the behavior of stressed materials.

Valorization of a high-sulfur petroleum coke for energy and fuels through its co-processing with a forest waste, using concrete wastes for sulphur and carbon dioxide capture under mild conditions

Current work provided a comprehensive assessment on the pyrolysis, combustion and gasification of a high-sulfur pet coke (PEC) and its blends with a forest waste (FOP). The potential of waste concrete fractions to capture SO2 and CO2 emissions was explored. The experiments were conducted in a fixed bed system and a thermogravimetric-mass spectrometric unit. Thermal behavior, reactivity, conversion, synergy, structural and chemical characteristics of solid materials, quantitative analysis of products and heating value, chemical, mineralogical and fusibility analysis of ashes were studied as a function of temperature, blending ratio and sorbent/fuel ratio. Addition of sorbent at a ratio Ca/S = 2 resulted in a desulfurization extent of 76–81 % during combustion. Quarry dust sorbent captured up to 95.4 % of CO2 emitted below 700 °C. At 1000 °C H2 content was 64.8–72.9 % mol and syngas yield 1.1–1.8 m3/kg. The gasification performance of PEC was improved upon blending with FOP.

Unveiling the fate of metal leaching in bimetal-catalyzed Fenton-like systems: pivotal role of aqueous matrices and machine learning prediction

Metal-based catalytic materials exhibit exceptional properties in degrading emerging pollutants within Fenton-like systems. However, the potential risk of metal leaching has become pressing environmental concern. This study addressed scientific issues pertaining to the leaching behavior and control strategies for metal-based catalytic materials. Innovative cobalt-aluminum hydrotalcite (CoAl-LDH) triggered peroxymonosulfate (PMS) activation system was constructed and achieved near-complete removal of Ciprofloxacin (CIP) across diverse water quality environments. Notably, it was found that the tunable ion exchange and Al3+ stabilization of CoAl-LDH occurred due to the particularity of neutral water quality, resulting in significantly lower Co2+ leaching levels (0.321 mg/L) compared to acidic conditions (5.103 mg/L). In light of this, machine learning technology was then employed for the first time to simulate the dynamic trend of Co2+ leaching and elucidated the critical regulatory roles and mechanisms of Al3+, aqueous matrix, and reaction rate. Furthermore, degradation systems based on different water quality and metal leaching levels regulated the generation levels of SO4.- and O2∙-, and the unique advantages of free radical attack paths were clarified through CIP degradation products and ecotoxicity analysis. These findings introduced novel insights and approaches for engineering application and pollution control in metal-based Fenton-like water treatment.

Temperature dependence of the friction and wear behavior of pure tungsten

In this work, the friction and wear characteristics of rolled pure tungsten were investigated by using atomic force microscope (AFM) and field emission scanning electron microscope (SEM) with electron backscatter diffraction (EBSD) characterization techniques. A ductile to brittle transition (DBT) related frictional wear behaviors have been discovered. The results indicated that the coefficient of friction maintains an almost constant value of 0.45 at low temperatures (≤ 400 °C), whereas it consistently decreases at 600 °C due to the generation of a surface oxide. The wear rate varies with temperatures and reaches a maximum at 200 °C due to the transition of the tungsten matrix from brittleness to pseudoplasticity, which leads to severe adhesive wear and large mass loss. In addition, the evolution of sub-grains underneath the friction layer and Vickers microhardness were evaluated as well. This work provides insight into understanding the relationship between temperatures, microstructure and the frictional properties of tungsten materials, and thus provides guidance for improving frictional wear behaviors in tungsten materials.

Modeling time-dependent deformation in concrete: A fractional calculus method with finite element implementation

This study presents a novel numerical method to simulate the time-dependent behavior of concrete materials. The deformation response of both traditional and fractional calculus (FC) viscoelastic models is analyzed by the proposed method, in which models’ one-dimensional constitutive relationships are extended to the three-dimensional form. By applying numerical and finite difference methods based on Caputo-type fractional integration, the stress-strain behavior of the FC viscoelastic model is discretized over the time scale. This method exhibits broad application prospects, and can be employed to represent various forms of viscoelastic models. For the concrete material, suitable FC viscoelastic models are developed. To facilitate practical engineering applications of the proposed model, a numerical solution algorithm is implemented in the finite element (FE) analysis through the User-defined Material Mechanical Behavior (UMAT) interface of the commercial FE software ABAQUS. Finally, FE results are compared with the experimental results from several concrete creep tests. The consistency between the FE results and experimental data confirms the effectiveness of the proposed model in describing concrete behavior. The proposed method and model provide theoretical and numerical support for a more profound understanding and simulation of the time-dependent deformation of RC specimens in practical engineering applications.

Enhanced tribological performance of MoS2 and hBN-based composite friction materials: Design of tribo-pair for automotive brake pad-disc systems

This research comprehensively analyzes the friction and wear behavior of composite friction materials when dry sliding against grey cast iron and laser-clad nickel-based (LC1) and iron-based (LC2) alloy discs. The composite friction materials (P1, P2, P3, P4, P5, and P6) under investigation contain graphite, MoS2, and hBN-based solid lubricant synthesized through the powder metallurgy technique. Tribological tests were conducted using a pin-on-disc configuration to simulate the dynamic interaction between the composite materials and the laser-clad grey cast iron discs. The tests were performed at a 60 N load, 6283.19 m sliding distance, and 2.094 m/s sliding velocity under dry sliding conditions. The results provide valuable insights into the effectiveness of MoS2 and hBN-based solid lubricant composites in reducing friction and wear when in contact with iron and nickel alloy-based laser-clad grey cast iron surfaces. The study elucidates the mechanisms governing tribological behavior, including the formation of friction plateaus and the role of laser-clad counter-discs in reducing wear. The specific wear rate of the nickel-based laser-clad counter disc (LC1) and iron-based laser-clad (LC2) system improved by 63.76 % and 48.32 %, respectively, compared to the conventional grey cast iron disc system when using the hBN-based pin (P6). Additionally, the specific wear rate of the hBN-based pin was 38.49 % lower than the conventional graphite-based pin when sliding against the grey cast iron counter-disc. Artificial Neural Network (ANN) was used to validate the wear rate of the best-performing tribological pair, namely the hBN-based pin (P6) and LC2 counter discs, through supervised learning.

Comparative analysis of experimental techniques for microstructural characterization of novel nanostructured aluminium alloys

Precipitation holds a pivotal role in comprehending the intrinsic behavior of materials. In the design of nanostructured metallic alloys, precipitates have found to increase the alloys' stability and response under extreme environmental conditions. Studies on precipitation often rely on conventional and ex situ electron-microscopy methods, but a systematic investigation that compares different sample conditions during heat treatment and its microstructural implications are rarely available. In this context, we employed a novel ultrafine-grained AlMgZnCuAg crossover alloy to compare three distinct conditions for investigating the precipitation sequence: (i) ex situ transmission electron microscopy (TEM) from bulk heating, (ii) ex situ TEM from TEM foil heating, and (iii) in situ TEM with microelectromechanical-system (MEMS) heating. Although the heat treatment procedure was consistent across all cases studied, the application of these three different experimental conditions in the same alloy system resulted in significant and non-negligible differences in the final precipitation behavior. Ultimately, it resulted in observable microstructural variations and precipitates with distinctively different shape and sizes and, as a result, we outline herein the major similarities and differences among these techniques to achieve comparable results. This knowledge will help to compare and assess results of precipitation sequences obtained in different conditions.

A Review of Impedance Spectroscopy Technique: Applications, Modelling, and Case Study of Relative Humidity Sensors Development

Impedance Spectroscopy (IS) is a general term for the technique referring to small-signal measurements of the linear electrical response of a domain of interest. This method is based on the analysis of the system’s electrical response to yield helpful information about its domain-dependent physicochemical properties (generally, the analysis is carried out in the frequency domain). Nowadays, there are many areas of application where IS can be used to evaluate or enhance the development of emerging products and processes. As a contribution to this field of research, this paper presents relevant theoretical–practical aspects of the interpretation and analysis of the electrical behavior of materials based on IS and IS modelling. The work starts by historically introducing IS and then goes through different domains of application of the technique, such as Materials Science and correlated areas. Afterwards, an introduction to IS usage for constructing equivalent electrical circuits is presented, aiming at modelling the materials’ electrical behavior, followed by examples from the literature that use the two possible circuit development approaches, the series and the parallel association of circuit elements. Lastly, the authors present a case study of their most recent efforts of a circuit model development of relative humidity (RH) sensors based on heterogeneous mixed metal oxide (MMO) nanostructures, used to understand and identify existing contributions to the overall electrical response of the sensors to moisture; in their case, the electrical response of the MMO sensors was modelled with a high level of superposition between the experimental and fitted data, using a parallel combination of circuit elements, which is an unconventional one.

A Crystal Plasticity Based Strain Rate Dependent Model across An Ultra-wide Range

Numerous studies have investigated the strain rate sensitive behaviors of materials, consistently reporting enhanced stress values and increased dislocation density with rising strain rates. Behind these phenomena lies the intrinsic nature of dislocation activity. In this context, we introduce an analysis method within a crystal-plasticity (CP) framework, incorporating molecular dynamics insights for a comprehensive range of strain rates (7.5 × 10−5/s to 5 × 107/s). This approach offers a refined understanding of strain rate sensitivity (SRS) behaviors, mainly influenced by dislocation movement laws and strain-rate-dependent saturation of dislocation density. We elucidate the impact of deformation loading conditions on Schmidt factors and active slip systems, which are also crucial for understanding variations in SRS. Ultimately, this study underscores the CP method's effectiveness in comprehensive SRS analysis, seamlessly integrating experimental observations with theoretical predictions for advanced material characterization.

The effect of gamma-ray irradiation on polymer-graphene nanocomposite interfaces

CNT yarns are used in ultra-high strength composites for use in manned deep-space vehicles. It has been previously demonstrated through experiments that gamma-ray irradiation substantially improves the mechanical performance of these composites. It is unclear how the irradiation affects the mechanical response of the CNT yarn/polymer interface that ultimately leads to these panel-level performance improvements. Physical insight into this process could enable further improvements in the CNT yarn/polymer interface design in the future. The objective of this research is to use molecular dynamics simulation to provide physical insight into the effect of gamma-ray irradiation on the mechanical behavior (interfacial interaction energy, shear resistance, adhesive strength) of the CNT yarn/polymer interface for a range of high-performance polymer systems. The simulation results indicate that gamma-ray irradiation (simulated via inclusion of defects on the CNT surface) has a most significant effect on the shear deformation resistance of CNT yarn/polymer interfaces, which likely leads to the experimentally-observed improvements in panel-level CNT yarn composites irradiated with gamma rays. The results of this study also demonstrate the importance of computational modeling in providing physical insight into observed bulk-scale material behavior. Although the predictions cannot be validated directly via experiment, such insight can ultimately lead to efficient improvements in material design (e.g. mechanical performance) that lead to further increases in panel-level composite performance.

An enhanced Energy-Based hysteresis model for electrical steel sheets considering mechanical stress

Mechanical stress significantly influences the hysteresis characteristics of silicon steel, which are crucial for the design of electrical equipment cores. This study develops an improved Energy-based hysteresis model that integrates the effects of mechanical stress by modifying the anhysteretic magnetization model to include total average anisotropy energy density and introducing a linear relationship between coercive force and mechanical stress. The model’s performance is demonstrated using 30QG120 oriented silicon steel sheets, where the hysteresis loops under varying stress conditions are successfully simulated and validated against experimental data. The results confirm the model’s accuracy and practical utility in predicting material behavior under mechanical stress, offering a valuable tool for optimizing electrical steel sheet design.

A 2-D fabric anisotropic hyperelastic constitutive model based on micromechanics analysis

The analysis of the large deformation process of two-dimensional (2-D) fabrics helps to obtain the new distribution of yarns’ orientation and fiber in-plane density, which exert a considerable influence on the mechanical properties of the 2-D fabric composite component. By examining the underlying micromechanics involved in the shearing process, we developed a shear constitutive law within an anisotropic hyperelastic constitutive model framework, which is capable of capturing the large deformation of 2-D fabrics precisely. The constitutive law introduces parameters with specific physical meanings, facilitating their acquisition and modification. The proposed model was implemented in ABAQUS using a dedicated subroutine, UANISOHYPER_INV, for defining anisotropic hyperelastic material behavior through invariant formulation. The shear properties of 2/2 twill fabric were examined, and the parameters of the shear constitutive model were determined via bias-extension tests and corresponding finite element computations. The accuracy and reliability of the proposed model were validated through a hemispherical stamping test on the 2-D fabric and frame shear experiments performed by other researchers. This work contributes to the field by providing a robust method for characterizing and predicting the shear behavior of textile composites, thus enhancing the design and optimization of advanced fabric materials.

Impact properties of an end of life tires’ rubber. Numerical validation considering large strain and strain rate conditions

The objective of the authors is to demonstrate that the inclusion of renewed rubber from recycled end of life tires (ELT) can improve the performance of any structural system designed to dissipate impact energy. An interesting application would be its use in road safety barriers. This research starts with the rigorous characterization of the recycled material in order to include it in a viable numerical model. The authors presented, in a previous work (*), the experimental viscoelastic properties of recycled rubber, obtained under impact conditions. Bergström-Boyce (BB) nonlinear viscoelastic model was selected as the most suitable to fit the material behavior. This model is defined by nine material constants that are impossible to obtain, uniquely and directly, considering that only compression test results are available as input data. To overcome this challenge, optimization methods were applied resulting in as many sets of parameters as used optimization methods were considered and, moreover, remarkable differences between constants were observed. Solving this problem is the motivation of the present research: the validation of the optimization method by mean of the numerical evaluation of the obtained sets. The software considered for the numerical evaluation of impact tests (LS-DYNA®) had two slightly different implementations for the BB model: the original, based on the work published in 2009 by Dal & Kaliske and a more recent one implemented by Bergström, based on his works published in 1998 and 2000. This leads to a new question: which is the most appropriate implementation-optimization method for calibrating this material? This paper provides the answer to this question carrying out a complete comparative numerical analysis of all sets by means of explicit dynamics simulations. All calibrations, using the original LS-DYNA® implementation, were in perfect agreement with the experimental results. However, only one optimization method produced acceptable results for the most recent approach. A robust method to characterize recycled rubber from recycled tires using the Bergström-Boyce nonlinear viscoelastic model is presented, despite the experimental limitations (González-Vega et al. 2022).