Various promising applications such as acoustic cloaking, sub-wavelength imaging, acoustic wave manipulation, transmission or reflection control etc. are feasible because of the ability of manipulating sounds and vibrations using artificially engineered “Acoustics meta-materials”. Recent works on space-coiling acoustic metamaterials show their extreme constitutive parameters like large refractive index, double negativity and zero mass density. Three dimensional structures have a wide application in sub-wavelength broadband acoustic wave suppression due to huge attenuation. Here we report the study of propagated and transmitted wave through 3D acoustic metamaterials structure using finite element method. Our simulations on 3D structure show a huge absorption/damping over few hundreds kilohertz frequency range.

Thermal transport across interfaces is an important issue for microelectronics, photonics, and thermoelectric devices and has been studied both experimentally and theoretically in the past. In this paper, thermal interface resistance (1/G) between aluminum and silicon with nanoscale vacancies was calculated using non-equilibrium molecular dynamics (NEMD). Both phonon-phonon coupling and electron-phonon coupling are considered in calculations. The results showed that thermal interface resistance increased largely due to vacancies. The effect of both the size and the type of vacancies is studied and compared. And an obvious difference is found for structures with different type/size vacancies.

We consider the simplest one-constant model, put forward by J. Eriksen, for nematic liquid crystals with variable degree of orientation. The equilibrium state is described by a director field n and its degree of orientation s, where the pair (n, s) minimizes a sum of Frank-like energies and a double well potential. In particular, the Euler-Lagrange equations for the minimizer contain a degenerate elliptic equation for n, which allows for line and plane defects to have finite energy. Using a special discretization of the liquid crystal energy, and a strictly monotone energy decreasing gradient flow scheme, we present a simulation of a plane-defect in three dimensions to illustrate our method.

We present a theoretical approach for modeling electrolyte solutions at interfaces that reaches into the mesoscale while retaining molecular detail. The total Hamiltonian of the system includes interactions arising from density and charge density (ion correlation) fluctuations, direct Coulomb interactions between ions, and at interfaces the image interactions, ion-solid and ion-water dispersion interactions. The model was validated against its ability to reproduce ion activity in 1:1 and 2:1 electrolyte solutions in the 0-2 M concentration range, its ability to capture the ion-specific effect in 1:1 electrolytes at the air-water interface, and solvent structure in a confined environment between hydrophobic surfaces, revealing the central role of ion hydration interactions in specific ion thermodynamic properties in the bulk solutions and at interfaces. The model is readily extensible to treat electrolyte interactions and forces across charged solid-water interfaces.

Here we present an alternative approach to coarse graining, based on the multiresolution diffusion-wavelet approach to operator compression, which does not require explicit atomistic-to-coarse-grained mappings. Our diffusion-wavelet method takes as input the topology and sparsity of the molecular bonding structure of a system, and returns as output a hierarchical set of degrees of freedom (DoFs) of system-specific coarse-grained variables. Importantly, the hierarchical compression provides a clear framework for modeling at many model scales (levels), beyond the common two-level CG representation. Our results show that the resulting hierarchy separates localized modes, such as a single C-C vibrational mode, from larger-scale motions, e.g., long-range concerted backbone vibrational modes. Our approach correctly captures small-scale chemical features, such as cellulose ring structures, and alkane side chains or CH2 units, as well as large-scale features of the backbone. In particular, the new method’s finest-scale modes describe DoFs similar to united atom models and other chemically-defined CG models. Modes at coarser levels describe increasingly large connected portions of the target polymers. For polyethylene and polystyrene, spatial coordinates and their associated forces were compressed by up to two orders of magnitude. The compression in forces is of particular interest as this allows larger timesteps as well as reducing the number of DoFs.

Dynamical effects of non-conservative forces in long, defect free atomic wires are investigated. Current flow through these wires is simulated and we find that during the initial transient, the kinetic energies of the ions are contained in a small number of phonon modes, closely clustered in frequency. These phonon modes correspond to the waterwheel modes determined from preliminary static calculations. The static calculations allow one to predict the appearance of non-conservative effects in advance of the more expensive real-time simulations. The ion kinetic energy redistributes across the band as non-conservative forces reach a steady state with electronic frictional forces. The typical ion kinetic energy is found to decrease with system length, increase with atomic mass, and its dependence on bias, mass and length is supported with a pen and paper model. This paper highlights the importance of non-conservative forces in current carrying devices and provides criteria for the design of stable atomic wires.

This article discusses novel algorithms for molecular-dynamics (MD) simulations with short-ranged forces on modern multi- and many-core processors like the Intel Xeon Phi. A task-based approach to the parallelization of MD on shared-memory computers and a tiling scheme to facilitate the SIMD vectorization of the force calculations is described. The algorithms have been tested with three different potentials and the resulting speed-ups on Intel Xeon Phi coprocessors are shown.

We present a novel method to build a coarse-grained (CG) model based on the Mori-Zwanzig (MZ) formalism that reproduces kinetics. Our approach leads to the computation of a generalized Langevin equation (GLE), which includes the memory kernel and the fluctuation that are consistent with brute force molecular dynamics (MD) simulations. Our CG model based on the MZ formalism successfully reproduces kinetics, i.e. the distribution of first passage times (FPT) and velocity autocorrelation functions (VACF), for alanine dipeptide. In addition, we show that the memory part of the CG model of GLE is essential to reproduce kinetics. In other words, the Markovian model fails to reproduce brute force MD results, whereas the GLE model succeeds.

Solid electrolyte interface (SEI) layer plays a key role in lithium-ion batteries’ degradation research. However, SEI layer microstructure prediction still needs further investigation, especially the lithium-ion diffusion in SEI layer considering its morphology evolution during the growth of SEI. Due to the unique advantage of avoiding explicitly tracking the interfaces with sharp composition gradients, a phase field model is developed to simulate the SEI formation and its morphology evolution that is regarded as a solidification process. Fick’s law and mass balance are applied to investigate lithium-ion concentration distribution and diffusion coefficients of different SEI layers (i.e., compact and porous SEI layers) predicted by the developed phase field model. The simulation results show lithium-ion diffusion coefficients between 298K and 318K are 1.34-1.87(10-16) m2/s and 1.73-2.18(10-12) m2/s for compact SEI and porous SEI layer, respectively. The developed model has great potential to be extended to three dimensional spaces for SEI layer spatial growth investigation and other interfaces with complex morphology evolution.

In the developing of scaffolds for cell culture, a large number of architectures with different combinations of properties should be tested to determine the best. This can be costly in time, money and materials. In this paper we have proposed an optimization model that aims to maximize the growth of osteoblasts on polymeric scaffolds by regulating their properties and architecture. Based on the optimization model it was implemented a genetic algorithm to calculate the architecture and properties of the scaffolds. The fiber diameter, pore diameter, porosity, Young's modulus and contact angle of the scaffolds were calculated through four electrospinning parameters: voltage (kV), concentration (% w/v), flow rate (ml/h) and distance (cm). A fitness value was assigned to each scaffold and the highest one was chosen as the best condition for osteoblast growth. The preliminary results obtained by the Genetic Algorithm were consistent with the tendencies reported experimentally in other studies. Also, the methodology established here can be easily adapted to different types of polymers and cells. Finally, the optimization model can be applied not only by means of heuristic method, like a Genetic Algorithm, but also by exact methods.

In this work we introduce an optimization–based method for the coupling of nonlocal and local diffusion problems. Our approach is formulated as a control problem where the states are the solutions of the nonlocal and local equations, the controls are the nonlocal volume constraint and the local boundary condition, and the objective of the optimization is a matching functional for the state variables in the intersection of the nonlocal and local domains. For finite element discretizations we present numerical results in a one–dimensional setting; though preliminary, our tests show the consistency and efficacy of the method, and provide the basis for realistic simulations.

The paper presents the results of numerical modeling of thermomechanical stresses and thermal fields for conditions of erosion-resistant electrode coatings of magnetically controlled MEMS switches with W-Ti-Cu structure at local temperature and electric current influence in axially symmetrical approximation. It is shown that the introduction of titan interlayer (30-100 nm) in the coating with W-Ti-Cu structure results in considerable (more than two times) decrease of internal thermomechanical stresses between layers that increases coating resistance to delamination. It is established that there is an optimum value of Ti layer thickness at which the minimum thermomechanical stresses are provided.

In this work, the formation of d-wave superconducting magnetic vortex is studied within the Bogoliubov-de Gennes formalism and the generalized Hubbard model, which leads to 2N2 coupled self-consistent equations for a supercell of N×N atoms. These equations determine the spatial variation of the superconducting gap as a function of the electron concentration and electron-electron interactions. The results show that the superconducting states induced by the correlated hopping (Δt3) are more sensitive to the presence of magnetic field than those induced by attractive nearest-neighbor interaction (V). Furthermore, we calculate the electronic specific heat as a function of the temperature for a given applied magnetic field, whose behavior has a qualitative agreement with experimental data.

We study the stability of small amplitude harmonic perturbation at the interface of a gel material surrounded by air. The equations describing the system's dynamics are solved using classical perturbation methods. Assuming that the amplitude decays over time, we establish conditions for the system to return to its equilibrium state. The proposed model includes the effect of the boundary conditions and can be extended to more general situation in which the material is surrounded by an arbitrary fluid.

Cellular networks are ubiquitous in nature. Most engineered materials are polycrystalline microstructures composed of a myriad of small grains separated by grain boundaries, thus comprising cellular networks. The recently discovered grain boundary character distribution (GBCD) is an empirical distribution of the relative length (in 2D) or area (in 3D) of interface with a given lattice misorientation and normal. During the coarsening, or growth, process, an initially random grain boundary arrangement reaches a steady state that is strongly correlated to the interfacial energy density. In simulation, if the given energy density depends only on lattice misorientation, then the steady state GBCD and the energy are related by a Boltzmann distribution. This is among the simplest non-random distributions, corresponding to independent trials with respect to the energy. Why does such simplicity emerge from such complexity? Here we describe an entropy based theory which suggests that the evolution of the GBCD satisfies a Fokker-Planck Equation, an equation whose stationary state is a Boltzmann distribution.

Generally, the electrodes are regarded as free electron gases when we calculate the transport characteristics of nanostructure materials or devices. In three dimensional electrodes, there are little electron correlation. However, in low-dimensional electrodes, electron correlation becomes much larger than that in three dimensional ones. Recently, nanotechnology has made much progress to fabricate two-dimensional (2D) electrodes easily and precisely. As a result, we must consider whether two-dimensional electrodes can be regarded as free electron gases. In this study, we investigate the electron energy spectrum of 2D electrodes, taking into consideration the electron correlation. These results suggest that the free electron model is justified only at the Fermi momentum and that we should not regard 2D electrodes as free electron gases without careful consideration under high electric field and/or high temperature.

Determining upconversion parameters is of high interest in laser material development. For many materials these parameters cannot be directly measured by experimental methods. These upconversion coefficients appear as unknown parameters in the laser rate equations, which are a system of coupled nonlinear differential equations that are used to model the dynamics of population densities in different energy levels. In this paper we propose the well-established system theoretic tools pertaining to the system inversion to be applied in this case. The unknown parameters can be considered as the inputs and the fluorescence signals can be considered as the outputs of the dynamical system. Therefore the determination of the unknown upconversion rates in the system equations from the output data is a classical system inversion problem. In this paper we demonstrate how to compute the unknown coefficients in the rate equations from the experimental emission data utilizing this method.

The brain, a mixture of neural and glia cells, vasculature, and cerebrospinal fluid (CSF), is one of the most complex organs in the human body. To understand brain responses to traumatic injuries and diseases of the central nervous system it is necessary to develop accurate mathematical models and corresponding computer simulations which can predict brain biomechanics and help design better diagnostic and therapeutic protocols. So far brain tissue has been modeled as either a poroelastic mixture saturated by CSF or as a (visco)-elastic solid. However, it is not obvious which model is more appropriate when investigating brain mechanics under certain physiological and pathological conditions. In this paper we study brain’s mechanics by using a Kelvin-Voight (KV) model for a one-phase viscoelastic solid and a Kelvin-Voight-Maxwell-Biot (KVMB) model for a two-phase (solid and fluid) mixture, and explore the limit between these two models. To account for brain’s evolving microstructure, we replace in the equations of motion the classic integer order time derivatives by Caputo fractional order derivatives and thus introduce corresponding fractional KV and KVMB models. As in soil mechanics we use the displacements of the solid phase in the classic (fractional) KVMB model and respectively of the classic (fractional) KV model to define a poroelastic-viscoelastic limit. Our results show that when the CSF and brain tissue in the classic (fractional) KVMB model have similar speeds, then the model is indistinguishable from its equivalent classic (fractional) KV model.