查看更多>>摘要：Geopolymer is a new green and environmental friendly building material. However, its preparation process involves so many variables that there is no complete and standardized preparation method so far. In this work, back propagation neural network (BPNN) was used to forecast the slump and compressive strength of composite geopolymers with its high precision and engineering applicability, the prediction results of BPNN were also compared with random forest (RF) and k nearest neighbors (KNN) algorithm model. To train the BPNN models, a total of 191 data sets were used, which collected from different researchers in the open literature, and ten input parameters were considered, then 29 data sets were randomly selected by computer to verify that the error of the model is within the acceptable range. The BPNN model was run by Matlab, and the determination coefficient of determination (R) has been used for investigating the proposed model accuracy. As a result, the R values of the BPNN model for prediction slump and compressive strength are 0.9394; the R values of the RF model for prediction slump and compressive strength are 0.9017 and 0.9274, respectively; and the R values of the KNN model for prediction slump and compressive strength are 0.9121 and 0.9059, respectively. Those results show the performance of the BPNN model was better than the latter two models to estimate the strength and slump, it can be considered that the BPNN has the advantages of high accuracy, high efficiency and strong promotion ability in the prediction of composite geopolymers.
查看更多>>摘要：Materials with symmetry protected nodal loops is accompanied by many exotic features, i.e., the presence of drumhead surface states. In addition, the crystallographic symmetries can determine the shape of the nodal loops. Here, based on the first-principles calculations and symmetry analysis, we reveal rich nodal loops in the existing material XSb (X = La, Pr, Nd) in the absence of spin-orbital coupling (SOC), which are enabled by symmetries. For example, a set of three nodal loops forms an inner chain at high symmetry points, and a nodal line penetrate the whole Brillouin zone. The stability of each nodal loop is ensured a mirror, and characterized by a topological invariant in zero-dimensional manifold. Furthermore, we also study the surface correspondence of the nodal loops. There exist drumhead surface states within/out of the projection of the nodal loops. In the presence of SOC, Dirac points emerge on high symmetry line, around which it shows a wide linear dispersion window. Notably, Dirac points are quite near to Fermi level, and Fermi arcs emanating from the projection of Dirac points could be clearly observed. In addition, we verify that these Fermi arcs are fragile, not topologically protected. Our work suggests a family of realistic materials to study the inner chains and Dirac semimetals.
查看更多>>摘要：In this work, we propose novel two-dimensional (2D) Janus Ni dichalcogenide materials and explore their feasibility, stability and evaluate their electronic and optical properties with ab-initio calculations. Three unique Janus materials, namely NiSSe, NiSTe and NiSeTe, with 2H hexagonal structure were proposed. Density functional theory (DFT) calculations, show that among the three proposed NiXY Janus 2D materials, NiSSe had the best energetic and dynamical stability. GGA PBE calculations showed NiSSe to have a metallic bandstructure with the Ni-Se interaction having a dominant role in the band profile near the Fermi energy. Electron localization function (ELF) and total potential plots show a distinguishable asymmetry in terms of valence electron localization and distribution between the S and Se atoms in 2D NiSSe. The presence of large amount of electron gas like feature in the ELF around the chalcogen atoms also indicates their importance in the conduction properties. Optical properties calculated with random phase approximation (RPA) show the 2D NiSSe to have broad spectrum optical response with significant peaks lying in each of the infra-red, visible and the ultraviolet range of the spectra.
Podgurschi, V.King, D. J. M.Luo, K.Wenman, M. R....
12页
查看更多>>摘要：Molecular dynamics simulations of single crystal zirconium fracture were performed to study the deformation mechanisms active on the basal and prismatic planes. The effects of temperature (0 to 300 K) and strain rate (10(8)-10(10) s(-1)) were investigated. Crack tip orientation was found to strongly affect the fracture behaviour. On the basal plane twinning ({11 (2) over bar1}< 1 (1) over bar 26 >) and emission of type dislocations that then dissociated into partial dislocations around pyramidal I-2 stacking faults were seen to occur during fracture. At higher strain rates (10(9) and 10(10) s(-1)), twinning occurred. The emission of edge dislocations (1/3 < 1 (2) over bar 10 > type) was prevalent on the prismatic plane and were found to be strongly affected by temperature. At higher temperature (150 and 300 K), the dislocation density increased. The crack grew further at 150-300 K than at 0 K and the shielding effect of dislocations was limited due to their movement away from the crack tip. The addition of iodine at basal I-2, pyramidal I-1 and I-2 stacking faults was seen to decrease the energy of its formation whereas for the prismatic stacking fault it was found to increase it. The iodine also changed the order of favourability of the stacking faults with basal I-2 and pyramidal I-1 stacking faults becoming much more favourable and prismatic going from most to least favourable.
查看更多>>摘要：ABS T R A C T Fracture behaviors of brittle materials are a crucial problem when it comes to reliability, especially for nanoscale devices and systems such as those built based on graphene. This study aims to use a new deep learning model, successfully incorporating data from molecular-level modeling, to predict the fracture path of graphene under the presence of various defects. In the process to build the model we first perform tensile test simulations on various graphene systems using molecular dynamics. The results are then transferred into image-based data for processing in the deep learning model. Based on this dataset we then construct multiple ConvLSTM-based models to learn the spatial-temporal information about crack propagation for each graphene system, respectively. The results show that our ConvLSTM-based models can predict the fracture path of graphene with 99 percent ac-curacy on a system of different crystallinity and 98 percent accuracy on different sets of defects, demonstrating excellent generalizability and transferability. These models demonstrate the power of exploiting deep learning for nanoengineering, and to specifically confer desired properties of materials based on defect engineering, which has great potential for next-generation materials by design.
Bhesania, Abhishek S.Kamboj, ParveshPeddakotla, Sai AbhishekKumar, Rakesh...
15页
查看更多>>摘要：Reaction kinetics parameters of a material depend on energy dynamics based on breaking and formation of all the types of bonds in the system. While employing molecular dynamics simulation, it can become tedious and a complicated job to use all the bond information for extracting reaction kinetics parameters. With this understanding, in the current study, the use of an unsupervised machine learning technique is demonstrated for extracting the reaction kinetics parameters from the molecular dynamics simulation of an ablative material. Molecular dynamics simulations are performed on crosslinked and non-crosslinked polymers in temperature regime where they would undergo pyrolysis decomposition. Non-negative Matrix Factorization (NMF) technique is used to reduce the bonding environment, obtained during the simulations, to the concentration profiles of a few principal components. A comparative analysis performed with polymers having different degrees of crosslinking reveals that the activation energy reduces with increase in the degree of crosslinking. The effect of heating rate on the reaction kinetics of phenolic polymers during the pyrolysis simulation is investigated in detail. The assumption of chemical equilibrium between gases and porous solid domain is frequently made in continuum level thermal response solvers. It is unknown if this assumption significantly affects the calculated reaction kinetics parameters. To understand the same, a molecular dynamics simulation, which eliminates the generated gas molecules in a systematic manner throughout the pyrolysis process, is carried out. Furthermore, to demonstrate the usefulness of reaction kinetics parameters extracted after manifestation of chemical equilibrium at microscale level, a one-dimensional heat conduction analysis is performed. The results obtained by not considering the gas particles in reaction modeling agree well with experiments. At the end, a multiscale thermal response analysis is performed over an axi-symmetric geometry for which, a relation is derived between pyrolysis gas species and solid material density evolution from MD simulations. Based on the relation, the axi-symmetric domain is segregated into different regions for their contribution in changing pyrolysis gas composition by either adding or consuming gas species.
查看更多>>摘要：Melting and solidification of pure metals and alloys are important research areas due to their practical applications, where the study of dynamic evolution of the interface offers a challenging task to the researchers. For the last two decades, lattice Boltzmann method (LBM) has been extensively used to model transport phenomena involving complex boundary at the phase interface for pure metals and alloys because of high computational efficiency and cost effectiveness of LBM. A state-of-art survey on application of LBM for melting and solidification phenomena is now presented in this work. This paper, first introduces the theory of thermal lattice Boltzmann method (TLBM) for heat and fluid flow, subsequently an elaborate coverage is presented on the methodologies used to study the melting-solidification phenomena of pure substances and alloy materials. The success of lattice Boltzmann (LB) method in investigating the morphological structure during solidification is specially emphasized. It is observed in this context that the phase field method (PFM) has evolved as the most popular choice for evaluating the microstructure. While the robustness of LBM can effectively handle the fluid flow calculation around the dendrites, phase field based lattice Boltzmann method (PFLBM) is very effective in simulating the growth of dendrites from the seed level to the very large scale. The realistic morphological structure can be accurately predicted due to the computational efficacy of PFLBM. A comprehensive coverage has been provided on application of PFLBM method in simulating the growth kinetics in alloys. Further, the application of the PFLBM in solidification has been showcased from open literature.
查看更多>>摘要：The deformation behaviors of crystal-glass nanocomposites with structural heterogeneities that contain different grain sizes in their crystal phase are studied by using molecular dynamics simulation. Their stress-strain response and microstructures evolved with the applied tensile strain are quantitively analyzed. It is found that the mechanical response of the nanocomposite is sensitive to the average grain size of its crystal phase, and the specimen with the smallest grain size exhibits the highest strength among all. Strain partitioning inevitably occurs between the crystal phase and the glassy domains during the tensile loading, while the average atomic shear strain of the glassy phase is increased with the grain size of the crystal phase. As well, the increased grain size also aggravates the strain localization inside the glassy domains, which promotes the formation of shear transformation zones (STZs) and facilitates the strain heterogeneities there. A mass of lath-like stain paths with severe strain localization are also observed to form in the nanocomposite specimen with a larger grain size, which can function as the transmission medium for delivering the shear strains between different domains and accommodating the plastic flows during the deformation. The present work is aimed to underline that the configuration of structural heterogeneities in the glass-crystal nanocomposite can alter the strain partitioning between different phase domains, which can be used to tune the mechanical performance of the nanocomposite. The unveiled atomistic deformation mechanism of the crystal-glass nanocomposite also provide new sights on designing and optimizing the structural heterogeneities of nanocomposites for achieving better mechanical properties in future.
查看更多>>摘要：A new method for temperature-dependent phase equilibrium prediction for use in multi-component phase field models of solidification is proposed. The method consists of two parts. First, the convex hull method is applied to predict the phase equilibrium at a single temperature. Second, a set of linear equations is developed to extend the equilibrium calculation over a range of temperatures. These linear equations are derived as an extension of the equation used for solidification of binary alloys in approximating the equilibrium state of multi-component systems. Phase field simulations of solidification of a Ti-Al-V-Fe alloy are performed to demonstrate the effectiveness of the present approach under isothermal and continuous cooling conditions. The results are compared against Thermo-Calc calculations, and indicate that a high accuracy of equilibrium prediction is achieved at a single and multiple temperatures, thus demonstrating that this approach can be successfully applied to the multi-component phase field models.
查看更多>>摘要：Interatomic potentials for Mn-Sn, Ni-Sn, Na-Cu, Na-Mn, and Na-Ni binary systems and Na-Cu-Sn, Na-Mn-Sn, and Na-Ni-Sn ternary systems have been developed on the basis of the second nearest-neighbor modified embedded atom method (2NN MEAM) formalism. The potentials can describe various fundamental materials properties such as structural, elastic, thermodynamic, and thermal properties in reasonable agreement with experiments and DFT calculations. It is demonstrated that the potentials can be used for atomistic simulations to understand material phenomena and to search for optimal tin-based alloy anode materials for sodium ion batteries.
NSTL
Elsevier