Thickness Effect of Nanocrystalline Layer on the Deformation Mechanism of Amorphous/Crystalline Multilayered Structure

Different thickness of amorphous/nanocrystalline multi-layered structure can be used to modulate the strength and ductility of the composite materials.In this work,molecular dynamics simulations were conducted to study the thickness effect of nanocrystalline layer on mechanical properties and deformation behavior of the Cu64Zr36/Cu multi-layer structure.The stress-strain relationship,local stress,local strain,and deformation mechanism are investigated.The results reveal that the change of thickness of the crystalline layer significantly affects the mechanical properties and deformation behavior.As the strain at the elastic region,the amorphous Cu64Zr36 layer dominates the mechanical behavior,leading the fact that Young’s modulus,first yielding stress,and first yielding strain are close to that of Cu64Zr36 BMG.As the strain at the plastic region,the contribution of the crystalline layer on the mechanical behavior becomes more and more significant with increasing the thickness of the crystalline layer.For the thickness ratio(amorphous/crystalline)of 4,the shear band deformation of amorphous layer dominates the mechanical properties.For the thickness ratio is 1,the glide dislocation of the crystalline layer dominates the stress-strain behavior.

A Layer-Based Mesh Generator and Scheme for 3D Printing Simulation

3D Printing,also called Additive Manufacturing,has become a promising manufacturing method to produce parts in various fields as it can produce parts even with very irregular shapes in a relatively shorter process and time.However,during the printing process,some problems could decrease the accuracy and quality of the printed parts,such as warpage due to thermal strains,deformation due to inadequate supports,etc.The finite element method is most commonly adopted to evaluate engineering problems in advance to reduce possible failures;however,the element meshes,needed for analyses,are always irregularly distributed,especially for irregular objects,and cannot match the layer-by-layer growing shapes of the printed parts in the 3D printing process.Without a proper element mesh,the analysis cannot be performed.To overcome this problem,a layer-based mesh generator combined with a corresponding scheme for the 3D Printing simulation is proposed and developed.With the proposed methods,the analysis models can be designed and generated to match the growing shapes,i.e.,layer-by-layer,and used to simulate the layer-by-layer growing behavior in the 3D printing process.Moreover,the proposed schemes directly adopt the Stereo-Lithography(STL)formatted geometric data as the geometry model on which the mesh generation and simulation are based.This makes them even easier to use since the STL geometry format is a De facto standard format used in the 3D printing industry.Several simulation cases have been conducted to demonstrate the effectiveness and efficiency of these proposed schemes.

Estimation Performance for the Cubature Particle Filter under Nonlinear/Non-Gaussian Environments

This paper evaluates the state estimation performance for processing nonlinear/non-Gaussian systems using the cubature particle lter(CPF),which is an estimation algorithm that combines the cubature Kalman lter(CKF)and the particle lter(PF).The CPF is essentially a realization of PF where the third-degree cubature rule based on numerical integration method is adopted to approximate the proposal distribution.It is benecial where the CKF is used to generate the importance density function in the PF framework for effectively resolving the nonlinear/non-Gaussian problems.Based on the spherical-radial transformation to generate an even number of equally weighted cubature points,the CKF uses cubature points with the same weights through the spherical-radial integration rule and employs an analytical probability density function(pdf)to capture the mean and covariance of the posterior distribution using the total probability theorem and subsequently uses the measurement to update with Bayes’rule.It is capable of acquiring a maximum a posteriori probability estimate of the nonlinear system,and thus the importance density function can be used to approximate the true posterior density distribution.In Bayesian ltering,the nonlinear lter performs well when all conditional densities are assumed Gaussian.When applied to the nonlinear/non-Gaussian distribution systems,the CPF algorithm can remarkably improve the estimation accuracy as compared to the other particle lterbased approaches,such as the extended particle lter(EPF),and unscented particle lter(UPF),and also the Kalman lter(KF)-type approaches,such as the extended Kalman lter(EKF),unscented Kalman lter(UKF)and CKF.Two illustrative examples are presented showing that the CPF achieves better performance as compared to the other approaches.

Low-energy electronic states of carbon nanocones in an electric field

The low-energy electronic states and energy gaps of carbon nanocones in an electric field are studied using a single-?-band tight-binding model. The analysis considers five perfect carbon nanocones with disclination angles of 60°, 120°, 180°, 240° and 300°, respectively. The numerical results reveal that the low-energy electronic states and energy gaps of a carbon nanocones are highly sensitive to its geometric shape(i.e. the disclination angle and height), and to the direction and magnitude of an electric field. The electric field causes a strong modulation of the state energies and energy gaps of the nanocones, changes their Fermi levels, and induces zero-gap transitions. The energy-gap modulation effect becomes particularly pronounced at higher strength of the applied electric field, and is strongly related to the geometric structure of the nanocone.

Earthquake Barcode from a Single-Degree-of-Freedom System

Earthquake is a violent and irregular ground motion that can severely damage structures. In this paper we subject a single-degree-of-freedom system, consisting of spring and damper, to an earthquake excitation, and meanwhile investigate the response behavior from a novel theory about the dynamical system, by viewing the time-varying signum function of It can reflect the characteristic property of each earthquake through and the second component of f, where is a time-sampling record of the acceleration of a ground motion. The barcode is formed by plotting with respect to time. We analyze the complex jumping behavior in a barcode and an essential property of a high percentage occupation of the first set of dis-connectivity in the barcode from four strong earthquake records: 1940 El Centro earthquake, 1989 Loma earthquake, and two records of 1999 Chi-Chi earthquake. Through the comparisons of four earthquakes, we can observe that strong earthquake leads to large percentage of the first set of dis-connectivity.

Molecular Dynamics Simulation of the Binding Interaction between Hormone Glucagon Protein and Self-Assembled Monolayer Molecules

Restrained molecular dynamics simulations were performed to study the binding affinity of the peptide with alkanethiols of different tail-groups, S（CH2）7CH3, S（CH2）7OH and S（CH2）7COOH, which self-assembled on Au（111） surface in the presence of water molecules. The curves of binding affinity were calculated by fixing the center of mass of the peptide at various distances from the assembling surface. Simulation results show that the binding affin- ity is in the order as COOH-SAMs〉OH-SAMs〉CH3-SAMs, while 100% COOH-SAMs〉5% COOH-SAMS in concentration. The effects on binding affinity by different tail-groups were also studied. Results show that the binding affinity between COOH-SAMs and the peptide is bigger than those of the others and increasing the acidity of COOH-SAMs will result in stronger attractive power.