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Sodium Prussian blue (SPB) with a cubic structure was successfully synthesized by a simple precipitation method in a hot acidic medium. Scanning electron microscopy images showed that the as-prepared SPB consisted of many microcubic structures with different morphologies and sizes because of the tailoring of its surface morphology by etching. The Fourier-transform infrared spectroscopy and energy-dispersive X-ray spectroscopy results indicated the existence of interstitial water and the replacement of Na+ ions by H+ ions in the SPB material. In addition, when used as a sodium-ion battery (SIB) cathode, the as-prepared SPB showed significantly different electrochemical behaviors in two different alkyl carbonate electrolytes (ethylene carbonate and propylene carbonate with 2% fluoroethylene carbonate electrolyte (EC-PC-2% FEC) and PC-2% FEC electrolyte). The results showed that in the PC-2% FEC electrolyte, the as-prepared SPB showed excellent rate capability and cycle stability, and hence was found to be a promising SIB cathode material.

Cantor-type high entropy alloys form a new family of metallic alloys characterised by a combination of high strength and high fracture toughness. An experimental study on the CoCrNi alloy is first performed to determine the damage and fracture mechanisms under various stress states. A micromechanics-based ductile fracture model is identified and validated using these experimental data. The model corresponds to a hyperelastic finite strain multi-yield surface constitutive description coupled with multiple nonlocal variables. The yield surfaces consist of three distinct nonlocal solutions corresponding to three different modes of void expansion within an elastoplastic matrix: a void growth mode governed by a Gurson-based yield surface corrected for shear effects, an internal necking-driven coalescence mode governed by an extension of the Thomason yield surface based on the maximum principal stress, and a shear-driven coalescence mode governed by the maximum shear stress. This advanced formulation embedded in large strain finite element setup captures the effects not only of the stress triaxiality but also of the Lode variable. In particular, the analysis shows that a failure model accounting for these two invariants of the stress tensor captures the fracture in high-entropy alloys over a wide range of conditions.

We propose a micro-mechanical numerical model able to predict the nonlinear behavior and failure of unidirectional fiber reinforced high-crosslinked epoxy subjected to transverse loading conditions. Statistical microstructural volume elements (SMVE) of a realistic composite material are generated from the statistical characterization of the fibers distribution and fiber radius estimated from SEM images of a similar material system. The fibers are assumed to be transversely hyperelastic isotropic and the matrix obeys a hyperelastic viscoelastic–viscoplastic constitutive model enhanced by a multi-mechanism nonlocal damage model. This polymer model captures the pressure dependency and strain rate effects. Besides, it also accounts for size effects through its internal length scales, allowing capturing, with the same unique set of parameters, the behaviors of the epoxy as pure material as well as matrix phase in composites, which are experimentally observed to be different. Additionally, since fiber/matrix interfaces of the considered composite material are categorized as strong ones, the true underlying failure mechanism is located in the matrix close to the fibers, and the interface does not need to be explicitly introduced in the model. The model prediction is found to be in good agreement with experimental results in terms of the global nonlinear stress–strain curves over various strain rates and pressure conditions, on the one hand for pure matrix samples, and on the other hand for the composite coupons, making the proposed framework a predictive virtual testing facility for material design. Finally, using this model, we study the localization behavior in order to characterize the post-failure behavior of the composite material: the cohesive strength is given by the stress–strain curve peak stress while the critical energy release rate is estimated by evaluating the dissipated energy accumulated during the post-peak localization stage. Finally, different SMVE realizations are considered allowing assessing the discrepancy in the failure characteristics of composites.

An inverse Mean-Field Homogenization (MFH) process is developed to improve the computational efficiency of non-linear stochastic multiscale analyzes by relying on a micro-mechanics model. First full-field simulations of composite Stochastic Volume Element (SVE) realizations are performed to characterize the homogenized stochastic behavior. The uncertainties observed in the non-linear homogenized response, which result from the uncertainties of their micro-structures, are then translated to an incremental-secant MFH formulation by defining the MFH input parameters as random effective properties. These effective input parameters, which correspond to the micro-structure geometrical information and to the material phases model parameters, are identified by conducting an inverse analysis from the full-field homogenized responses. Compared to the direct finite element analyzes on SVEs, the resulting stochastic MFH process reduces not only the computational cost, but also the order of uncertain parameters in the composite micro-structures, leading to a stochastic Mean-Field Reduced Order Model (MF-ROM). A data-driven stochastic model is then built in order to generate the random effective properties under the form of a random field used as entry for the stochastic MF-ROM embedded in a Stochastic Finite Element Method (SFEM). The two cases of elastic Unidirectional (UD) fibers embedded in an elasto-plastic matrix and of elastic UD fibers embedded in a damage-enhanced elasto-plastic matrix are successively considered. In order to illustrate the capabilities of the method, the stochastic response of a ply is studied under transverse loading condition.

A material network consisting of discrete material nodes and their interactions can represent complex microstructure responses. Under this interaction viewpoint, the material network can be viewed as a trainable system involving fitting parameters including not only the weights of the material nodes but also the parameters characterizing their interactions. As opposed to the other existing works, this interaction-based material network does not rely on the micromechanics of multiple-phase laminates but on constraining all requirements of a truly microscopic boundary value problem including the stress and strain averaging principles and the Hill–Mandel energetically consistent condition. Consequently, the proposed framework can be applied to microstructures with the presence of voids, which is not achievable with the laminate theory. To make a material network become a surrogate of a full-field microscopic model , this work proposes two different training procedures to calibrate its fitting parameters. On the one hand, a nonlinear training procedure is proposed considering sequential data collected from finite element simulations on the full-field model subjected to proportional loading paths. On the other hand, a linear elastic training procedure considers only the elastic response of the heterogeneous material. The accuracy and efficiency of the proposed framework for microstructures with the presence of voids are demonstrated by comparing the predictions of the trained material networks with the ones of the direct numerical simulations in both contexts of virtual testing and multiscale simulations. It is also shown that the linear elastic training procedure requires a lower computational cost but could lead to less accurate predictions in comparison with the nonlinear training procedure.

A material network consists of discrete material nodes, which, when interacting, can represent complex microstructure responses. In this work, we investigate this concept of material networks under the viewpoint of the hierarchical network interactions. Within this viewpoint, the response of the material network is governed by a well-defined system of equations and an arbitrary number of phases can be considered, independently of the network architecture. The predictive capability is achieved by, on the one hand, sufficiently deep and rich network interactions to tie the discrete material nodes together, and, on the other hand, an efficient offline training procedure. For this purpose, a unified and efficient framework for an arbitrary network architecture is developed, not only for the offline training, but also for the online evaluation. The efficiency and prediction accuracy of the material network as a surrogate of a homogenization-based multiscale model in predicting the stress–strain response in both contexts of a virtual test and of FE 2 multiscale simulations are demonstrated through numerical examples with two-phase and three-phase fiber-reinforced composites.

The COVID-19 pandemic is considered a global disaster that affects all areas of the world; however, it is also seen as a motivation for domestic and foreign scientists to focus on researching solutions to reduce its damage. This article aims to explore the correlation of scientific publications of countries in Southeast Asia, among research fields in Vietnam and among topics published by Vietnamese educational institutions in the context of a pandemic. 1392 Southeast Asian countries’ publications related to COVID-19 were referenced from the Scopus database, including 123 articles from Vietnam (up to August 27th, 2020). Statistics show that Vietnam ranks fifth in the number of scientific publications with research cooperation of researchers from 20 different countries. Regarding the research fields of Vietnam, pharmacy is the main research topic, social science ranks third following environmental science. In the field of social science, articles focus on four key topics: epidemic prevention, reduction of pandemic effects on life and socioeconomics, factors related to online learning of students, healthcare for the elderly. From the analysis results, the authors recommend that researchers should pay attention to other topics in the social sciences that have not been published, such as psychological effects of infected or suspected nCovi, the impact of COVID-19 to disadvantaged groups in society.

The ductile fracture behavior of a high strength steel is addressed in this two-part study using a micromechanics-based approach. The objective of Part II is to propose, identify, and validate a numerical model of ductile fracture based on the Gurson–Tvergaard–Needleman model. This model is enhanced by the Nahshon–Hutchinson shear modification in combination with a generalization of the Thomason coalescence criterion within a fully nonlocal form and relying on a damage-to-crack transition technique. The material model involves parameters of different natures either related to the micro-mechanics of porous materials or to semi-empirical formalisms. The void nucleation model and elastoplastic behavior have been developed and identified in Part I. The other parameters are identified in this part using inverse modeling based on both the numerical results of void cell simulations and the experimental measurements. The model is shown to adequately predict the effect of stress triaxiality and Lode parameter on the fracture strain as well as the fracture anisotropy. While the cup-cone and slant fracture paths in the round bars and in the plane strain specimens, respectively, cannot be captured using the pure continuum approach, the damage-to-crack transition framework reproduces these experimental observations.

The aim of this work is to study the thermo-elastic quality factor (Q) of micro-resonators with a stochastic multi-scale approach. In the design of high-Q micro-resonators, thermo-elastic damping is one of the major dissipation mechanisms, which may have detrimental effects on the quality factor, and has to be predicted accurately. Since material uncertainties are inherent to and unavoidable in micro-electromechanical systems (MEMS), the effects of those variations have to be considered in the modeling in order to ensure the required MEMS performance. To this end, a coupled thermo-mechanical stochastic multi-scale approach is developed in this paper. Thermo-mechanical micro-models of polycrystalline materials are used to represent micro-structure realizations. A computational homogenization procedure is then applied on these statistical volume elements to obtain the stochastic characterizations of the elasticity, thermal expansion, and conductivity tensors at the meso-scale. Spatially correlated meso-scale random fields can thus be generated to represent the stochastic behavior of the homogenized material properties. Finally, the distribution of the thermo-elastic quality factor of MEMS resonators is studied through a stochastic finite element method using as input the generated stochastic random field.

A large strain hyperelastic phenomenological constitutive model is proposed to model the highly nonlinear, rate-dependent mechanical behavior of amorphous glassy polymers under isothermal conditions. A co-rotational formulation is used through the total Lagrange formalism. At small strains, the viscoelastic behavior is captured using the generalized Maxwell model. At large strains beyond a viscoelastic limit characterized by a pressure-sensitive yield function, which is extended from the Drucker-Prager one, a viscoplastic region follows. The viscoplastic flow is governed by a non-associated Perzyna-type flow rule incorporating this pressure-sensitive yield function and a quadratic flow potential in order to capture the volumetric deformation during the plastic process. The stress reduction phenomena arising from the post-peak plateau and during the failure stage are considered in the context of a continuum damage mechanics approach. The post-peak softening is modeled by an internal scalar, so-called softening variable, whose evolution is governed by a saturation law. When the softening variable is saturated, the rehardening stage is naturally obtained since the isotropic and kinematic hardening phenomena are still developing. Beyond the onset of failure characterized by a pressure-sensitive failure criterion, the damage process leading to the total failure is controlled by a second internal scalar, so-called failure variable. The final failure occurs when the failure variable reaches its critical value. To avoid the loss of solution uniqueness when dealing with the continuum damage mechanics formalism, a non-local implicit gradient formulation is used for both the softening and failure variables, leading to a multi-mechanism non-local damage continuum. The pressure sensitivity considered in both the yield and failure conditions allows for the distinction under compression and tension loading conditions. It is shown through experimental comparisons that the proposed constitutive model has the ability to capture the complex behavior of amorphous glassy polymers, including their failure.

The ductile fracture behavior of a high strength steel is investigated using a micromechanics-based approach with the objective to build a predictive framework for the fracture strain and crack propagation under different loading conditions. Part I of this study describes the experimental results and the determination of the elastoplastic behavior and damage nucleation under different stress triaxiality and Lode parameter values. The damage mechanism starts early void nucleation from elongated inclusions, either by particle cracking under loading oriented along the major axis, or by matrix decohesion when the main loading is transverse. Void nucleation is followed by plastic growth and coalescence. The long inclusion axis is preferentially aligned in one direction leading to significant failure anisotropy with the fracture strain in the transverse direction being almost 50% lower compared to the longitudinal one, even though the plastic behavior is isotropic. The experimental data are first used to calibrate the elastoplastic model. An enhanced anisotropic nucleation model is then developed and integrated into the Gurson–Tvergaard–Needleman scheme. The parameters identification of the anisotropic nucleation model is finally performed and validated towards the experimental results. All these elements are subsequently used in Part II to simulate the full failure behavior of all testing specimens in the entire spectrum of stress states, from nucleation to final failure.

The compressive behavior of nanocomposite foams is studied by both experimental and computational micro-mechanics approaches with the aim of providing an efficient computational model for this kind of material. The nanocomposites based on polypropylene (PP) and different contents of multi-walled carbon nanotubes (CNTs) are prepared by melt mixing method. The nanocomposite samples are foamed using super-critical carbon dioxide (ScCO2) as blowing agent at different soaking temperatures. The influence of this foaming parameter on the morphological characteristics of the foam micro-structure is discussed. Differential Scanning Calorimetry (DSC) measurements are used to quantify the crystallinity degree of both nanocomposites and foams showing that the crystallinity degree is reduced after the foaming process. This modification leads to mechanical properties of the foam cell walls that are different from the raw nanocomposite PP/CNTs material. Three-point bending tests are performed on the latter to measure the flexural modulus in terms of the crystallinity degree. Uniaxial compression tests are then performed on the foamed samples under quasi-static conditions in order to extract the macro-scale compressive response. Next, a two-level multi-scale approach is developed to model the behavior of the foamed nanocomposite material. On the one hand, the micro-mechanical properties of nanocomposite PP/CNTs cell walls are evaluated from a theoretical homogenization model accounting for the micro-structure of the semi-crystalline PP, for the degree of crystallinity, and for the CNT volume fraction. The applicability of this theoretical model is demonstrated via the comparison with experimental data from the described experimental measurements and from literature. On the other hand, the macroscopic behavior of the foamed material is evaluated using a computational micro-mechanics model using tetrakaidecahedron unit cells and periodic boundary conditions to estimate the homogenized properties. The unit cell is combined with several geometrical imperfections in order to capture the elastic collapse of the foamed material. The numerical results are compared to the experimental measurements and it is shown that the proposed unit cell computational micro-mechanics model can be used to estimate the homogenized behavior, including the linear and plateau regimes, of nanocomposite foams.

An advanced modeling framework is developed for predicting the failure of ductile ma- terials relying on micromechanics, physical ingredients, and robust numerical methods. The approach is based on a hyperelastic finite strain multi-surface constitutive model with multiple nonlocal variables. The three distinct nonlocal solutions for the expansion of voids embedded in an elastoplastic matrix are considered: a void growth phase governed by the Gurson–Tvergaard–Needleman yield surface, a void necking coalescence phase governed by a heuristic extension of the Thomason yield surface based on the maximum princi- pal stress, and a competing void shearing coalescence phase triggered by the maximum shear stress. The first solution considers the diffused plastic deformation around the voids while the last two solutions correspond to a state of plastic localization between neigh- boring voids. This combination captures the Lode variable and shear effects, which play important roles in dictating the damage evolution rates. The implicit nonlocal formulation with multiple nonlocal variables, including the volumetric and deviatoric parts of the plas- tic strain, and the mean equivalent plastic strain of the matrix, regularizes the problem of the loss of solution uniqueness when material softening occurs whatever the localization mechanism. The predictive capability of the proposed model is demonstrated through dif- ferent numerical simulations in which complex failure patterns such as slant and cup-cone of respectively plane strain and axisymmetric samples under tensile loading conditions de- velop.

The failure process of ductile porous materials is simulated by representing the damage nucleation, growth and coalescence stages up to crack initiation and propagation using a physically-based constitutive model. In particular, a non-local damage to crack transition framework is developed to predict the fracture under various loading conditions while minimising case-dependent calibration process. The formulation is based on a discontinuous Galerkin method, making it computationally efficient and scalable. The initial stable damage process is simulated using an implicit non-local Gurson-Tvergaard-Needleman (GTN) model ensuring solution uniqueness beyond the onset of softening. Once the coalescence criterion is satisfied, which can physically arise before or during the softening stage, a cohesive band is introduced. Within the cohesive band, a void coalescence-based governing law is solved, accounting for the stress triaxiality state and material history, in order to capture the near crack tip failure process in a micromechanically sound way. Two coalescence models are then successively considered and compared. First, with a view to model verification towards literature results, a numerical coalescence model detects crack initiation at loss of ellipticity of a local model, and the crack opening is governed by ad-hoc parameters of the GTN model. Alternatively, the Thomason criterion is used to detect crack nucleation during the softening stage while the Thomason coalescence model governs the crack opening process. This latter model is able to reproduce slant and cup-cone failure modes in plane-strain and axisymmetric specimens, respectively.

The aim of this work is to develop a stochastic multiscale model for polycrystalline materials, which accounts for the uncertainties in the micro-structure. At the finest scale, we model the micro-structure using a random Voronoi tessellation, each grain being assigned a random orientation. Then, we apply a computational homogenization procedure on statistical volume elements to obtain a stochastic characterization of the elasticity tensor at the meso-scale. A random field of the meso-scale elasticity tensor can thus be generated based on the information obtained from the SVE simulations. Finally, using a stochastic finite element method, these meso-scale uncertainties are propagated to the coarser scale. As an illustration we study the resonance frequencies of MEMS micro-beams made of poly-silicon materials, and we show that the stochastic multiscale approach predicts results in agreement with a Monte Carlo analysis applied directly on the fine finite-element model, i.e. with an explicit discretization of the grains.

We report the growth of ZnO nanorods on Si/SiO 2 subtrates by the thermal evaporation method at different distances (substrate temperatures) from vapor source to substrates. SEM images showed that morphologies of nanorods were significantly affected by distance from the substrate to vapor source. Energy dispersive X-ray spectroscopy (EDS) spectra present change of the ratio of zinc to oxygen in ZnO nanostructures as the substrate temperature varied. X-ray diffraction patterns revealed that the prepared ZnO nanorods are preferentially oriented in the c -axis at lower substrate temperature. The shift towards small angle of the XRD pattern peaks is consistent with the presence of the redundant zinc and the lack oxygen in the ZnO lattice. The photoluminescence (PL) spectra of the ZnO nanorods show beside the near band edge UV emission, a very broad emission ranges from green to near-infrared (NIR). The NIR emission is interpreted as due to the transition of carriers between radiative recombination centers related to Zn interstitials and oxygen interstitials.

When considering problems of dimensions close to the characteristic length of the material, the size effects can not be neglected and the classical (so-called first-order) multiscale computational homogenization scheme (FMCH) looses accuracy, motivating the use of a second-order multiscale computational homogenization (SMCH) scheme. This second-order scheme uses the classical continuum at the micro-scale while considering a second-order continuum at the macro-scale. Although the theoretical background of the second-order continuum is increasing, the implementation into a finite element code is not straightforward because of the lack of high-order continuity of the shape functions. In this work, we propose a SMCH scheme relying on the discontinuous Galerkin (DG) method at the macro-scale, which simplifies the implementation of the method. Indeed, the DG method is a generalization of weak formulations allowing for inter-element discontinuities either at the C 0 level or at the C 1 level, and it can thus be used to constrain weakly the C 1 continuity at the macro-scale. The C 0 continuity can be either weakly constrained by using the DG method or strongly constrained by using usual C 0 displacement-based finite elements. Therefore, two formulations can be used at the macro-scale: (i) the full-discontinuous Galerkin formulation (FDG) with weak C 0 and C 1 continuity enforcements, and (ii) the enriched discontinuous Galerkin formulation (EDG) with high-order term enrichment into the conventional C 0 finite element framework. The micro-problem is formulated in terms of standard equilibrium and periodic boundary conditions. A parallel implementation in three dimensions for non-linear finite deformation problems is developed, showing that the proposed method can be integrated into conventional finite element codes in a straightforward and efficient way.

In order to predict the effective properties of heterogeneous materials using the finite element approach, a boundary value problem (BVP) may be defined on a representative volume element (RVE) with appropriate boundary conditions, among which periodic boundary condition is the most efficient in terms of convergence rate. The classical method to impose the periodic boundary condition requires identical meshes on opposite RVE boundaries. This condition is not always easy to satisfy for arbitrary meshes. This work develops a new method based on polynomial interpolation that avoids the need of matching mesh condition on opposite RVE boundaries.

In the response to the demand for electrical energy, much effort aimed to develop and commercialize high temperature superconducting (HTS) power equipments has been made around the world. Especially, HTS transformer is one of the most promising devices. For the development of HTS transformer, the cryogenic insulation technology should be established. In this paper V − t characteristics of polyimide (Kapton) tape and GFRP used as turn-to-turn and structural insulations, respectively were studied. Moreover, breakdown hole site of GFRP after breakdown was also discussed. The experimental results show that the time to breakdown is conditioned on applied electric stress and the lifetime indices n of Kapton tape decrease slightly as the number of tape increases while the lifetime indices n of GFRP decrease strongly with increasing thickness. Furthermore, the breakdown holes of GFRP were not at the contact point, at which the electric field is maximum value, between sphere electrode and GFRP sample and its location depends on applied voltage as well as sphere diameter.