Combination Of Material Properties Research Articles

The Analysis of Impedance Spectra for Core–Shell Microstructures: Why a Multiformalism Approach is Essential

AbstractThe impedance response of a core–shell microstructure with 80% core volume fraction has been simulated using finite‐element modeling and compared to two equivalent circuits for a wide range of shell permittivity and conductivity values. Different equivalent circuits, corresponding to different variants of the well‐known brick layer model, are applicable for different combinations of material properties in the microstructure. When the shell has a similar conductivity or permittivity to the core, adding a parallel pathway increases the accuracy of the fit by ≈±10%. When both the conductivity and permittivity values of the core and shell regions are different the series circuit is a better fit. This is confirmed by multiformalism impedance analysis, which reveals features in the data that are not apparent using a single formalism. Finally, the conductivity and permittivity values for both the shell and core are extracted from the simulated spectra using all formalisms and compared to the original input values. The accuracy of the extracted values often depends on the impedance formalism used. It is concluded that impedance spectroscopy data must be analyzed using multiple formalisms when considering core–shell microstructures.

Bayesian Optimized Deep Convolutional Network for Electrochemical Drilling Process

Electrochemical machining is a promising non-traditional manufacturing process to make high-quality parts. The benefits of minimal thermally and mechanically induced stresses, free of burr, and a low surface roughness are appealing for industry and research institutes. However, the combined chemical reaction, electric field, fluid mechanics, and material properties involve a significant number of independent parameters which are difficult to analyze in order to draw comprehensive conclusions. To our current knowledge, process responses such as the material removal rate, optimal feed rate, and cutting profile cannot be represented accurately by analytical solutions. In recent years, deep learning has had tremendous success in analyzing sophisticated systems. The improved computation efficiency and reduced size of the training dataset required for deep learning have enabled various prediction models in the manufacturing industry. In this paper, a new approach is developed using the deep convolutional network with the Bayesian optimization algorithm to predict the diameters of the drilled hole from an electrochemical machining process. The Keras application programming interface (API) was used to build the deep convolutional network; the feed rate, pulse-on time, and voltage were used as input parameters to provide a fair comparison with a neural network from previous research. Random dropout layers were added to prevent overfitting of the network. Instead of tuning the network parameter by trial and error, the Bayesian parameter optimization algorithm was implemented to find the optimal set of parameters of the deep convolutional network that yields the minimum mean square error. The proposed algorithm was compared with a previously developed neural network with partially embedded physical knowledge. Improved training speed and accuracy were observed in comparison with the traditional neural network. The prediction model using the proposed deep learning algorithm demonstrated better prediction accuracy and provided a more systematic way to select the hyperparameter for the deep convolutional network.

Anti-erosion performance of asphalt pavement with a sub-base of cement-treated mixtures

In this paper, the factors that affect the anti-erosion performance of three grades of cement-treated mixtures and their degree of association were studied using the Baohan highway in the Qinba mountain area, China as an engineering example. Firstly, the principal factors that affected changes in the anti-erosion performance of cement-treated mixtures and its law were analyzed with self-development model testing, which is considering changes in the aggregate’s fractal dimension, compaction, cement dosage, curing age, water content, and cement strength grade in the mixtures. Secondly, the correlation coefficient between the influencing factors, scouring mass, and the predicted model for the cement-treated mixtures’ scouring mass were developed according to the Grey Theory. The results showed that the mixtures’ anti-erosion performance increased as cement content, strength, and curing age increased. Further, their anti-erosion performance increased firstly and then weakened with increased water content and compaction. In comparing cement-treated mixtures with suspended dense and skeleton voids, the former’s scouring resistance was better. Among all these factors, the mixtures’ structural type affected its erosion resistance greatly, while the cement strength grade had little effect. The cement-treated mixtures’ scouring mass prediction model was established by combining material properties and external environmental factors, which can provide a reference for the design and construction of highways’ base and subgrade in similar areas.

A Novel In Situ Experiment to Investigate Wear Mechanisms in Biomaterials

A number of experimental techniques have been used to characterize the mechanical properties and wear of biomaterials, from nanoindentation to scratch to atomic force microscopy testing. While all these experiments provide valuable information on the mechanics and functionality of biomaterials (e.g., animals’ teeth), they lack the ability to combine the measurement of force and sliding velocities with high resolution imaging of the processes taking place at the biomaterial-substrate interface. Here we present an experiment for the in situ scanning electron microscopy characterization of the mechanics of friction and wear of biomaterials with simultaneous control of mechanical and kinematic variables. To illustrate the experimental methodology, we report the wear of the sea urchin tooth, which exhibits a unique combination of architecture and material properties tailored to withstand abrasion loads in different directions. By quantifying contact conditions and changes in the tooth tip geometry, we show that the developed methodology provides a versatile and promising tool to investigate wear mechanisms in a variety of animal teeth accounting for microscale effects.

A novel design toolkit to assess asphalt-rubber gap-graded mixture performance: Target properties and parametric relationships

This study evaluated the performance of asphalt-rubber gap-graded (AR-Gap) mixtures under various test conditions and established a novel design toolkit that was proficient to rank the mixtures, which helped recommend the best performing material. A total of 28 asphalt mixtures, including, one dense-graded and 27 AR-Gap mixtures were considered. Euclidean distance approach was utilized to determine the best AR-Gap mixture based on ten pavement material design parameters. It is envisaged that this toolkit will help researchers and practitioners to prioritize the desired combinations of asphalt mixture materials properties, thereby assisting in selection of best performing pavement system for field implementation.

Bistability in thermomechanical metamaterials structured as three-dimensional composite tetrahedra

The letter begins with the thermomechanical model of a three degree-of-freedom tetrahedral unit cell subject to cycles of heating and cooling. Geometric nonlinearity, mechanical constraint and dissimilar material properties of thermoelastic elements lead to a build-up of thermally-driven stored strain energy as dictated by the thermomechanical potential. For certain geometric configurations and combinations of material properties in the composite structure, the solution bifurcates at a critical thermal load causing a discontinuous buckling or ‘pop-through’ of the interior triad. Interestingly, if the pop-through action coincides with an abrupt inward displacement of the tetrahedral vertices then the effective volume of the unit cell shrinks. The phenomenon is termed negative ‘intermittent’ volumetric thermal expansion. In total, six types of thermal load–response curves are identified. By systematic nonlinear analysis of the thermomechanical potential, the stability diagram and phase diagram pinpoint the locations of bifurcations, cusps and features that mark a shifts in hysteretic behavior. The diagrams map the thermomechanical response to the design of the unit cell. A region is identified in the phase diagram corresponding to the sets of design parameters that lead to the metamaterial response.

A holistic inverse approach based on a multi-objective function optimisation model to recover elastic-plastic properties of materials from the depth-sensing indentation test

Recent years have seen an increased interest in the mechanical characterisation of materials via the inverse analysis of depth-sensing indentation data; however, at low-loads both the reaction forces measured by the instrument and the contact evolution at the indenter-material interface may be severely affected by indentation size effects (ISEs). Notwithstanding the knowledge of ISE, the inverse analyses proposed to date have failed to investigate the divergence between the small-scale properties measured via indentation and the large-scale properties extracted from other techniques, e.g. tensile testing. Therefore, this study investigates the sensitivity of an inverse analysis methodology to the indentation size in relation to the size of the microstructure. The proposed inverse analysis approach is based on a multi-objective function (MOF) optimisation model that finds the combination of material properties (Young's modulus, yield stress and strain-hardening exponent) that provides the best fit to both the experimental load-displacement (P-h) curve extracted from the indentation instrument and pile-up profile of the residual imprint measured with an atomic force microscope. Therefore, the piling-up/sinking-in effect, which is strongly linked to the plastic hardening behaviour of the indented material, is considered to address the non-uniqueness issue of the inverse analysis of indentation. A Berkovich indenter was used to measure the near surface properties of three different materials, including a titanium alloy (Ti-6Al-4 V), chromium-molybdenum-vanadium steel (CrMoV) and high purity copper (C110); materials have been selected to represent a wide range of ductile metallic materials so as to assess the generality of the MOF model.

On the emergence of negative effective density and modulus in 2-phase phononic crystals

In this paper we report metamaterial properties including negative and singular effective properties for what would traditionally be considered non locally resonant 2-phase phononic unit cells. The negative effective material properties reported here occur well below the homogenization limit and are, therefore, acceptable descriptions of overall behavior. The material property combinations which make this possible were first revealed by a novel level set based topology optimization process which we describe. The optimization process revealed that a 2-phase unit cell in which one of the phases is simultaneously lighter and stiffer than the other results in dynamic behavior which has all the attendant characteristics of a locally resonant composite including negative effective properties far below the homogenization limit. We investigate this further using the Craig–Bampton decomposition and clarify that these properties emerge through an interplay between the fundamental internal modeshape of the unit cell and a rigid body mode. Through explicit numerical calculations on 1-D, 2-phase unit cells, we show that negative effective properties only appear for the specific material property combination mentioned above. Furthermore, we provide a proof which supports this conclusion. The concept is also shown to hold for 2-D unit cells where we show that an appropriately designed hexagonal unit cell made of 2 material phases exhibits negative effective shear modulus and density in an appropriate frequency regime in which it also exhibits negative refraction. As in the 1-D case, we show that the homogenized description in the 2-D case is rigorous as well. An important conclusion of this paper is that the class of unit cells expected to result in negative properties can be expanded beyond the classic unit cell (three-phase unit cells with an explicit locally resonant phase) to include topologically simpler 2-phase unit cells as well.

Learning from nature: Use material architecture to break the performance tradeoffs

In material science, the enhancement of a specific material performance is often accompanied by undermining another material property, notoriously known as the performance tradeoffs, such as that between strength and toughness, stiffness and energy dissipation, and flexibility and fast response. Free combinations of material properties that go beyond these performance tradeoffs are highly desirable in areas as diverse as civil engineering, soft robotics, armor designs, and reconfigurable metamaterials. Learning from nature, we 3D print architected materials with bio-inspired microstructures that successfully surpass the above performance tradeoffs. The integration of microstructural elements on multiple length scales (hierarchical designs) and on one specific length scale (hybrid designs) are further discussed and compared. Through experimental and theoretical analysis, we reveal that the performance enhancements stem from the material architecture's significant manipulation over the deformation field, crack location, and crack pattern. This study on the relationship between material microstructure and material performance will aid architected material design with ideal combinations of mechanical properties.

Remarkable thermoelectric performance in BaPdS2 via pudding-mold band structure, band convergence, and ultralow lattice thermal conductivity

Efficient thermoelectric materials require a rare and contraindicated combination of materials properties: large electrical conductivity, large Seebeck coefficient, and low thermal conductivity. One strategy to achieve the first two properties is via low-energy electronic bands containing both flat and dispersive parts in different regions of crystal momentum space, known as a pudding-mold band structure. Here, we illustrate that ${\mathrm{BaPdS}}_{2}$ successfully achieves the pudding-mold band structure for the valence band, contributing to a large $p$-type thermoelectric power factor, due to its anisotropic crystal structure containing zigzag chains of edge-sharing square planar ${\mathrm{PdS}}_{4}$ units; large power factor is achieved for $n$-type doping as well due to band convergence. In addition, ${\mathrm{BaPdS}}_{2}$ exhibits ultralow lattice thermal conductivity, and thus also achieves the third property, due to extremely soft and anharmonic interactions in its transverse acoustic phonon branch. We predict a remarkably large thermoelectric figure of merit, with peak values between 2 and 3 for two of the three crystallographic directions, suggesting ${\mathrm{BaPdS}}_{2}$ warrants experimental investigation.

Arising Student Consciousness Regarding Structural Properties of Natural Materials with a Structural Challenge Employing Arundo Donax

All our actions claim now sustainable choices, and radical changes in materials need to be made. In this perspective there is the awareness that nature can help to provide viable solutions. In particular, the choice of natural materials for structures, perfectly optimized by the structural point of view, can be made. In this paper an experimental teaching experience regarding the structural behaviour of Arundo Donaxreed, made in a Structural course of Design of the Industrial Product of the University of Bologna, is reported. Arundo Donax has been firstly characterized from the mechanical point of view and then used in a structural challenge focusing on the best use of a given quantity of reed for a “bridge type structure” with fixed span and width. The main goals of the course were, on one hand (with mechanical characterization of Arundo), to give students sensitiveness on strength and stiffness of the material, on the other (with the structural challenge) were to make the student think about the combination of material properties and shape of constructions to reach the best structural performances.

Improving the R&D process efficiency of the selective laser sintering industry through numerical thermal modeling

CITATION: Olivier, C. M., Oosthuizen, G. A. & Sacks, N. 2019. Improving the R&D process efficiency of the selective laser sintering industry through numerical thermal modeling. Procedia Manufacturing, 33:131-138, doi:10.1016/j.promfg.2019.04.017.

Application of three-dimensional shakedown solutions in railway structure under multiple Hertz loads

Shakedown analysis is a robust approach to solve the strength problem of a structure under cyclic or repeated loading, e.g. railway structure subjects to rolling and sliding loads. A three-dimensional analytical shakedown solution is developed in this paper for the strength analysis of cohesive-frictional materials under multiple Hertz loads, which is then applied into the shakedown analysis of railway structure. Different to the pavement, the railway structure subjects to multiple wheel loads acting on the surface of two parallel rails, and then transformed to the substructure, which leads to different elastic and residual stress fields. For the application of Melan's shakedown theorem, the residual stress field in railway strucuture is rationally simplified to find the most critical plane that influence the most on the shakedown limit. The elastic stresses is then analytically derived for a single layer half-space under multiple Hertz loads, and is obtained numerically by means of the finite element technique for the multi-layered railway structure. Finally, the shakedown limit can be obtained in a direct way. Parametric study indicates how wheel loads, material properties such as frictional coefficient, friction angle and Poisson's ratio, and multi-layers influence the shakedown limit and stability condition of railway structure. It is found that the shakedown load increases with the increase of cohesion ratio, ballast frictional angle, and thickness ratio. However, the increase of the shakedown load ceases once the failure location moves from ballast layers to sub-ballast layers. This indicates that there is an optimum combination of material properties and layer thickness which provides the maximum resistance to the train loads. The obtained results give a useful reference for the engineering design of the railway structure.

Coaxially-structured fibres with tailored material properties for vascular graft implant

Readily-available small-diameter arterial grafts require a great combination of materials properties, including high strength, compliance, suturability, blood sealing and anti-thrombogenicity, as well as anti-kinking property for those used in challenging anatomical situations. We have constructed grafts composed of coaxially-structured polycaprolactone (PCL)/gelatin nanofibres, and tailored the material structures to achieve high strength, compliance and kink resistance, as well as excellent water sealing and anti-thrombogenicity. Coaxially-structured fibres in the grafts provided mechanical stability through the core, while flexibility and cell adhesion through the sheath. Results showed that graft compliance increased while strength decreased with the concentration ratio between core and sheath polymers. Compared to pure PCL fibrous surfaces, coaxial PCL/gelatin fibrous surfaces potently inhibited platelet adhesion and activation, providing excellent anti-thrombogenicity. To render sufficient burst strength and suturability, an additional layer of pure PCL was necessary to cap the layer of coaxial PCL/gelatin fibres. The two-layered grafts with the wall thickness comparable to native arteries demonstrated artery-like compliance and kink resistance, properties important to arteries under complex mechanical loading. The in vivo evaluation was performed using the interposition carotid artery graft model in rabbits for three months. Interestingly, results from ultrasonic imaging and histological analysis demonstrated that the two-layered grafts with a thinner outer PCL layer, which possessed higher compliance and kink resistance, showed increased blood flow, minimal lumen reduction and fibrosis. All vascular grafts exhibited patency and induced limited cell infiltration. Together, we presented a facile and useful approach to fabricate vascular grafts with superior graft performances, biomechanical properties, and blood compatibility. Grafts with artery-like compliance and flexibility have demonstrated improved implantation outcomes.

Biological composites-complex structures for functional diversity.

The bulk of Earth's biological materials consist of few base substances-essentially proteins, polysaccharides, and minerals-that assemble into large varieties of structures. Multifunctionality arises naturally from this structural complexity: An example is the combination of rigidity and flexibility in protein-based teeth of the squid sucker ring. Other examples are time-delayed actuation in plant seed pods triggered by environmental signals, such as fire and water, and surface nanostructures that combine light manipulation with mechanical protection or water repellency. Bioinspired engineering transfers some of these structural principles into technically more relevant base materials to obtain new, often unexpected combinations of material properties. Less appreciated is the huge potential of using bioinspired structural complexity to avoid unnecessary chemical diversity, enabling easier recycling and, thus, a more sustainable materials economy.

Concentration dependent properties lead to plastic ratcheting in thin island electrodes on substrate under cyclic charging and discharging

It is known that the mechanical properties of electrodes in lithium-ion batteries, such as modulus, yield stress, and interfacial strength, can depend strongly on lithium concentration. Here we show that a thin film island electrode with properties dependent on lithium concentration naturally undergoes plastic ratcheting with accumulative deformation and failure during cyclic charging and discharging. Some key predictions from numerical simulations are validated by galvanostatic tests. Strategies to avoid ratcheting include limiting the electrode size and/or selecting a balanced combination of concentration dependent materials properties.

Effect of grain size and magnetic texture on iron-loss components in NO electrical steel at different frequencies

The magnetic properties of non-grain-oriented (NO) electrical steels are a direct product of their inherent material properties in combination with induced changes due to material processing and external operational conditions such as magnetization and frequency. Chemical composition, grain size and texture are elementary intrinsic factors which determine the magnetic properties. Focus of this study is to improve the understanding of grain size and texture as important factors that affect different loss-components. A strong focus is placed on the frequency dependence and concurrent loss component distribution over application relevant frequency ranges of electrical machines. Due to its impact on the eddy current losses as well as the hysteresis components, the final thickness is additional subject of this study. A total of seven materials are produced on an experimental production line from one alloy. By different production and processing steps, different grain structures, textures and final thickness are achieved. The changes in the materials are attributed to the process variations and magnetically characterized. A loss separation procedure as well as loss modeling is performed and discussed. This work is part of a research field which aims to improve parametric models with low additional computational effort for the numerical simulation of electrical machines. The goal is to improve the accuracy of models with a deeper understanding of the material science.

Electrochemical-mechanical modeling of solid polymer electrolytes: Impact of mechanical stresses on Li-ion battery performance

We analyze the effects of mechanical stresses arising in a solid polymer electrolyte (SPE) on the electrochemical performance of the electrolyte component of a lithium ion battery. The SPE is modeled with a coupled ionic conduction-deformation model that allows to investigate the effect of mechanical stresses induced by the redistribution of ions. The analytical solution is determined for a uniform planar cell operating under galvanostatic conditions with and without externally induced deformations. The roles of the polymer stiffness, internally-induced stresses, and thickness of the SPE layer are investigated. The results show that the predictions of the coupled model can strongly deviate from those obtained with an electrochemical model—up to +38% in terms of electrostatic potential difference across the electrolyte layer—depending on the combination of material properties and geometrical features. The predicted stress level in the SPE is considerable as it exceeds the threshold experimentally detected for irreversible deformation or fracture to occur in cells not subjected to external loading. We show that stresses induced by external solicitations can reduce the concentration gradient of ions across the electrolyte thickness and prevent salt depletion at the electrode-electrolyte interface.

Novel Pyrolyzed Carbon Processing for Advanced Microelectronic Applications

Sandia National Laboratories has developed an ability to fabricate multilayered, all carbon MEMS devices, complete with future mixed material signal routing. Carbon is a durable and adaptable material, suitable for many microelectronics applications and can be micromachined from blanket films, enabling a production scalable fabrication process. Silicon based MEMS systems have dominated the market for 20+ years of development, with supplemental effort leveraging the IC industry. Carbon as a standalone material and silicon with carbon offer unique combinations of material properties which complement future design space for harsh environments [Figure 1]. It can withstand high temperatures, and can also be tuned for specific performance characteristics by incorporating nanoparticles, effectively manipulating resistivity, Young’s modulus and Poisson’s ratio. Carbon is highly conductive, inexpensive, and easy to produce. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525. The views expressed in the article do not necessarily represent the views of the U.S. Department of Energy or the United States Government. Figure 1

(Plenary) 4D Printing for Sensors and Energy Applications

Sustained advances in 3D printing techniques have resulted in the emergence of 4D printing that incorporates additional dimension where stimuli-responsive smart materials change the shape of the printed structure. Unlike the 3D printed structures, a 4D printed structure evolves as a function of time. The mechanical and structural properties of a 4D printed structure can be pre-programmed using a combination of material properties and computational modeling. We have shown that it is possible to print structures that are electrically conducting. This electrically conducting structure can be transformed under physical stimuli into an active circuit element. Such circuit elements can be the basis for transferring electrical power using single contact, single conductor concept for powering sensors. Stimuli dependent shape can be used for tuning the electrical resonance of single conductor electrical transmission. This single conductor, single contact power delivery also offers opportunities for imbedded sensors in 3D and 4D printed structures. It is also possible to use similar 4D printed structures for developing tunable structures for target analyte pre-concentrators for enhancing the sensitivity of sensors. These 4D printed structures will have myriads of applications in chemical sensing. Our recent results will be presented. We will also address the challenges and opportunities for their future applications.