Material Properties Research Articles

Lead-Free Halide Double Perovskites for Sustainable Environmental Applications

The development of renewable energy sources has become a crucial objective in today's world due to increasing environmental concerns and the depletion of fossil fuels. Solar energy has emerged as a promising alternative. In recent years, there has been a significant focus on perovskite solar cells due to their remarkable power conversion efficiencies and their ability to be produced in a cost-effective manner. These cells have attracted considerable attention from researchers and industry professionals alike. However, traditional perovskite materials often contain toxic lead, raising concerns about their environmental impact and long-term sustainability. This article highlights the environmental concerns associated with lead-based perovskite materials and explores the advantages, challenges, and potential of lead-free halide double perovskites as sustainable alternatives for achieving an enlightening and sustainable future in the field of photovoltaics. Lead-free halide perovskites have been an area of active research in the field of nanotechnology and material science due to their potential for various applications. We provide an overview of perovskite solar cells as a promising technology, discussing their material properties and device performance. Furthermore, we present a comparative analysis between lead-based and lead-free perovskites, emphasizing the challenges and future perspectives associated with the development and implementation of lead-free alternatives. Through this analysis, we aim to shed light on the potential of lead-free halide double perovskites and inspire further research in the quest for environmentally friendly materials for solar energy applications.

Strain mode measurement of asphalt pavements using distributed fibre optic sensor data

This paper proposes a method for measuring strain modes in asphalt pavements using distributed fibre optic strain sensor data. A processing algorithm based on cross power spectral density (CPSD) was developed to utilize high spatial resolution strain data to determine the CPSD peak frequency and corresponding relative amplitude. The proposed method was applied in both laboratory and field settings, comparing the results of distributed fibre optic cables with those of accelerometers or theoretical solutions to validate accuracy. Local heating of asphalt structures was used to test the sensitivity of the measured strain modes to changes in material properties. The results demonstrate that different fibre optic cables can provide peak frequencies comparable to traditional accelerometers (±0.6 Hz). Additionally, they offer relative amplitude with a resolution of 1 cm, achieving a modal assurance criterion exceeding 0.95 when compared to theoretical strain mode shapes. The method also sensitively reflects material property changes at different positions within the asphalt structure. This indicates that the proposed approach can effectively measure strain modes in asphalt structures, offering a more detailed understanding of the distribution of structural properties compared to traditional methods.

Reliability-based topology optimization of imperfect structures considering uncertainty of load position

In this paper, a novel optimization technique is implemented to explore the effects of considering uncertain load positions. Therefore, the integration of reliability-based design into structural topology optimization, while considering imperfect geometrically nonlinear analysis, is proposed. By comparing the results obtained from perfect and imperfect geometrically and materially nonlinear analyses, this study examines the impact of nonlinearity on probabilistic and deterministic analyses. Concerning probabilistic analysis, the originality of this research lies in its incorporation of the position of the applied load as a stochastic variable. This distinctive approach complements the consideration of other relevant parameters, including volume fraction, material properties, and geometrical imperfections, with the overarching goal of capturing the variability arising from real-world conditions. For the assessment of uncertainties, normal distribution is assumed for all these parameters. Normal distributions are chosen due to their advantages in terms of simplicity, ease of implementation, and computational efficiency. These characteristics are particularly beneficial when dealing with complex optimization algorithms and extensive analyses, as is the case in our research. The proposed algorithm is validated according to the results of benchmark problems. Structural examples like cantilever beam, pinned-shell, and L-shaped beam problems are further explored within the context of imperfect geometrically nonlinear reliability-based topology optimization, with specific regard to the probabilistic aspect of the location of the externally applied loads. Moreover, the results of the suggested approach suggest that the inclusion of a probabilistic design strategy has influenced topology optimization. The reliability index acts as a controlling constraint for the resulting optimized configurations, including the mean stress values associated with the resulting topologies.

Probabilistic Safety Assessment of Off-site Power System under Typhoon Considering Failure Correlation between Transmission Towers

High-intensity typhoons can cause failure to the structures, systems, and components of nuclear power plants (NPPs) and off-site power systems. Instances have occurred where failure of the off-site power system caused by typhoons has affected NPPs. The off-site power system has been in cases where a typhoon failed multiple transmission towers. In Korea, transmission towers have similar design criteria and material properties and experience similar wind characteristics, leading to a correlation in their failure probabilities. Assuming independent or totally dependent failure probabilities among the transmission towers is unrealistic. For a realistic PSA of the off-site power system due to typhoon-induced high winds, it is necessary to consider an appropriate failure correlation. This study performed a PSA of an off-site power system due to typhoon-induced high winds, considering the failure correlation between transmission towers. The failure correlation between transmission towers based on distance was calculated. The wind fragility of the off-site power system was convolved with the typhoon-induced high-wind hazard at the Kori NPP to calculate the probability of the NPP losing its power supply. Thus, applying the failure correlation of typhoon-induced high winds to the PSA of the off-site power system is considered realistic.

Piezomagnetic Behavior of Functionally Graded Cylinders under Non-Axisymmetric Hygrothermal Loading: Interplay between Loading Contribution, Material Properties, and Elastic Response

Piezomagnetic Behavior of Functionally Graded Cylinders under Non-Axisymmetric Hygrothermal Loading: Interplay between Loading Contribution, Material Properties, and Elastic Response

Contour maps of mechanical properties in ternary ZrB2-TiC-SiC ceramic system

Monolithic ZrB2, ZrB2-SiC, ZrB2-TiC and ZrB2-SiC-TiC were fabricated by hot pressing. Contour maps depicting grain size and mechanical properties were generated on the ZrB2-SiC-TiC ternary diagram through experimental data and software fitting. These visual representations effectively establish the relationships between chemical composition and material properties, despite the similar high hardness of three main compounds. Notably, the average grain size of ZrB2-SiC-TiC is significantly reduced by an order of magnitude compared to monolithic ZrB2. Both strength and hardness exhibit a strong correlation with grain size, while the elastic modulus demonstrates insensitivity to microstructure changes. The evolution of toughness proves to be complex.

Statistical Analysis of Near-surface Structure and Material Properties on Momentum Transfer in Rubble Pile Targets Impacted by Kinetic Impactors

Abstract Rubble pile asteroids consist of reassembled fragments of once larger monolithic asteroid parent bodies. Recent spacecraft missions to asteroids like Itokawa, Ryugu, Bennu, and Dimorphos suggest that rubble pile asteroids are common in the asteroid population, and rubble piles could be a likely structure among potentially hazardous objects. Therefore, it is important to understand the response of rubble pile targets to kinetic impacts for potential future deflection needs. The recent Double Asteroid Redirection Test (DART) mission motivates an investigation of kinetic impacts into rubble pile targets to understand their effects on deflection. Here, we simulate kinetic impacts into Dimorphos-sized asteroid targets to understand the effect of the impact site structure on the deflection efficiency of relevant sizes for planetary defense. We perform 52 two-dimensional simulations where we vary the impact site structure of the impact site, the target porosity, and the material behavior/strength model to understand their relative effects on crater size and the momentum enhancement factor (β). We find that the effects of the impact site on both crater size and β are greatest for impacts into weaker targets, where impact sites rich in matrix material result in statistically larger craters and higher βs compared to impact sites rich in boulder material. Further, impact site structures that promote increased boulder ejection result in larger β values. These results provide important intuition to understand the DART impact and to extrapolate results to future potential missions.

3d Mapping Of Stiffness Evolution Of Hardening Concrete With Saps Using Elastic Wave Tomography

Phenomena occurring during the delicate phase of concrete curing can have a strong influence on the final mechanical properties. Therefore, monitoring the changes during hydration can provide meaningful information on the material properties. Lately, non-destructive techniques have received great attention for monitoring earlyage concrete. This paper aims to assess the ultrasonic velocity and stiffness development of hardening concrete during various curing stages using the Elastic Wave Tomography (EWT) technique. The monitoring of the curing process starts as soon as seven hours after casting and lasts up to seventy hours. A three-dimensional (3D) wave velocity map is created, and conventional concrete is compared to concrete containing SuperAbsorbent Polymers (SAPs), a novel admixture used for shrinkage mitigation by providing internal curing in the cementitious matrix. However, SAPs have been proven to reduce compressive strength when added to concrete, due to the increased porosity they induce. This porosity may also result in the reduction of the wave velocity. However, the internal curing provided by the SAPs can promote the formation of new hydration products in the matrix and thus (partly) compensate for the strength loss making the uniformity of the internal curing another important point of concern. EWT can provide global information on the homogeneity of the influence of the SAPs in the cementitious matrix as opposed to the wave velocity of a single wave path that is usually examined in practice. In addition, the determination of the early-age stiffness evolution can be connected to the final mechanical properties of the material. The dynamic Young’s Modulus is calculated and compared to the static Young’s modulus at 28 days. Predictions towards the static Young’s modulus are also made, showing good agreement.

Implicit modular coupled heat transfer analysis for functionally graded materials using the SVC-FMC method

Functionally graded materials have found extensive applications in the aerospace industry and solar energy systems due to their excellent performance in enhancing heat transfer/insulation. Developing corresponding theoretical frameworks for the coupled radiation and conduction heat transfer (CRCHT) is crucial for unlocking their full potential and expanding their applicability in various high-performance and critical applications. Considering the limitations of existing frameworks in addressing CRCHT problems in practical applications, such as the explicit iteration procedure and the linearization assumption, a fully implicit framework as the source value caching function Monte Carlo (SVC-FMC) method is proposed based on the null collision reverse Monte Carlo and the Green's Function Markov Superposition Monte Carlo, which are suitable for solving the radiative transfer equation and the energy equation within non-uniform media. The accuracy of the proposed method is validated with different heat transfer systems. It was observed that the maximum root mean square error during the verification process did not exceed 0.08, thereby demonstrating the efficacy of SVC-FMC in analyzing CRCHT processes involving gradient materials. Results reveal that the material properties that transcend the functional distribution form will augment the strengthening effect of heat transfer/insulation. The scattering characteristics significantly influence the strengthening effect caused by refractive index distribution.

Machine learning powered predictive modelling of complex residual stress for nuclear fusion reactor design

Fusion In-vessel components, assembled and maintained using laser welding, one of the most promising techniques, exhibit complex distributions of residual stress, microstructures, and material properties. These residual stresses can compromise structural integrity and lifespan of critical components. Although using advanced experimental measurements can evaluate the residual stress for individual case, extending the measurements to massive number of components are costly and time-consuming. Traditional machine learning (ML) models struggle to account for the heterogeneity and anisotropy of these stress distributions. Here, we develop a novel ML framework based on the Eurofer97 steel, the structural material for in-vessel components. The ML framework is trained on high-resolution residual stress data derived from recently-developed evaluation techniques. Combining with microstructures, the model enables prediction of heterogenous and anisotropic residual stress distribution. It successfully predicts the compressive residual stress in fusion zone (∼−200 MPa) balanced by tensile residual stress in heat affected zone (∼300 MPa), aligning closely with experimental results with the R-squared value of 0.989 and the mean square error of 10−4. Unlike experiments that take hours, the ML model provides predictions within seconds. It offers valuable insights into residual stress prediction for various joints, enhancing the reliability and lifetime prediction of in-vessel components.

Synthetic thermal image generation and processing for close proximity operations

The new scenarios foreseen in forthcoming space missions have increased interest towards optical-based relative navigation techniques, which have demonstrated efficacy in a variety of operational conditions. Although object detection methods have predominantly been used within the visible spectrum, optical payloads struggle in weak lighting conditions and are susceptible to overexposure. Consequently, thermal imaging systems are being investigated as a potential solution, as their integration into the current systems would greatly extend future mission capabilities. This study seeks to fill the gap in literature by assessing the performance of state-of-the-art object detection algorithms with images captured in the thermal spectrum. Given the scarcity of readily available thermal infrared (TIR) images captured in orbit, a novel rendering pipeline is implemented to generate physically accurate thermal images relevant to close-proximity scenarios. These synthetic representations feature a simplified target spacecraft against Earth and deep space backgrounds, including variations in illumination conditions, material properties, relative state, and scale. To ensure realistic outputs, the radiative field of the Earth is modelled based on satellite measurements collected in the cloud and Earth radiant energy system (CERES) database. To enrich the fidelity of the outputs, a thermal sensor model and the corresponding noise levels are introduced in the pipeline. The generated images are then used to test the performance of traditional object detection algorithms in discerning the region of interest (ROI) under different orbital scenarios. The results demonstrate the effectiveness of the selected methodologies in mitigating the influence of the Earth in the ROI extraction process, while also revealing a performance degradation due to the presence of multi-material targets.

Stub column behaviour of high strength steel square hollow sections with semi-circular stiffeners

This paper proposes a novel high strength steel square hollow section with semi-circular stiffeners, aiming to delay or eliminate premature local buckling failure of the steel tube and lead to improved compressive performance. A total of 9 stiffened and unstiffened stub columns were tested to investigate the failure modes and compressive responses. The test results showed that the stiffened sections achieved significantly higher compressive strength with delayed local buckling failure compared to the unstiffened counterparts. Tensile coupons were extracted from flat, corner and curve portions of the steel tubes in order to determine the corresponding material properties. Finite element (FE) models were established to numerically simulate the tested stub columns, in which both failure modes and load-end shortening curves could well replicate the test results. Parametric studies were then implemented using the validated FE model to extend the dataset. The obtained test and numerical results were used to assess the applicability of existing design standards and methods. It was found that EC3, ANSI/AISC 360-22, AS 4100 and Direct Strength Method (DSM) could be safely adopted in cross-section classifications and cross-section capacity predictions.

A new nanoindentation approach for determining both indentation size effect and continuous apparent activation volume during loading of nanocrystalline Ni and Ni-20 wt.% Fe alloy

A new nanoindentation approach is developed in this study to determine both indentation size effect (ISE) and continuous apparent activation volume () during loading of nanocrystalline nickel (NC Ni) and nanocrystalline nickel-20 wt.% iron alloy (NC Ni-Fe alloy). This approach involves conducting nanoindentation tests under loading modes controlled by both constant strain rate (CSR) and constant loading rate (CLR). Firstly, a new empirical expression for the parameter in the modified Nix-Gao model is established to study the strain rate dependence of the ISEs created in the CSR and CLR tests. Then, continuous data of each individual sample (indentation) during loading are obtained in the CLR test through the alternative use of continuous stiffness measurement technique. The stress dependence of is analyzed based on Duhamel et al.’s model, which considers the role of vacancies generated during inhomogeneous dislocation nucleation. Finally, based on the above experimental and theoretical work as well as transmission electron microscopy observation, the influences of loading mode, loading rate, and material properties (stacking fault energy) on resulting intrinsic hardness of NC Ni and NC Ni-Fe alloy are analyzed. The nanoindentation approach developed in this study provides profound insights into the mechanical behaviors during loading and underlying mechanisms of materials.

Copper based high temperature heat storage macrocapsules with optimized inner cavity

The development of practical high temperature metallic phase change macrocapsules still faces difficulties, because metallic phase change materials undergo volume expansion during phase transformations, which can lead to outer shell rupture. When a core made of stacked metal powders is used, a cavity is eventually formed inside the capsule that acts as a cushion for volume expansion, thus reducing the risk of capsule rupture. However, the cavity will weaken the thermal storage capacity of the capsule, and in order to obtain a capsule with good thermal storage capacity and long-time cycling stability, it is necessary to find a suitable cavity volume of the capsule. In this paper, Cu powders are used as the core raw material, which are spherelized into millimeter level spheres, and the Cu powder spheres are isostatically pressed using an isostatic presser under different pressures to achieve the optimization of the cavity volume by reducing the gap between the powders. The high strength α-Al2O3 is selected as the shell, and sintering additives MgO and SiO2 are doped into the raw material, and the Cu@MgO-SiO2/Al2O3 capsules are prepared after two-step sintering treatment. The material properties and thermal storage properties of the capsules are investigated in detail, which have strong thermal storage properties, for example, in the temperature interval of 1000-1100 ℃, capsules with a core-shell structure (named as 9@1.5-100MPa, prepared with initial diameter of Cu core of 9mm, shell thickness of 1.5mm, and isostatic pressing under 100MPa to the core precursor) exhibit a high heat storage density of 222J/g and 841 MJ/m³. In addition, we conduct melting-solidification cycle tests, which confirms the excellent durability of the capsules. The comprehensive results show that the Cu@MgO-SiO2/Al2O3 macrocapsules possess strong thermal storage capacity and can be used as effective thermal storage materials, especially in advanced high temperature thermal storage systems.

Contact Antibacterial and Biocompatible Polymeric, Composite with Copper Zeolite Filler and Copper Oxide, Nanoparticles: A Step Towards New Raw Materials for the Biomedical Industry

This paper introduces a simple procedure for developing composite materials with antibacterial and biocompatible properties using polylactic acid (PLA) and polypropylene (PP). These composites incorporate three variants of zeolites in different percentages as filler agents: pure zeolite (PZ), copper ion-saturated zeolite (LZ), and copper-ion-saturated zeolite with copper oxide nanoparticles (LZ-nCu). The composites were prepared by the extrusion method and manufactured by injection molding. The impact of these zeolites on various material properties was evaluated, including morphology, thermal stability, mechanical properties, antibacterial capacity, biocompatibility, water absorption, and chemical resistance. The results demonstrated that (i) the incorporation of zeolite into the PP matrix improved thermal stability and increased the tensile modulus of the composites. For PLA-based composites, although there was a slight decrease in these values compared to pure PLA, they remained within acceptable ranges; (ii) zeolite LZ and LZnCu composites at 5 and 10% by weight effectively inhibited the growth of Gram-positive and Gram-negative bacteria within a maximum of 2 hours of contact; and (iii) composites containing 10% by weight of PZ, LZ, or LZ-nCu showed reduced mechanical properties due to a tendency to form agglomerates. Additionally, LZ and LZ-nCu composites with the same percentage proved highly toxic to human gingival fibroblast cells (HGFs). PLA/LZ-nCu at 5% and PP/LZ at 5% composites exhibited antibacterial properties with bactericidal effects upon contact, high biocompatibility, and lower water absorption compared to the pure polymeric matrix. These results highlight the operational effectiveness of the procedure and suggest the potential of these composites in biomedical applications, such as in vitro dentistry, without contamination risks.

A parameterized modeling method for analyzing welding residual stress in orthotropic steel deck

This paper presents a new parameterized method for establishing OSD models and analyzing WRS, and two plugins are developed based on the graphical user interface (GUI) of Abaqus. This parameterized method addresses the extremely high cost of manual modeling of OSD in Abaqus. In the two presented plugins, the OSD dimensions and welds size, the material properties, the welding heating source, and the mesh properties are parameterized, and the OSD model can be created automatically by the plugins without users’ pre-processing operations in Abaqus, which significantly facilitates the OSD modeling and the WRS analysis. The plugins developed in this study can provide the WRS analysis in the OSD with any dimensions and welding technologies, and the applicability of the plugins is verified by the consistency between the simulated WRS analysis results by plugins and those reported in the literature.

Powder dosing within continuous manufacturing: A lean approach for gravimetric dosing configuration and equipment selection

This work presents a novel approach to select gravimetric dosing configurations for continuous unit operations in pharmaceutical processing. It optimizes material, time, and personnel use, and allows selections for configurations of materials not included in the model by robust material attribute-based interpolation. The approach does not apply Principal Component Analysis (PCA) and Partial Least Squares (PLS). Instead, a reduced set of material attributes that require measurement was determined from existing material attribute libraries found in literature. Only those identified 17 attributes were measured for 13 materials and employed in this study. The established model proved to be predictive for an even further reduced attribute set of 12 attributes. The model introduces a simplified method for selecting feeding equipment combining precision metrics (relative mean intra-bin variability) and model parameters (fmax, fmin, beta). The reduction of Material Attributes (MAs) in this short-cut method enables fast evaluation and enhances resource efficiency by incorporating only a few selected MAs into the model and therefore introduces a different line of thinking. It was also possible to compare feeding of different hopper geometries, showing that flat bottom-hoppers have higher dosing precision than round bottom-hoppers. In conclusion, this work introduces a smart and innovative model that simplifies the equipment selection process and brings objectivity through a comprehensive numerical description of the discharge characteristics, and provides new options for continuous dosing in pharma through combining precision and curve fitting parameters.

Nitrogen-doped modified graphene aerogel enhancing interfacial bonding with lithium aluminium silicate ceramics for broadband microwave absorption

The swift progression of e-communication technology has resulted in significant electromagnetic pollution, necessitating the urgent need for effective microwave-absorbing materials to mitigate this issue. Augmenting heterogeneous phase interfaces and incorporating heteroatoms constitute viable strategies for enhancing the electromagnetic properties of functional materials. In this study, a series of lithium aluminium silicate glass-ceramic/nitrogen-doped graphene (LAS/N-GF) aerogels was synthesised via the hydrothermal and freeze-drying methods. An innovative bonding mechanism for the heterogeneous phase interface was revealed, in which nitrogen doping enabled the formation of lattice defects in LAS ceramic particles and graphene and promoted a closed approach for unsaturated carbon and silicon atoms to form carbon-silicon bonds through the electrostatic force generated by interfacial polarisation. Given that covalent bonds are widely recognized as stable carrier channels, the presence of carbon-silicon bonds at the interface facilitates electron migration, ultimately leading to improved microwave absorption. The maximum absorptivity of the LAS/N-GF aerogels could reach -47.98 dB at 8.96 GHz with a filler loading as low as 10 wt.%. It is noteworthy that the LAS/N-GF aerogel exhibits an effective absorption bandwidth of 8.34 GHz, which fully spans the entire X-band and more than two-thirds of the Ku-band. Such exceptional performance is rarely observed in dielectric loss materials. Finally, the application potential of the LAS/N-GF aerogels in microwave absorbers was simulated and analysed. The unique chemical phenomenon stemming from the bonding at the carbon material-ceramic interface offers a fresh perspective in interface science, enabling a deeper comprehension of the underlying mechanism of microwave absorption.

Resonant spin dynamics of 2D electrons with strong Rashba and Zeeman couplings

Two-dimensional (2D) systems enable enhancing and diversifying the spin–orbit coupling of carriers, a key factor for better charge-spin conversion efficiencies in modern spintronic devices. Increasing 2D spin interactions also modifies dynamical spin-dependent properties of 2D materials, enabling to display resonant phenomena. In this work we focus on dynamical properties of the charge-spin conversion and analyze the resonant spin dynamics of 2D electrons upon strong spin–orbit coupling and Zeeman spin splittings, possibly exceeding the inverse relaxation times of electrons. We derive resonant frequencies and relaxation rates from the Bloch kinetic equations and examine how the trajectories of spin susceptibility poles change with variations in spin splittings and the relaxation time, paying special attention to the interplay between competing Rashba and Zeeman effect.

Multichannel Analysis of Surface Waves based on Common Virtual Source Gathers of Seismic Ambient Noise Cross-Correlations: A Case Study at an Earth Dam in Brazil

The S-wave velocity (Vs) is a valuable parameter for assessing the mechanical properties of subsurface materials for geotechnical purposes. Seismic surface wave methods have become prominent for estimating near-surface Vs models. Researchers have proposed methods based on passive seismic signals as efficient alternatives to enhance depth of investigation, lateral resolution and reduce field effort. This study presents the Multichannel Analysis of Surface Waves (MASW) utilizing Common Virtual Source Gathers (CVSGs) derived from seismic ambient noise cross-correlations, based on Ambient Noise Seismic Interferometry concepts. The method is applied to passive data acquired with an array of receivers at the Paranoá earth dam in Brasília, Brazil, to construct a pseudo-2D Vs image of the massif for interpretation. Our findings showcase the adopted processing flow and combination of methods as an effective approach for near-surface Vs estimation, demonstrating its usability also for large earth dam embankments.