Wudil, Y. S.Peng, Q.Alsayoud, A. Q.Gondal, M. A....
6页
查看更多>>摘要：Pressure engineering is a conventional approach to modify the material's interatomic bond length, density, forces as well as other intrinsic properties. The effects of hydrostatic pressure on the electronic and thermoelectric properties of n-type halide perovskite CsSnI3 have been investigated using first-principles approach with spin-orbit coupling included. Electronic structure analysis illustrates that the material is a direct gap semiconductor. The partial charge density calculation suggested that electrons from Cs atoms do not contribute to the valence bonding instead assist in balancing the overall charge distribution. The material's bandgap decreases with applied pressure up to 1.7 Gpa, where band inversion was observed, after which further compression widened the energy gap. Accompanying with Boltzmann's theory, it was shown that CsSnI3 is a potential candidate for thermoelectric energy harvesting. Hence, materials modification through pressure application is an effective approach to tune the electronic structure and thermoelectric properties of CsSnI3. We achieved the optimum ZT of 1.26 at 1 Gpa pressure and 600 K temperature, close the band inversion region.
查看更多>>摘要：This work reexamines the insertion of O atoms in the L1(0) gamma-TiAl system using first-principles calculations and thermodynamic modeling in the independent point defect approximation. It includes a study of intrinsic point defects, the insertion of many alloying elements (more than twenty were considered), as well as a study of their interaction with oxygen. The formation of complex defects composed of either vacancies, anti-sites or solute elements is then studied. Results at the atomic scale show a high segregation of oxygen in titanium-rich environments: oxygen easily segregates onto Ti anti-sites (Ti-Al) and alloying elements are located in the vicinity of Al sub-lattices. DFT point-defect energetics shows that there is a clear correlation between the nature and site preference of an alloying element, and the oxygen segregation energy in the vicinity of this solute. The thermodynamic model shows that at equilibrium, oxygen does not occupy isolated interstitial sites but prefers to be located in the vicinity of Ti anti-sites or alloying elements. The effect of this strong segregation on oxygen diffusivity is discussed hereinafter. Results show a strong slowdown in oxygen diffusivity due to intrinsic defects. For Ti/Al > 0.5 ratios, the traps for O diffusion are mainly constituted by Ti anti-sites, and the addition of solutes does not contribute much to the trapping of diffusing O atoms. For Ti/Al < 0.5 ratios however, the contribution of solutes to trapping phenomena can be very important, and a decrease by 1-2 orders of magnitude of effective O diffusion coefficients can be observed for temperatures around 800-1100 K.
查看更多>>摘要：This paper focuses on the roughness evolution and surface topography variation of constrained surface, which is restricted by the mold or tool in the forming process. A crystal plasticity finite element model, which couples the microstructure of polycrystalline, the crystal plasticity constitutive model and the real surface topography of the material, is developed. How to use the real surface of the workpiece as the surface topography of the finite element model is proposed, in which number and location of peaks and valleys on the surface, are accurately captured in the constructed real surface model. The comparison shows that simulation predictions of both the deformed surface topography and the surface roughness agree reasonably well with experimental measurements at various press down ratio of mold. The influences from workpiece and mold on the roughness evolution of constrained surface are comprehensively analyzed. It can be seen clearly that roughness evolution of constrained surface is the combination result of both the surface flattening due to the mold restriction and the surface roughening due to the material inhomogeneity of the workpiece. The lubricant existing in the contact surface of the workpiece and mold should been paid much more attention in the roughness evolution analysis. The influence of the lubrication condition on the roughness evolution of constrained surface is analyzed by combining the CEL finite element method and compression experiments. In deformation stage II of the roughness evolution, the closed cavities begin to form on the surface. Lubricant in the closed cavities plays an important role in limiting the flattening behavior of the surface topography. This paper provides a deeper insight into the comprehensive understanding of the roughness evolution of constrained surface, which contributes to the surface roughness control of plastic deformation products considering the effects of the workpiece, mold and lubrication condition.
查看更多>>摘要：Strengthening in complex multicomponent systems such as solid solution alloys is controlled primarily by the dynamic interactions between dislocation lines and heterogeneously distributed solute species. Modeling of extended defect length scales in such multicomponent systems becomes prohibitively expensive, motivating the development of reduced order approaches. This work explores the application of the Concurrent AtomisticContinuum (CAC) method to model dislocation mobility in random alloys at extended length scales. By employing recently developed average-atom interatomic potentials, the average "bulk" material response in coarse-grained regions interacts with true random solute species in the atomistic-scale domain. We demonstrate that spurious stresses in domain resolution transition regions are eliminated entirely due to the CAC formulation. Simultaneously, the key details of local stress fluctuation due to randomness in the dislocation core region are captured, and fluctuating stress smoothly decays to the long-range dislocation stress field response. Dislocation mobility calculations, for line lengths over 400 nm, are computed as a function of alloy composition in the model FeNiCr system and compared to full molecular dynamics (MD). The results capture the composition-dependent trends, while reducing degrees of freedom by nearly 40%. This approach can be readily extended to any system described by an EAM potential and facilitates the study of large-scale defect dynamics in complex solute environments to support computational alloy design.
查看更多>>摘要：Shear stress relaxation through the motion of multiple edge dislocations in a periodic cell is studied by molecular dynamics and discrete dislocation methods. In both methods, we consider systems with an initial edge dislocation on the parallel slip planes. The initial shear strain is applied to the system along the Burgers vector of the dislocations. The velocity profile for a single edge dislocation fitted from a molecular dynamics (Bryukhanov, 2020) is used as the input to discrete dislocation dynamics. The dependence of shear stress, plastic strain, and plastic strain rate on time are analyzed. We show that when dislocations are sufficiently far from each other, relaxation occurs due to dislocation motion, and dislocation velocity can exceed the anisotropic speed of sound. If the dislocations are closer together, relaxation is due to the growth of stacking faults. We find that the stress at which the stress relaxation mechanism changes decreases with increasing dislocation density. Stress relaxation in a Cu-Ni solid solution occurs faster than in pure Cu due to a higher dislocation velocity in the high-velocity regime. However, the shear stress at which nickel atoms increase the plastic strain rate increases with an increase in dislocation density. The dependence of the relaxation time on the dislocation density obtained in discrete dislocation simulations is approximated using the power law. The elastic interaction between dislocations reduces the exponent of the power law from 1/rho to approximately 1/rho(0.8) for both pure Cu and Cu-Ni solid solutions.
Zahiri, Amir HassanCarneiro, LuizOmbogo, JamieChakraborty, Pranay...
8页
查看更多>>摘要：{10 (1) over bar2} twinning occurs extensively in Mg to accommodate plastic deformation. With multiple active twin variants, twin-twin interaction occurs and this often forms twin-twin boundaries. In this work, the {11 (2) over bar2} twin-twin boundary is studied using electron backscatter diffraction (EBSD) analysis and atomistic simulations. EBSD data show that many of the twin-twin boundaries align well with {11 (2) over bar2} or {11 (2) over bar6} planes. Further, atomistic simulations reveal dynamically the formation of {11 (2) over bar2} boundary via the interaction of two non-cozone {10 (1) over bar2} twin variants. Moreover, the twinning mode of the {11 (2) over bar2} boundary is found to be an extension twin with second undistorted plane of {11 (2) over bar6}. In addition, the {11 (2) over bar2} boundaries contribute significantly to the 60 degrees < 01 (1) over bar0 > peak in the misorientation histogram; they also play an essential role in the unique strong strain hardening under c-axis tension. Our findings are crucial for completing the twinning theories for Mg.
查看更多>>摘要：In this paper, interfacial and elastic properties of polymer-based nanocomposites reinforced by carbon nanocones (CNCs) are investigated. The CNCs are transitional structures from graphene to carbon nanotubes and, depending on their apex angles, show either more graphene or more nanotube behavior. Due to the importance of the interphase layer and its impact on the elastic properties of nanocomposites, the molecular dynamics method is used to investigate the behavior of polyethylene polymer in the interface of the CNCs. The MD simulation results reveal that there are two distinct interphase layers, i. e. the inner interphase region inside the CNCs and the outer interphase region outside the CNCs. While the outer interphase regions are the same in all cases, the size and properties of the inner interphase depend on the geometries of CNCs. Using the results of MD simulations, the finite element method is used to simulate CNC-reinforced polyethylene nanocomposites in larger dimensions. In finite element modeling, the effects of different orientations of nanofillers, various volume fractions, and geometrical parameters of the CNCs are studied.
查看更多>>摘要：Practicing two-dimensional semiconductor compounds as a photocatalyst could be a common way for watersplitting since the existence of the photogenerated holes-electron is greater than that within the 3D compounds. In any case, when the unique 2D semiconductor is utilized as a photocatalyst for the water-splitting, whole the photogenerated electron-holes will appear at the surface for the oxidation and decrease responses, individually, and they will confine every other on the corresponding surface. Subsequently, building the 2D vdW heterostructure can move forward this issue by isolating the photogenerated holes-electron at diverse sheets for the hydrogen advancement response and oxygen advancement response to break down water. In this framework, we investigate the 2D vdW GaSe/AlN and GaSe/ZnO heterostructures employing density functional theory. Our predictions show that the four stacking buildings all contain weak and the interface binding energies are negative, which implies that their interlayer couplings have a place in the vdW interaction and their arrangements are energetically favorable. Further, for GaSe/AlN vdW heterostructures characterized by type II band structure, showing the ability to continuously separate holes and electrons photogenerated. However, GaSe/ZnO vdW heterostructures are of type I band alignment. We have found that the vdW forces separating the interface of the heterostructure, which implies the heterostructure is designed by vdW synergy preferably of covalent bond. Moreover, band edge positions of GaSe, AlN, ZnO, and GaSe/AlN(ZnO) heterostructures satisfy the demand for the redox reactions of water splitting at pH= 0.
Garcia-Carrillo, MiguelEspinoza-Martinez, Adriana B.Ramos-de Valle, Luis F.Sanchez-Valdes, Saul...
9页
查看更多>>摘要：Prediction and achievement of, simultaneously, the highest thermal and lowest electrical conductivity in polymer composites prior to their manufacturing is of great interest to avoid excessive experimentation and to achieve the best material performance for diverse applications. However, traditional modeling and optimization methods are not effective due to the non-linear complex behavior of both properties in polymer composites. In this study, two artificial neural networks (ANN) were developed with the aim of approximate the thermal conductivity and the electrical conductivity of high density polyethylene (HDPE)-carbon particle composites, based on data obtained experimentally. Composites were prepared by twin-screw extrusion using four different types of carbon particles at different concentrations. The obtained ANN models were used as objective functions in a multi-objective genetic algorithm (GA) to optimize the design parameters of the composites to maximize their thermal conductivity and minimize their electrical conductivity. ANN models showed a good correlation between simulated and experimental data, evidenced by correlation factors, R, above 0.97. Multi-layer perceptron ANN with three neurons in a single hidden layer and trained by the Levenberg-Marquardt algorithm exhibited the best predictive performance in both models. As a result of the multi-objective optimization process by GA, a set of Pareto optimal solutions for maximizing thermal conductivity and minimizing electrical conductivity was obtained. Conformity tests were performed to validate the optimization capability of the GA method. The optimization and modeling procedure developed can be applied to other properties of polymer composites.
Elapolu, Mohan S. R.Shishir, Md. Imrul RezaTabarraei, Alireza
14页
查看更多>>摘要：A machine learning model is proposed to predict the brittle fracture of polycrystalline graphene under tensile loading. The model employs a convolutional neural network, bidirectional recurrent neural network, and fully connected layer to process the spatial and sequential features. The spatial features are grain orientations and location of grain boundaries whereas sequential features are associated with the crack growth. Molecular dynamics modeling is used to obtain the fracture process in pre-cracked polycrystalline graphene sheet subjected to tensile loading. The data from molecular dynamic simulations along with novel image-processing techniques are used to prepare the data set required to train and test the proposed model. Crack growth obtained from the machine learning model shows a close agreement with the molecular dynamic simulations. The proposed machine learning model predicts crack growth instantaneously avoiding the computational costs associated with molecular dynamics simulations.
NSTL
Elsevier