Multiscale Calculations Research Articles

W and X Photoluminescence Centers in Crystalline Si: Chasing Candidates at Atomic Level Through Multiscale Simulations

Several atomistic techniques have been combined to identify the structure of defects responsible for X and W photoluminescence lines in crystalline Si. We used kinetic Monte Carlo simulations to reproduce irradiation and annealing conditions used in photoluminescence experiments. We found that W and X radiative centers are related to small Si self-interstitial clusters but coexist with larger Si self-interstitials clusters that can act as nonradiative centers. We used molecular dynamics simulations to explore the many different configurations of small Si self-interstitial clusters, and selected those having symmetry compatible with W and X photoluminescence centers. Using ab initio simulations, we calculated their formation energy, donor levels, and energy of local vibrational modes. On the basis of photoluminescence experiments and our multiscale theoretical calculations, we discuss the possible atomic configurations responsible for W and X photoluminescence centers in Si. Our simulations also reveal that the intensity of photoluminescence lines is the result of competition between radiative centers and nonradiative competitors, which can explain the experimental quenching of W and X lines even in the presence of the photoluminescence centers.

Data Decomposition Techniques with Multi-Scale Permutation Entropy Calculations for Bearing Fault Diagnosis.

This paper presents the local mean decomposition (LMD) integrated with multi-scale permutation entropy (MPE), also known as LMD-MPE, to investigate the rolling element bearing (REB) fault diagnosis from measured vibration signals. First, the LMD decomposed the vibration data or acceleration measurement into separate product functions that are composed of both amplitude and frequency modulation. MPE then calculated the statistical permutation entropy from the product functions to extract the nonlinear features to assess and classify the condition of the healthy and damaged REB system. The comparative experimental results of the conventional LMD-based multi-scale entropy and MPE were presented to verify the authenticity of the proposed technique. The study found that LMD-MPE’s integrated approach provides reliable, damage-sensitive features when analyzing the bearing condition. The results of REB experimental datasets show that the proposed approach yields more vigorous outcomes than existing methods.

Solution of the Nonlinear High-Fidelity Generalized Method of Cells Micromechanics Relations via Order-Reduction Techniques

The High-Fidelity Generalized Method of Cells (HFGMC) is one technique, distinct from traditional finite-element approaches, for accurately simulating nonlinear composite material behavior. In this work, the HFGMC global system of equations for doubly periodic repeating unit cells with nonlinear constituents has been reduced in size through the novel application of a Petrov-Galerkin Proper Orthogonal Decomposition order-reduction scheme in order to improve its computational efficiency. Order-reduced models of an E-glass/Nylon 12 composite led to a 4.8–6.3x speedup in the equation assembly/solution runtime while maintaining model accuracy. This corresponded to a 21–38% reduction in total runtime. The significant difference in assembly/solution and total runtimes was attributed to the evaluation of integration point inelastic field quantities; this step was identical between the unreduced and order-reduced models. Nonetheless, order-reduced techniques offer the potential to significantly improve the computational efficiency of multiscale calculations.

A Multi-scale model for CO2 capture: A Nickel-based oxygen carrier in Chemical-looping Combustion

In this work, we present a multi-scale modelling framework for the Ni-based oxygen carrier (OC) particle that can explicitly account for the complex reaction mechanism taking place on the contacting surface between gas and solid reactants in Chemical Looping Combustion (CLC). This multi-scale framework consists of a gas diffusion model and a surface reaction model. Continuum equations are used to describe the gas diffusion inside OC particles, whereas Mean-field approximation method is adopted to simulate the micro-scale events, such as molecule adsorption and elementary reaction, occurring on the contacting surface. A pure CO stream is employed as the fuel gas whereas the NiO is used as the metal oxide because it is one of the mostly used material in laboratory and pilot-scale plants. Rate constants for the micro-scale events considered in the present work were obtained from a systematic Density Functional Theory (DFT) analysis, which provides a reasonable elementary reaction kinetics and lays a solid foundation for multi-scale calculations. A sensitivity analysis on the size of intra-particle pore and the adsoprtion rate constant was conducted to assess the mass transport effects on the porous particle. The proposed multi-scale model shows reasonable tendencies and responses to changes in key modelling parameters.

Do surfaces of positive electrostatic potential on different halogen derivatives in molecules attract? like attracting like!

Coulomb's law states that like charges repel, and unlike charges attract. However, it has recently been theoretically revealed that two similarly charged conducting spheres will almost always attract each other when both are in close proximity. Using multiscale first principles calculations, we illustrate practical examples of several intermolecular complexes that are formed by the consequences of attraction between positive atomic sites of similar or dissimilar electrostatic surface potential on interacting molecules. The results of the quantum theory of atoms in molecules and symmetry adapted perturbation theory support the attraction between the positive sites, characterizing the F•••X (X = F, Cl, Br) intermolecular interactions in a series of 20 binary complexes as closed-shell type, although the molecular electrostatic surface potential approach does not (a failure!). Dispersion that has an r-6 dependence, where r is the equilibrium distance of separation, is found to be the sole driving force pushing the two positive sites to attract. © 2017 Wiley Periodicals, Inc.

Investigating the effects of CNT aspect ratio and agglomeration on elastic constants of crosslinked polymer nanocomposite using multiscale modeling

Multiscale modeling has been developed to calculate the Young's modulus of carbon nanotube (CNT) reinforced epoxy‐based nanocomposites. Molecular dynamics was used to construct nanocomposite models consisting of crosslinked network structure of epoxy resin as the matrix material and CNT as the reinforcement at nanoscale. Transversely, isotropic stiffness matrices were calculated using constant strain method on four cases with different CNT chiralities. Effective fiber method was employed to scale bridging from nanoscale to microscale. In multiscale calculations, various types of micromechanical methods were investigated and Halpin–Tsai formulation was selected due to its more realistic predictions. The results showed that increasing CNT aspect ratio from 1 to 1,000 results in an increase in nanocomposite Young's modulus by about three times for nanocomposite reinforced with CNT(20,0). Comparing CNT(5,0) with CNT(20,0) reinforced polymer results, suggested that increasing the CNT radius resulted in a decrease in nanocomposite moduli to about one half. Multiscale results indicated that CNT agglomeration can decrease nanocomposite Young's modulus to one‐third compared to the dispersed CNT case. Predicted results were compared with numerical and experimental results found in the literature and good agreement was observed. POLYM. COMPOS., 39:4513–4523, 2018. © 2017 Society of Plastics Engineers

Interfacial exchange interactions and magnetism of Ni2MnAl/Fe bilayers

Based on a multi-scale calculations, combining ab-initio methods with spin dynamics simulations, we perform a detailed study of the magnetic behavior of Ni2MnAl/Fe bilayers. Our simulations show that such a bilayer exhibits a small exchange bias effect when the Ni2MnAl Heusler alloy is in a disordered B2 phase. Additionally, we present an effective way to control the magnetic structure of the Ni2MnAl antiferromagnet, in the pseudo-ordered B2-I as well as the disordered B2 phases, via a spin-flop coupling to the Fe layer.

Multiscale modeling of spin transport across a diffuse interface

We present multiscale calculations to describe the spin transport behavior of the Co/Cu bilayer structure including the effect of the interface. The multiscale approach introduces the connection between the ab initio calculation used to describe the electronic structure of the system and the generalized spin accumulation model employed to describe the spin transport behavior. We have applied our model to atomically smooth and diffuse interfaces. The results demonstrate the huge importance of the use of first principle calculations, not only due to the interfacial coordinates optimization but also the magnetic and electronic properties obtained through the electronic structure. The system including the effect of interface with and without the charge fluctuation are studied. The results indicate that changes of electronic structure at the Co/Cu interface give rise to an interfacial resistance distributed over several atomic planes, similar to the effect of interface diffusion. We argue that even atomically smooth Co/Cu interfaces have properties analogous to a diffuse interface due to the variation of electronic structure at the interface.

Dynamic load balancing for CAFE multiscale modelling methods for heterogeneous hardware infrastructure

The paper presents new approach to Static and Dynamic Load Balancing (DBL) for loosely coupled multiscale modelling methods executed in heterogeneous hardware infrastructure. The most popular configurations of computing nodes composed of modern multicore CPUs, GPUs and co-processors, are used. The proposed load balancing approach takes into account previously determined computational character of methods applied in particular scales, which depends on a size of input data, operational intensity and limitations of hardware architecture. Such limitations are defined by the Roofline model and then used in the algorithm as boundary conditions, allowing to determine maximum performance of an algorithm for particular device. Multiscale calculations based on upscaling approach are analysed by using Cellular Automata Finite Element (CAFE) method. The qualitative results, obtained after application of proposed load balancing procedure, are discussed in the paper in details.

Multiscale real-space quantum-mechanical tight-binding calculations of electronic structure in crystals with defects using perfectly matched layers

We consider the scattering of incident plane-wave electrons from a defect in a crystal modeled by the time-harmonic Schrödinger equation. While the defect potential is localized, the far-field potential is periodic, unlike standard free-space scattering problems. Previous work on the Schrödinger equation has been almost entirely in free-space conditions; a few works on crystals have been in one-dimension. We construct absorbing boundary conditions for this problem using perfectly matched layers in a tight-binding formulation. Using the example of a point defect in graphene, we examine the efficiency and convergence of the proposed absorbing boundary condition.

Like Charges Attract?

Using multiscale first-principles calculations, we show that two interacting negatively charged B12I9(-) monoanions not only attract, in defiance of the Coulomb's law, but also the energy barrier at 400 K is small enough that these two moieties combine to form a stable B24I18(2-) moiety. Ab initio molecular dynamics simulations further confirm its stability up to 1500 K. Studies of other B12X9(-) (X = Br, Cl, F, H, Au, CN) show that while all of these B24X18(2-) moieties are stable against dissociation, the energy barrier, with the exception of B24Au18(2-), is large so as to hinder their experimental observation. Our results explain the recent experimental observation of the "spontaneous" formation of B24I18(2-) in an ion trap. A simple model based upon electrostatics shows that this unusual behavior is due to competition between the attractive dipole-dipole interaction caused by the aspherical shape of the particle and the repulsive interaction between the like charges.

Multiscale seamless-domain method for solving nonlinear heat conduction problems without iterative multiscale calculations

Multiscale seamless-domain method for solving nonlinear heat conduction problems without iterative multiscale calculations

Universal roles of hydrogen in electrochemical performance of graphene: high rate capacity and atomistic origins.

Atomic hydrogen exists ubiquitously in graphene materials made by chemical methods. Yet determining the effect of hydrogen on the electrochemical performance of graphene remains a significant challenge. Here we report the experimental observations of high rate capacity in hydrogen-treated 3-dimensional (3D) graphene nanofoam electrodes for lithium ion batteries. Structural and electronic characterization suggests that defect sites and hydrogen play synergistic roles in disrupting sp2 graphene to facilitate fast lithium transport and reversible surface binding, as evidenced by the fast charge-transfer kinetics and increased capacitive contribution in hydrogen-treated 3D graphene. In concert with experiments, multiscale calculations reveal that defect complexes in graphene are prerequisite for low-temperature hydrogenation, and that the hydrogenation of defective or functionalized sites at strained domain boundaries plays a beneficial role in improving rate capacity by opening gaps to facilitate easier Li penetration. Additional reversible capacity is provided by enhanced lithium binding near hydrogen-terminated edge sites. These findings provide qualitative insights in helping the design of graphene-based materials for high-power electrodes.

Multiscale characterization and modeling of granular materials through a computational mechanics avatar: a case study with experiment

Through a first-generation computational mechanics avatar that directly links advanced X-ray computed tomographic experimental techniques to a discrete computational model, we present a case study where we made the first attempt to characterize and model the grain-scale response inside the shear band of a real specimen of Caicos ooids subjected to triaxial compression. The avatar has enabled, for the first time, the transition from faithful representation of grain morphologies in X-ray tomograms of granular media to a morphologically accurate discrete computational model. Grain-scale information is extracted and upscaled into a continuum finite element model through a hierarchical multiscale scheme, and the onset and evolution of a persistent shear band is modeled, showing excellent quantitative agreement with experiment in terms of both grain-scale and continuum responses in the post-bifurcation regime. More importantly, consistency in results across characterization, discrete analysis and continuum response from multiscale calculations are found, achieving the first and long sought-after quantitative breakthrough in grain-scale analysis of real granular materials.

Chemically functionalized magnetic exchange interactions of hybrid organic-ferromagnetic metal interfaces

We theoretically explore through systematic multiscale ab initio and Monte Carlo calculations how the surface magnetism of a ferromagnetic surface can be fine-tuned by nonmagnetic organic molecules containing a single $\ensuremath{\pi}$ bond. We demonstrate that a magnetic hardening or softening can be induced depending on the electronegativity of the heteroatom or when the $\ensuremath{\pi}$-bond ``bridges'' the magnetic surface atoms. Finally, the Monte Carlo simulations revealed taylored macroscopic hysteresis loops corresponding to soft and hard molecule-surface magnets.

2D Nanovaristors at Grain Boundaries Account for Memristive Switching in Polycrystalline BiFeO3

Memristive switching in polycrystalline materials is widely attributed to the formation and rupture of conducting filaments, believed to be mediated by oxygen‐vacancy redistribution. The underlying atomic‐scale processes are still unknown, however, which limits device modeling and design. Here, experimental data are combined with multiscale calculations to elucidate the entire atomic‐scale cycle in undoped polycrystalline BiFeO3. Conductive atomic force microscopy reveals that the grain boundaries behave like 2D nanovaristors, while on the return part of the cycle, the decreasing current is through the grains. Using density‐functional‐theory and Monte Carlo calculations, the atomic‐scale mechanism of the observed phenomena is deduced. Oxygen vacancies in nonequilibrium concentrations are initially distributed relatively uniformly, but they are swept into the grain boundaries by an increasing voltage. A critical voltage, the SET voltage, then eliminates the barrier for hopping conduction through vacancy energy levels in grain boundaries. On the return part of the cycle, the grain boundaries are again nonconductive, but the grains show nonzero conductivity by virtue of remote doping by oxygen vacancies. The RESET voltage amounts to a heat pulse that redistributes the vacancies. The realization that nanovaristors are at the heart of memristive switching in polycrystalline materials may open possibilities for novel devices and circuits.

Graphdiyne as a promising substrate for stabilizing Pt nanoparticle catalyst

At present, Pt nanoparticle catalysts in fuel cells suffer from aggregation and loss of chemical activity. In this work, graphdiyne, which has natural porous structure, was proposed as substrate with high adsorption ability to stabilize Pt nanoparticles. Using multiscale calculations by ab initio method and the ReaxFF potential, geometry optimizations, molecular dynamics simulations, Metropolis Monte Carlo simulations and minimum energy paths calculations were performed to investigate the adsorption energy and the rates of desorption and migration of Pt nanoparticles on graphdiyne and graphene. According to the comparison between graphdiyne and graphene, it was found that the high adsorption ability of graphdiyne can avoid Pt nanoparticle migration and aggregation on substrate. Then, simulations indicated the potential catalytic ability of graphdiyne-Pt-nanoparticle system to the oxygen reduction reaction in fuel cells. In summary, graphdiyne should be an excellent material to replace graphite or amorphous carbon matrix for stabilizing Pt nanoparticle catalysts.

Thermal properties of a spin spiral: Manganese on tungsten(110)

We report a detailed study of the magnetic properties of a monoatomic layer of Mn on W(110). By comparing multiscale numerical calculations with measurements we evaluate the magnetic ground state of the system and its temperature-dependent evolution. We find that the ground state consists of a cycloidal spin spiral (CSS) that persists up to the N\'eel temperature with a temperature-independent wavelength. However, by continuously increasing the temperature, that CSS becomes thermally depinned. This results in a time-averaged absence of magnetic order, a process that can be viewed as the antiferromagnetic analog of superparamagnetism.

Abstract W P88: THINkS: A Novel Tool for Multiscale CFD Calculations of the Cerebral Vasculature

Background: Computational Fluid Dynamics (CFD) is emerging as a tool for better assessment and management of cerebral aneurysms. However, CFD calculations are often restricted to a small arterial zone and the solution could be inaccurate depending on the boundary conditions prescribed. A 1D simulation of the complete vessel network, THINkS (Total Human Intravascular NetworK Simulation), is introduced to better describe boundary conditions and to provide flow information related to the complete complex vessel network. Methods: THINkS is a modifiable, 1D network simulation of the complete human blood circulatory system. A validation of THINkS was performed using volumetric flow rates recorded in the cerebral vasculature waveforms over the cardiac cycle. Validated waveforms of the; (1) ICA proximal to the siphon, (2) ICA proximal to circle of Willis (CoW), and (3) mid- basilar artery were obtained. THINkS predictions were compared to the experimental bounds for both absolute and dimensionless flow rate quantities. Results: THINkS calculations indicated usefulness of the model in predicting the trends of cerebral flow patterns. THINkS solutions were validated with a number of in vivo experimental data and the agreement was excellent. A comparison with experiments for the impact of incomplete CoW to the flow patterns was also made and the trend shows an excellent agreement with reported data. Conclusion: THINkS allows for more accurate boundary conditions for 3D zonal-based CFD calculations. THINkS has been validated against available experimental data and shown to respond correctly to the flow pattern change caused by the variation in CoW. It provides the detailed flow information of the entire human body including cerebral vessel network. Our aim is to use THINkS to generate accurate flow assessments, guide surgical treatment plans, and more reliably predict risks associated with vascular lesions.

Multiscale calculations of dislocation bias in fcc Ni and bcc Fe model lattices

In order to gain more insights on void swelling, dislocation bias is studied in this work. Molecular static simulations with empirical potentials are applied to map the dislocation–point defects interaction energies in both fcc Ni and bcc Fe model lattices. The interaction energies are then used to numerically solve the diffusion equation and obtain the dislocation bias. The importance of the dislocation core region is studied under a the temperature range 573–1173K and the dislocation densities 1012–1015m-2. The results show that larger dislocation bias is found in the fcc Ni than in the bcc Fe under different temperatures and dislocation densities. The anisotropic interaction energy model is used to obtain the dislocation bias and the result is compared to that obtained using the atomistic interaction model, the contribution from the core structure is then shown in both the Ni lattice and the Fe lattice.