Multi sites vs single site for catalytic combustion of methane over Co3O4(110):A first-principles kinetic Monte Carlo study

Single-atom catalysts have been applied in many processes recently.The difference of their kinetic behavior compared to the traditional heterogeneous catalysts has not been extensively discussed yet.Herein a complete catalytic cycle of CH4 combustion assuming to be confined at isolated single sites of the Co3O4(110)surface is computationally compared with that on multi sites.The macroscopic kinetic behaviors of CH4 combustion on Co3O4(110)is systematically and quantitatively compared between those on the single site and multi sites utilizing kinetic Monte Carlo simulations upon the energetic information from the PBE+U calculation and statistic mechanics.The key factors governing the kinetics of CH4 combustion are disclosed for both the catalytic cycles respectively following the single-site and multi-site mechanisms.It is found that cooperation of multi active sites can promote the activity of complete CH4 combustions substantially in comparison to separated single-site catalyst whereas the confinement of active sites could regulate the selectivity of CH4 oxidation.The quantitative understanding of catalytic mechanism paves the way to improve the activity and selectivity for CH4 oxidation.

Kinetic Monte Carlo Simulation of EB-PVD Film:Effects of Substrate Temperature

The 2D kinetic Monte Carlo （KMC） simulation was used to study the effects of different substrate temperatures on the microstructure of Ni-Cr films in the process of deposition by the electron beam physical vapor deposition （EB-PVD）. In the KMC model, substrate was assumed to be a ＂surface＂ of tight-packed rows, and the simulation includes two phenomena： adatom-surface collision and adatom diffusion. While the interaction between atoms was described by the embedded atom method, the jumping energy was calculated by the molecular static （MS） calculation. The initial location of the adatom was defined by the Momentum Scheme. The results reveal that there exists a critical substrate temperature which means that the lowest packing density and the highest surface roughness structure will be achieved when the temperature is lower than the smaller critical value, while the roughness of both surfaces and the void contents keep decreasing with the substrate temperature increasing until it reaches the higher critical value. The results also indicate that the critical substrate temperature rises as the deposition rate increases.

Influence of CH_3SiCl_3 Consistency on Growth Process of SiC Film by Kinetic Monte Carlo Method

CH3SiCl3 （MTS）-H2-Ar system has been applied to prepare SiC film with chemical vapor deposition （CVD） method in this paper. For three facets of SiC film, some significant influence on growth rate, surface roughness, thickness and relative density brought by MTS consistency has been mainly discussed with kinetic monte carlo （KMC） method. The simulation results show that there is a certain scale for mol ratio of H2 to MTS （H2/MTS） with different deposition temperature. When MTS consistency increases, growth rate and surface roughness of three facets all increase, which manifests approximate linearity relationship. Thickness of three facets also increases while increasing trend of three facets thickness is different obviously. Although relative density of three facets all increases, increasing trend shows a little difference with MTS consistency increasing.

Kinetic Monte Carlo simulations of optimization of self-assembly quantum rings growth strategy based on substrate engineering

In this paper, the kinetic Monte Carlo simulations of the self-assembly quantum rings （QRs） based on the substrate engineering, which is related to the eventual shape of the formed quantum ring, are implemented. According to the simulation results, the availability of the QR with tunable size and the formation of smooth shape on the ideal flat substrate are checked. Through designing the substrate engineering, i.e., changing the depth, the separation and the ratio between the radius and the height of the embedded inclusions, the position and size of QR can be controlled and eventually the growth strategy of optimizing the self-assembly QRs is accomplished.

Influence of helium on the evolution of irradiation-induced defects in tungsten:An object kinetic Monte Carlo simulation

Understanding the evolution of irradiation-induced defects is of critical importance for the performance estimation of nuclear materials under irradiation.Hereby,we systematically investigate the influence of He on the evolution of Frenkel pairs and collision cascades in tungsten(W)via using the object kinetic Monte Carlo(OKMC)method.Our findings suggest that the presence of He has significant effect on the evolution of irradiation-induced defects.On the one hand,the presence of He can facilitate the recombination of vacancies and self-interstitial atoms(SIAs)in W.This can be attributed to the formation of immobile He-SIA complexes,which increases the annihilation probability of vacancies and SIAs.On the other hand,due to the high stability and low mobility of He-vacancy complexes,the growth of large vacancy clusters in W is kinetically suppressed by He addition.Specially,in comparison with the injection of collision cascades and He in sequential way at 1223 K,the average sizes of surviving vacancy clusters in W via simultaneous way are smaller,which is in good agreement with previous experimental observations.These results advocate that the impurity with low concentration has significant effect on the evolution of irradiation-induced defects in materials,and contributes to our understanding of W performance under irradiation.

Magnetization dynamics of mixed Co–Au chains on Cu(110) substrate:Combined ab initio and kinetic Monte Carlo study

We present an investigation of the one-dimensional ferromagnetism in Au–Co nanowires deposited on the Cu（110）surface. By using the density functional theory, the influence of the nonmagnetic copper substrate Cu（110） on the magnetic properties of the bimetallic Au–Co nanowires is studied. The results show the emergence of magnetic anisotropy in the supported Au–Co nanowires. The magnetic anisotropy energy has the same order of magnitude as the exchange interaction energy between Co atoms in the wire. Our electronic structure calculation reveals the emergence of new hybridized bands between Au and Co atoms and surface Cu atoms. The Curie temperature of the Au–Co wires is calculated by means of kinetic Monte Carlo simulation. The strong size effect of the Curie temperature is demonstrated.

Kinetic Monte Carlo Simulation of Deposition of Co Thin Film on Cu(001)

A kinetic Monte Carlo （kMC） simulation is conducted to study the growth of ultrathin film of Co on Cu（001） surface. The many-body, tight-binding potential model is used in the simulation to represent the interatomic potential. The film morphology of heteroepitaxial Co film on a Cu（001） substrate at the transient and final state conditions with various incident energies is simulated. The Co covered area and the thickness of the film growth of the first two layers are investigated. The simulation results show that the incident energy influences the film growth and structure. There exists a transition energy where the interracial roughness is minimum. There are some void regions in the film in the final state, because of the influence of the island growth in the first few layers. In addition, there are deviations from ideal layer-by-layer growth at a coverage from 0 - 2 monolayers （ML）.

The XPK Package:A Comparison between the Extended Phenomenological Kinetic(XPK) Method and the Conventional Kinetic Monte Carlo(KMC) Method

Recently, we proposed the extended phenomenological kinetics (XPK) method, which overcomes the notorious timescale separation difficulty between fast diffusion and slow chemical reactions in conventional kinetic Monte Carlo (KMC) simulations. In the present work, we make a comprehensive comparison, based on the newly developed XPK package, between the XPK method and the conventional KMC method using a model hydrogenation reaction system. Two potential energy surfaces with different lateral interactions have been designed to illustrate the advantages of the XPK method in computational costs, parallel efficiency and the convergence behaviors to steady states. The XPK method is shown to be efficient and accurate, holding the great promise for theoretical modelling in heterogeneous catalysis, in particular, when the role of the lateral interactions among adsorbates is crucial.

Quantitative Simulation Study of Metal Additive Manufacturing by Kinetic Monte Carlo

Metal additive manufacturing (AM) is a disruptive manufacturing technology that takes into account the needs of complex structural forming and high-performance component forming. At present, the understanding of metal additive manufacturing simulation methods is not thorough enough, which restricts the development of metal additive manufacturing. Present work discusses the evolution of KMC method simulation results for simulating metal additive manufacturing at different length ratios and different scanning speeds. The results reveal that as the scanning speed increases, the main grains in the simulation results are transformed from coarse columnar grains to crescent-shaped grains, which are in good agreement with the existing experimental results. Besides, as the ratio of unit physical length to unit simulation length increases, the ratio of unit physical time to unit simulation time gradually decreases.

Coarse-Grained Langevin Approximations and Spatiotemporal Acceleration for Kinetic Monte Carlo Simulations of Diffusion of Interacting Particles

Kinetic Monte Carlo methods provide a powerful computational tool for the simulation of microscopic processes such as the diffusion of interacting particles on a surface, at a detailed atomistic level. However such algorithms are typically computationatly expensive and are restricted to fairly small spatiotemporal scales. One approach towards overcoming this problem was the development of coarse-grained Monte Carlo algorithms. In recent literature, these methods were shown to be capable of efficiently describing much larger length scales while still incorporating information on microscopic interactions and fluctuations. In this paper, a coarse-grained Langevin system of stochastic differential equations as approximations of diffusion of interacting particles is derived, based on these earlier coarse-grained models. The authors demonstrate the asymptotic equivalence of transient and long time behavior of the Langevin approximation and the underlying microscopic process, using asymptotics methods such as large deviations for interacting particles systems, and furthermore, present corresponding numerical simulations, comparing statistical quantities like mean paths, auto correlations and power spectra of the microscopic and the approximating Langevin processes. Finally, it is shown that the Langevin approximations presented here are much more computationally efficient than conventional Kinetic Monte Carlo methods, since in addition to the reduction in the number of spatial degrees of freedom in coarse-grained Monte Carlo methods, the Langevin system of stochastic differential equations allows for multiple particle moves in a single timestep.

Kinetic Monte Carlo simulations of plasma-surface reactions on heterogeneous surfaces

Reactions of atoms and molecules on chamber walls in contact with low temperature plasmas are important in various technological applications.Plasma-surface interactions are complex and relatively poorly understood.Experiments performed over the last decade by several groups prove that interactions of reactive species with relevant plasma-facing materials are characterized by distributions of adsorption energy and reactivity.In this paper,we develop a kinetic Monte Carlo(KMC)model that can effectively handle chemical kinetics on such heterogenous surfaces.Using this model,we analyse published adsorption-desorption kinetics of chlorine molecules and recombination of oxygen atoms on rotating substrates as a test case for the KMC model.

A Simple Kinetic Monte Carlo Approach for Epitaxial Submonolayer Growth

Two-component submonolayer growth on triangular lattice is qualitatively studied by kinetic Monte Carlo techniques.The hopping barrier governing surface diffusion of the atoms is estimated using pair interaction potentials.Several degrees of freedoms enhancing the surface diffusion of atoms are also introduced.The main advantages of the presented technique are the reduced number of free parameters and the clear diffusion activated mechanism for the segregation of different types of atoms.The potential of this method is exemplified by reproducing(i)phase-boundary creation and dynamics related to vacancies and stacking faults;(ii)a special co-deposition and segregation process where the segregated atoms of the second component surround the islands formed by the first type of atoms.

Simulation of Three-Dimensional Strained Heteroepitaxial Growth Using Kinetic Monte Carlo

Efficient algorithms for the simulation of strained heteroepitaxial growth with intermixing in 2+1 dimensions are presented.The first of these algorithms is an extension of the energy localization method[T.P.Schulze and P.Smereka,An energy localization principle and its application to fast kinetic Monte Carlo simulation of heteroepitaxial growth,J.Mech.Phys.Sol.,3(2009),521-538]from1+1 to 2+1 dimensions.Two approximations of this basic algorithm are then introduced,one of which treats adatoms in a more efficient manner,while the other makes use of an approximation of the change in elastic energy in terms of local elastic energy density.In both cases,it is demonstrated that a reasonable level of fidelity is achieved.Results are presented showing how the film morphology is affected by misfit and deposition rate.In addition,simulations of stacked quantum dots are also presented.

Inverted List Kinetic Monte Carlo with Rejection Applied to Directed Self-Assembly of Epitaxial Growth

We study the growth of epitaxial thin films on pre-patterned substrates that influence the surface diffusion of subsequently deposited material using a kinetic Monte Carlo algorithm that combines the use of inverted lists with rejection.The resulting algorithm is well adapted to systems with spatially heterogeneous hopping rates.To evaluate the algorithm’s performance we compare it with an efficient,binary-tree based algorithm.A key finding is that the relative performance of the inverted list algorithm improves with increasing system size.

Kinetic Monte Carlo Simulation of Metallic Nanoislands Grown by Physical Vapor Deposition

We report kinetic Monte-Karlo(KMC)simulation of self-assembled synthesis of nanocrystals by physical vapor deposition(PVD),which is one of most flexible,efficient,and clean techniques to fabricate nanopatterns.In particular,self-assembled arrays of nanocrystals can be synthesized by PVD.However size,shape and density of self-assembled nanocrystals are highly sensitive to the process conditions such as duration of deposition,temperature,substrate material,etc.To efficiently synthesize nanocrystalline arrays by PVD,the process control factors should be understood in detail.KMC simulations of film deposition are an important tool for understanding the mechanisms of film deposition.In this paper,we report a KMC modeling that explicitly represents PVD synthesis of self-assembled nanocrystals.We study how varying critical process parameters such as deposition rate,duration,temperature,and substrate type affect the lateral 2D morphologies of self-assembled metallic islands on substrates,and compare our results with experimentally observed surface morphologies generated by PVD.Our simulations align well with experimental results reported in the literature.

A Kinetic Monte Carlo Approach for Self-Diffusion of Pt Atom Clusters on a Pt(111)Surface

A lattice Kinetic Monte Carlo(KMC)approach is considered to study the statistical properties of the diffusion of Pt atom clusters on a Pt(111)surface.The interatomic potential experienced by the diffusing atoms is calculated by the embedded atom method and the hopping barrier for the allowed atomic movements are calculated using the Nudged Elastic Band method.The diffusion coefficient is computed for various cluster sizes and system temperatures.The obtained results are in agreement with the ones obtained in previous experimental and theoretical works.A simple scaling argument is proposed for the size dependence of the diffusion coefficient’s prefactor.A detailed statistical analysis of the event by event KMC dynamics reveals two important and co-existing mechanisms for the diffusion of the cluster’s center of mass.At low temperatures(below T=400K)the dominating mechanism responsible for the displacement of the cluster’s center of mass is the periphery(or edge)diffusion of the atoms.At high temperatures(above T=800K)the dissociation and recombination of the clusters becomes more and more important.

Coarse-graining Calcium Dynamics on Stochastic Reaction-diffusion Lattice Model

We develop a coarse grained （CG） approach for efficiently simulating calcium dynamics in the endoplasmic reticulum membrane based on a fine stochastic lattice gas model. By grouping neighboring microscopic sites together into CG cells and deriving CG reaction rates using local mean field approximation, we perform CG kinetic Monte Carlo （kMC） simulations and find the results of CG-kMC simulations are in excellent agreement with that of the microscopic ones. Strikingly, there is an appropriate range of coarse proportion rn, corresponding to the minimal deviation of the phase transition point compared to the microscopic one. For fixed m, the critical point increases monotonously as the system size increases, especially, there exists scaling law between the deviations of the phase transition point and the system size. Moreover, the CG approach provides significantly faster Monte Carlo simulations which are easy to implement and are directly related to the microscopics, so that one can study the system size effects at the cost of reasonable computational time.

Coarse-grained Simulations of Chemical Oscillation in Lattice Brusselator System

The oscillation behavior of a two-dimension lattice-gas Brusselator model was investigated. We have adopted a coarse-grained kinetic Monte Carlo （CG-KMC） procedure, where m×m microscopic lattice sites are grouped together to form a CG cell, upon which CG processes take place with well-defined CG rates. Such a CG approach almost fails if the CG rates are obtained by a simple local mean field （s-LMF） approximation, due to the ignorance of correlation among adjcent cells resulting fl＇om the trimolecular reaction in this nonlinear system. By proper incorporating such boundary effects, thus introduce the so-cMled b-LMF CG approach. Extensive numerical simulations demonstrate that the b-LMF method can reproduce the oscillation behavior of the system quite well, given that the diffusion constant is not too small. In addition, the deviation from the KMC results reaches a nearly zero minimum level at an intermediate cell size, which lies in between the effective diffusion length and the minimal size required to sustain a well-defined temporal oscillation.

Molecular Simulations of Adsorption and Diffusion Behaviors of Benzene Molecules in NaY Zeolite

In the article the Grand Canonical Monte Carlo （GCMC）, molecular dynamics（MD）, and kinetic Monte Carlo （KMC） simulations with particular focus on ascertaining the loading dependence of benzene diffusion in the zeolite were performed. First, a realistic representation of the structure of the sorbate-sorbent system was obtained based on GCMC simulation. The simulation clearly shows the characteristics of the adsorption sites of the benzene-NaY system, from which two kinds of preferably adsorbing sites for benzene molecules, called SⅡ and W sites, are identified. The structure thus obtained was then used as a basis for KMC and MD simulations. A compara-tive study by introducing and comparing two different mechanisms underlying jump diffusion in the zeolite of in-terest shows that the.MS diffusivity values predicted by the KMC and MD methods are fairly close to each other,leading to the conclusion that for benzene diffusion in NaY, the SⅡ→W→SⅡ jumps of benzene molecules are dominated,while the W→Wjumps do not exist in the process. These findings provide further support to our previous conclusion about the absence of the W→W jumps in the process of benzene diffusion in NaY. Finally, to relations, for predicting the self-and MS difthsivities were derived and found to be in fair agreement with the KMC and MD simulations.

Simulation of multilayer homoepitaxial growth on Cu （100） surface

The processes of multilayer thin Cu films grown on Cu （100） surfaces at elevated temperature （250-400K） are simulated by mean of kinetic Monte Carlo （KMC） method, where the realistic growth model and physical parameters are used. The effects of small island （dimer and trimer） diffusion, edge diffusion along the islands, exchange of the adatom with an atom in the existing island, as well as mass transport between interlayers are included in the simulation model. Emphasis is placed on revealing the influence of the Ehrlic-Schwoebel （ES） barrier on growth mode and morphology during multilayer thin film growth. We present numerical evidence that the ES barrier does exist for the Cu/Cu（100） system and an ES barrier EB 〉 0.125eV is estimated from a comparison of the KMC simulation with the realistic experimental images. The transitions of growth modes with growth conditions and the influence of exchange barrier on growth mode are also investigated.