Material Related Parameters Research Articles

Towards implementation of alloy-specific thermo-fluid modelling for laser powder-bed fusion of Mg alloys

Multi-physics thermo-fluid modeling has been extensively used as an approach to understand melt pool dynamics and defect formation as well as optimizing the process-related parameters of laser powder-bed fusion (L-PBF). However, its capabilities for being implemented as a reliable tool for material design, where minor changes in material-related parameters must be accurately captured, is still in question. In the present research, first, a thermo-fluid computational fluid dynamics (CFD) model is developed and validated against experimental data. Considering the predicted material properties of the pure Mg and commercial ZK60 and WE43 Mg alloys, parametric studies are done attempting to elucidate how the difference in some of the material properties, i.e., saturated vapor pressure, viscosity, and solidification range, can influence the melt pool dynamics. It is found that a higher saturated vapor pressure, associated with the ZK60 alloy, leads to a deeper unstable keyhole, increasing the keyhole-induced porosity and evaporation mass loss. Higher viscosity and wider solidification range can increase the non-uniformity of temperature and velocity distribution on the keyhole walls, resulting in increased keyhole instability and formation of defects. Finally, the WE43 alloy showed the best behavior in terms of defect formation and evaporation mass loss, providing theoretical support to the extensive use of this alloy in L-PBF. In summary, this study suggests an approach to investigate the effect of materials-related parameters on L-PBF melting and solidification, which can be extremely helpful for future design of new alloys suitable for L-PBF.

Numerical analysis of field aging in asphalt pavements via coupling of diffusion process and kinetics aging model

The asphalt aging model is a crucial module in the Mechanistic-Empirical (ME) pavement design programme for asphalt pavement performance prediction. In this study, an analytical aging model that couples diffusion and kinetics aging model (CDKAM) is improved to analyze and predict the field aging of asphalt pavements. The complex modulus (E*) of field cores was used as the aging property to illustrate the derivation of explicit expressions of time-averaged thermal source term ( TST ¯ ( t ) ) and time-averaged diffusion coefficient ( D ¯ ( t ) ). The value of the material-related parameter (M) in TST ¯ ( t ) model differs among different mixtures, which could assess the mixture’s susceptibility to thermal oxidation. The CDKAM with TST ¯ ( t ) and D ¯ ( t ) was used to predict E* of field aging for asphalt pavements in Texas after 22-month service life. The calibrated CDKAM could reasonably quantify the aging extent over time and the aging gradient over depth for studied asphalt pavements.

Characterization of Hot Deformation Behavior and Processing Maps Based on Murty Criterion of SAE8620RH Gear Steel

The hot deformation behavior and microstructure evolution of the SAE8620RH gear steel were investigated through a single-pass hot compression test at deformation temperatures between 850 and 1100 °C and strain rates between 0.02 and 8.0 s−1 by 60% reduction. A novel strain compensation constitutive model was developed, and the 2D processing maps were established by Murty’s criterion. Results showed that the relationship between material-related parameters and strain can be mathematically expressed by a highly reliable 8th-order polynomial. The constructed strain compensation constitutive model demonstrated remarkable predictive precision, as evidenced by the correlation coefficient (R) and the absolute values of average relative error (AARE) of 0.978 and 4%, respectively. The flow instability domains considerably expanded towards the high deformation temperature region as the strain increased. Microstructure analysis confirmed the accuracy of the processing map constructed by Murty’s criterion. The most noticeable optimum processing windows for SAE8620RH gear steel at a strain of 0.7 occurred within the temperature range of 1000–1100 °C and the strain rate range of 0.3–1.0 s−1, due to high η values exceeding 0.3 and equiaxial dynamic recrystallization microstructure.

Simulation of the effect of material properties on yttrium oxide memristor-based artificial neural networks

This paper reports a simulation study concerning the effect of yttrium oxide stoichiometry on output features of a memristor-based single layer perceptron neural network. To carry out this investigation, a material-oriented behavioral compact model for bipolar-type memristive devices was developed and tested. The model is written for the SPICE (Simulation Program with Integrated Circuits Emphasis) simulator and considers as one of its inputs a measure of the oxygen flow used during the deposition of the switching layer. After a thorough statistical calibration of the model parameters using experimental current–voltage characteristics associated with different fabrication conditions, the corresponding curves were simulated and the results were compared with the original data. In this way, the average switching behavior of the structures (low and high current states, set and reset voltages, etc.) as a function of the oxygen content can be forecasted. In a subsequent phase, the collective response of the devices when used in a neural network was investigated in terms of the output features of the network (mainly power dissipation and power efficiency). The role played by parasitic elements, such as the line resistance and the read voltage influence on the inference accuracy, was also explored. Since a similar strategy can be applied to any other material-related fabrication parameter, the proposed approach opens up a new dimension for circuit designers, as the behavior of complex circuits employing devices with specific characteristics can be realistically assessed before fabrication.

Analytical Study on Reinforced Concrete Columns and Composite Columns under Lateral Impact

This study investigates the lateral impact responses of reinforced concrete (RC) and composite columns through dynamic nonlinear analysis using LS-DYNA. The simulation results were first validated against experimental results performed earlier on four different cross sections. The finite element analysis results show that the simulation results of LS-DYNA can predict the experimental results well and can be used for further parametric analysis. The overall impact resistance of the four new composite columns is significantly better than that of RC columns. Among the composite columns, the solid concrete-filled double steel tube (S-DS) column has the best impact resistance with higher impact plateau force and smaller mid-span deflection under the same test conditions. It was found that the impact response process of all types of composite columns was similar. Finally, parametric analysis of the composite columns is performed to study the influence of load, material and other related parameters on the impact response of the composite columns. The results provide new information on the impact response of composite columns and the influence of materials and load parameters. The study provides a basis for the design and analysis of composite columns under lateral impact loading.

Tailored Polyelectrolyte Multilayer Systems by Variation of Polyelectrolyte Composition and EDC/NHS Cross-Linking: Controlled Drug Release vs. Drug Reservoir Capabilities and Cellular Response for Improved Osseointegration.

Polyelectrolyte multilayers (PEM) are versatile tools used to investigate fundamental interactions between material-related parameters and the resulting performance in stem cell differentiation, respectively, in bone tissue engineering. In the present study, we investigate the suitability of PEMs with a varying collagen content for use as drug carriers for the human bone morphogenetic protein 2 (rhBMP-2). We use three different PEM systems consisting either of the positively charged poly-L-lysine or the glycoprotein collagen type I and the negatively charged glycosaminoglycan heparin. For a specific modification of the loading capacity and the release kinetics, the PEMs were stepwise cross-linked before loading with cytokine. We demonstrate the possibility of immobilizing significant amounts of rhBMP-2 in all multilayer systems and to specifically tune its release via cross-linking. Furthermore, we prove that the drug release of rhBMP-2 plays only a minor role in the differentiation of osteoprogenitor cells. We find a significantly higher influence of the immobilized rhBMP-2 within the collagen-rich coatings that obviously represent an excellent mimicry of the native extracellular matrix. The cytokine immobilized in its bioactive form was able to achieve an increase in orders of magnitude both in the early stages of differentiation and in late calcification compared to the unloaded layers.

Prediction of welded joint fatigue properties based on a novel hybrid SPDTRS-CS-ANN method

This paper proposes a prediction model of welded joint fatigue properties based on single-parameter decision-theoretic rough set (SPDTRS)-cuckoo search (CS)-artificial neural network (ANN) hybrid algorithm. To establish the fatigue performance database of EH36 steel, the preprocessing and data cleaning are carried out by analytic hierarchy process (AHP) and box-plot method to obtain reliable fatigue properties prediction. Therein, the SPDTRS theory is used to analyze the weight of fatigue properties influencing factors, the CS algorithm is used to avoid the over-fitting and local optimization of ANN. During process, the influencing factors are regarded as input and the material related parameters C and m are conducted as output to realize the fatigue properties prediction, which improves the accuracy and stability of the present prediction method. According to the comparisons between the experimental and predicted results, it is found that the predicted S-N curves are within ± 1.1 error band of the experimental results, the average error of fatigue life is less than 10%, and can be within ± 1.2 error band. As a result, the fatigue properties prediction model reasonably shows the fatigue properties of welded structures, and provides a certain reference for fatigue design of welded structures.

Exploiting spring-back differences for joining and pre-stressing sheet metal structures with tendons during forming – A mathematical-physical process model

Pre-stressing enables slender and high-strength structures in civil engineering. Previous studies have shown that it also offers a high potential for lightweight design of load-bearing sheet metal structures. Here, it is not only possible to join the sheet metal structures with the necessary tendons during a forming process, but also to pre-stress them at the same time. However, a targeted application of this technology requires a comprehensive understanding of the process mechanisms as well as calculation methods enabling an efficient structure and process design. To achieve this, the present article describes an analytical model of the underlying process mechanisms during the elastic-plastic forming process as well as the creation of the pre-stressing force acting between tendon and metal structure after spring-back. It is then transferred to two application-oriented processes. Numerical parameter studies serve the validation of these models and the further comprehension of additional process phenomena. It is shown that only a few geometrical, material and process related parameters are required to accurately calculate the pre-stressing force with a deviation of mostly less than 10 % from the numerical results.

Understanding synaptic characteristics of nonvolatile analog redox transistor based on mobile ion-modulated-electrolyte thickness model for neuromorphic applications

Linear and symmetric updates of the channel current of the redox transistor are involved in bulk mobile ion motion. In this study, we introduce the concept of a variable effective electrolyte thickness (teff) precisely tuned by gate voltage-driven ions into the drain current equation of a conventional transistor. In order to understand the switching characteristics of a nonvolatile analog redox transistor that serves as an artificial synapse for neuromorphic systems, we developed a physics-based model in MATLAB. The simulated synaptic update curves obtained using identical gate pulses were in good agreement with the fabricated Cu-ion-actuated CuOx/HfOx/WOx redox transistor. We then analyzed the impact of geometrical and material-related parameters on the synaptic behavior, taking into account the ion speed and the degree of allowable electric field through the electrolyte. In addition, we performed Monte Carlo simulation to create a non-uniformly changed teff circumstance. With this, we reproduced the fluctuated update of the channel current every gate pulse, which is occasionally observed experimentally when mobile ions are easily moved randomly. Our simulation results revealed that the redox transistor immune to the unevenly changed teff can be achieved by lowering the ion velocity.

Effect of electrode/dielectric interface on energy storage performance of BaZr0.35Ti0.65O3 film capacitors

In this work, correlative parameters of the interfacial layer adjacent to an electrode in BaZr0.35Ti0.65O3 (BZT) films, including the thickness of an interface layer (δ), the effective charge density (Neff) in a depleted layer, and other material related parameters, were evaluated. To the 145 nm-thick BZT films on different bottom electrodes, the sample with thick δ and large Neff behaved with slim P–E loops (efficiency >85.0%) and a desirable energy density of 42.1 J/cm3. While in the bulk effect dominated 300 nm-thick BZT films, a much high energy density of 83.5 J/cm3 with an efficiency of 80.5% was achieved. These suggest that the energy storage properties can be modulated through the control of the structure of the electrode/BZT interface and the film thickness.

A Theory-Guided Deep Neural Network for Time Domain Electromagnetic Simulation and Inversion Using a Differentiable Programming Platform

In this communication, a trainable theory-guided recurrent neural network (RNN) equivalent to the finite-difference-time-domain (FDTD) method is exploited to formulate electromagnetic propagation, solve Maxwell’s equations, and the inverse problem on differentiable programming platform Pytorch. For forward modeling, the computation efficiency is substantially improved compared to conventional FDTD implemented on MATLAB. Gradient computation becomes more precise and faster than the traditional finite difference method benefiting from the accurate and efficient automatic differentiation on the differentiable programming platform. Moreover, by setting the trainable weights of RNN as the material-related parameters, an inverse problem can be solved by training the network. Numerical results demonstrate the effectiveness and efficiency of the method for forward and inverse electromagnetic modeling.

Design of adhesively bonded lap joints with laminated CFRP adherends: Review, challenges and new opportunities for aerospace structures

Adhesive bonding is one of the most suitable joining technologies in terms of weight and mechanical performance for current carbon fiber reinforced polymer aircraft fuselage structures. However, traditional joint topologies such as single overlap joints induce high peel stresses, resulting in sudden failure and low joint strength when compared to metal adherends. This drawback in using carbon fiber reinforced polymer is hindering their performance and efficiency in full-scale structures where joints are essential.The goal of this paper is to review how the joint design can help to improve the lap shear strength of composite bonded joints, to recognize the challenges that still need to be understood and to give insight into new opportunities. The focus is thereby on means to increase the matrix-dominated out-of-plane strength of the adherend in order to postpone delamination failure, as it is known to be the most prone type of failure of composite bonded joints. The paper is divided in two main parts: firstly, a review of topology-related and material-related design parameters is given and secondly, future opportunities to improve out-of-plane strength of CFRP bonded joints yet to be explored are discussed.

Multidisciplinary topology optimization incorporating process-structure-property-performance relationship of additive manufacturing

Multidisciplinary topology optimization (TO) for additive manufacturing (AM) exhibits unprecedented design and manufacturing freedom as an effective lightweight methodology. In order to fully utilize the AM advantages of materialized arrangement in spatial and voxel-by-voxel digitalized printing, multidisciplinary TO for AM requires a full understanding of the process-structure-property-performance (PSPP) relationship to establish the quantitative correlation of part property and multiple process factors, including laser-, process-, and material-related parameters. This study incorporates the PSPP relationships of laser sintered material with topology optimizer so as to provide a guideline for TO collaborative AM design. The proposed workflow involves mapping functions of PSPP relationships via a data-driven approach and then optimizes the multiple process parameters and structural topology by the gradient-based algorithm. Compared with conventional optimization approaches, three case-dependent optimizations demonstrate the effectiveness of the proposed approach yielding encouraging improvements of lightweight performance. The multidisciplinary TO can be generally applied to types of AM technologies, establishing a strong linkage of physical product and digital design.

Modeling of Al and Ga Droplet Nucleation during Droplet Epitaxy or Droplet Etching.

The temperature dependent density of Al and Ga droplets deposited on AlGaAs with molecular beam epitaxy is studied theoretically. Such droplets are important for applications in quantum information technology and can be functionalized e.g., by droplet epitaxy or droplet etching for the self-assembled generation of quantum emitters. After an estimation based on a scaling analysis, the droplet densities are simulated using first a mean-field rate model and second a kinetic Monte Carlo (KMC) simulation basing on an atomistic representation of the mobile adatoms. The modeling of droplet nucleation with a very high surface activity of the adatoms and ultra-low droplet densities down to 5 × 10 cm is highly demanding in particular for the KMC simulation. Both models consider two material related model parameters, the energy barrier for surface diffusion of free adatoms and the energy barrier for escape of atoms from droplets. The rate model quantitatively reproduces the droplet densities with = 0.19 eV, = 1.71 eV for Al droplets and = 0.115 eV for Ga droplets. For Ga, the values of are temperature dependent indicating the relevance of additional processes. Interestingly, the critical nucleus size depends on deposition time, which conflicts with the assumptions of the scaling model. Using a multiscale KMC algorithm to substantially shorten the computation times, Al droplets up to 460 °C on a 7500 × 7500 simulation field and Ga droplets up to 550 °C are simulated. The results show a very good agreement with the experiments using = 0.19 eV, = 1.44 eV for Al, and = 0.115 eV, = 1.24 eV ( 300 °C) or = 1.24 + 0.06 (T[°C] − 300)/100 eV ( °C) for Ga. The deviating is attributed to a re-nucleation effect that is not considered in the mean-field assumption of the rate model.

The Use of Simulated Body Fluid (SBF) for Assessing Materials Bioactivity in the Context of Tissue Engineering: Review and Challenges.

Some special implantable materials are defined as “bioactive” if they can bond to living bone, forming a tight and chemically-stable interface. This property, which is inherent to some glass compositions, or can be induced by applying appropriate surface treatments on otherwise bio-inert metals, can be evaluated in vitro by immersion studies in simulated body fluid (SBF), mimicking the composition of human plasma. As a result, apatite coating may form on the material surface, and the presence of this bone-like “biomimetic skin” is considered predictive of bone-bonding ability in vivo. This review article summarizes the story and evolution of in vitro bioactivity testing methods using SBF, highlighting the influence of testing parameters (e.g., formulation and circulation of the solution) and material-related parameters (e.g., composition, geometry, texture). Suggestions for future methodological refinements are also provided at the end of the paper.

Consolidated results of the laboratory and full scale field validation of an active flap system

This article presents the consolidated results of a comprehensive validation campaign of a pneumatic active flap system (AFS) developed within the scope of the Induflap2 project [1] in a collaboration effort between Siemens Gamesa Renewable Energy A/S (SGRE), the Technical University of Denmark (DTU), and Rehau GmbH. The validation results presented herein include wind tunnel measurements, measurements in a rotating test rig under free atmospheric conditions, as well as the validation at full scale on a 4MW wind turbine with 130m rotor diameter (SWT-4.0-130). This article is of a summarizing character and the reader is referred to further literature where applicable. During the course of the project, several revisions of the AFS were developed and tested at different levels of fidelity. Along with the different variations of the AFS, the impact of variations of the geometric and material related design parameters were studied. Two of the latest revisions of the AFS were tested at full scale on a wind turbine. The measurements presented herein focus solely on the latest revision of the AFS (internally referred to as the FT008rev10 concept). The different tests and measurements were performed in the period from 2016 to 2019. During the full scale measurements, a wind speed dependent load impact between 5% and 10% was measured for the blade root flapwise bending moments, demonstrating thus a large potential for turbine loading adjustments to perform active load control on modern wind turbines.

Fatigue of clothoid shaped rib shear connectors

Rib shear connectors can be used in steel and concrete composite structures in which conventional shear connectors reach their limits. Especially in the field of bridge construction widely used shear connectors such as headed studs often exhibit insufficient fatigue strength due to the welded connection of the studs to the steel beam. In such structures, innovative rib shear connectors can be used to transfer longitudinal shear forces in the interface between steel and concrete. In order to take full advantage of the better load bearing behaviour of these innovative shear connectors under cyclic loading, new experimental investigations have been conducted aiming to clarify the circumstances under which fatigue failure occurs in the shear connection. The influence of load- as well as material-related parameters on the fatigue behaviour of the shear connectors was systematically analysed. The results of the performed investigations show that high upper load levels mainly influence failure related with concrete fatigue, while high load ranges have great impact on steel fatigue. Furthermore, the occurring slip in the interface of steel and concrete in case of cyclic pry-out failure was found to correlate with the static deformation capacity of the rib shear connectors.

A universal law for predicting the motion behaviors of skyrmions under spatially-varying strain field

As topologically protected particle-like magnetization configurations, magnetic skyrmions are promising carriers for information storage and processing. However, the inevitable strain field, probably induced in micro-nano manufacture process, could limit their practical applications. Here, we theoretically demonstrate a universal law governing the motion behavior of a single skyrmion under the influence of a spatially-varying strain field without other external fields. We elucidate that its motion is perpendicular to the spatial distribution of the strain field, and that the velocity obeys the quantitative relationship v=χFsε, where χ is the material-related parameter and Fsε=∫my∂yεmydxdy is the driving force induced by the strain field. Based on this theoretical framework, we propose two typical racetrack configurations with the weaken skyrmion Hall effect, presenting themotion along the longitudinal direction in a lateral field and the rotation around the center of racetrack in a radial field. Our findings open a door for understanding the inherent relationship between strain field and skyrmions and provide a basic idea to manipulate skyrmions in the presence of strain field.

Analytic solutions for calculating the surface inclination of isotropic media and bare substrates by using reflection-based generalized ellipsometry

Using ellipsometry for curved-surface characterization requires the knowledge of the surface normal vector in order to determine material-related surface parameters like refractive index, layer thickness, or birefringence of the surface material at the incidence point, because the recorded signal depends on both the (unknown) surface normal vector n→ and material-related surface characteristics. It is convenient in ellipsometry to parametrize the surface normal vector by the angle of incidence θ and the azimuthal rotation angle ϕ. Depending on the design of the ellipsometer, there may be two angles, ϕ1 and ϕ2, necessary, which describe the azimuthal rotation before and after the light is reflected off the sample, respectively. The authors present analytic formulas to determine ϕ1 and ϕ2 for optically isotropic samples using generalized ellipsometry. The resulting measurement uncertainty is lower than that of previously known methods. Furthermore, the authors provide an analytic formula to calculate θ from the ellipsometric angles Ψ and Δ for bare substrates with known refractive index N1=n1−ik1. The formulas have been evaluated with experimental data acquired with a conventional and an imaging retroreflection-based return-path ellipsometer.

Progress of multiscale materials crystallization

The generation of physical properties and energy conversion takes place in materials, and material crystallization is the core of new material creation and frontier direction of exploration. Multi-scale material crystallization is a common scientific challenge faced by researchers in many fields. Material crystallization models are based on corresponding phase diagrams such that the material composition and related physical and chemical parameters can be determined and combined with material crystallization theory and growth methods to realize material crystallization. In this paper, the main theories from nucleation to growth and crystallization growth methods of some materials are reviewed; research on material crystallization is developing toward multi-scale, multi-factor, and quantification. Material crystallization equipment is progressing toward automation, digitalization, and intelligentization. Material crystallization studies focus on multi-scale phase evolution, including the mass and energy transfer process from nucleation to growth that requires the coordinated collaboration of multidisciplinary fields.