Research on KMC-based evolution simulation of dust particles in virtual campus environment

Study on formation of step bunching on 6H-SiC (0001) surface by kinetic Monte Carlo method

We employ a three-dimensional (3D) lattice model based on the kinetic Monte Carlo (KMC) method to study cell self-assembly and cellular aggregate fusion of multicellular aggregate systems. This model is developed to describe and predict time evolution of postprinting morphological structure formation during morphogenesis of tissues or organs in a novel biofabrication process known as bioprinting. In this new technology, live multicellular aggregates are used as the fundamental building blocks, known as the bio-ink, to make tissue or organ constructs via the layer-by-layer deposition technique in biocompatible hydrogels; the printed bio-constructs embedded in the hydrogels are then placed in bioreactors to undergo the fusion process to form the desired functional tissue or organ products. In this paper, we implement the lattice model in an efficient list-based KMC algorithm to simulate the making of a set of tissue/organ constructs in several designer's geometries (a ring, a sheet and a tube), which involves a large number of cells of a single type and various other extracellular matrix materials like agarose etc. We then study the process of cell sorting in fusion of cellular aggregates involving multiple cell types with diverse adhesivities and compatible extracellular hydrogels. The KMC simulations reported in this paper agree qualitatively with the available experimental results. In the meantime, they are also comparable to the results obtained from cellular particle dynamics (CPD) simulations.

A multi-scale method for modeling degradation of bioresorbable polyesters

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.

In the paper, we focus on atom diffusion behavior in Ni-based superalloys, which have important applications in the aero-industry. Specifically, the expressions of the key physical parameter – transition rate (jump rate) in the diffusion can be given from the diffusion theory in solids and the kinetic Monte Carlo (KMC) method, respectively. The transition rate controls the diffusion process and is directly related to the energy of vacancy formation and the energy of migration of atom from density functional theory (DFT). Moreover, from the KMC calculations, the diffusion coefficients for Ni and Al atoms in the γ phase (Ni matrix) and the γʹ phase (intermetallic compound Ni3Al) of the superalloy have been obtained. We propose a strategy of time stepping to deal with the multi-time scale issues. In addition, the influence of temperature and Al concentration on diffusion in dilute alloys is also reported.

Computer simulations of the early-stage growth of Ge clusters at elevated temperatures on patterned Si substrate using the kinetic Monte Carlo method

Diffusion of small two-dimensional Cu islands (containing up to 10 atoms) on Cu(111) has been studied using the newly developed self-learning Kinetic Monte Carlo (SLKMC) method which is based on a database of diffusion processes and their energetics accumulated automatically during the implementation of the SLKMC code. Results obtained from simulations in which atoms hop from one fcc hollow site to another are compared with those obtained from a parallel set of simulations in which the database is supplemented by processes revealed in complementary molecular dynamics simulations at $500\phantom{\rule{0.3em}{0ex}}\mathrm{K}$. They include processes involving the hcp (stacking-fault) sites, which facilitate concerted motion of the islands (simultaneous motion of all atoms in the island). A significant difference in the scaling of the effective diffusion barriers with island size is observed in the two cases. In particular, the presence of concerted island motion leads to an almost linear increase in the effective diffusion barrier with size, while its absence accounts for strong size-dependent oscillations and anomalous behavior for trimers and heptamers. We also identify and discuss in detail the key microscopic processes responsible for the diffusion and examine the frequencies of their occurrence, as a function of island size and substrate temperature.

Effects of substrate strain on epitaxial growth are studied, using the kinetic Monte Carlo (kMC) method. The strain dependences of the activation energy barrier and the attempt frequency are considered. The homo-epitaxial growth on Ag (111) surface with uniform tensile strain is simulated, and influences of substrate strain on the nucleation of island and the morphology are investigated. On the tensile-strained surface, the island density increases due to the suppression of the adatom diffusion on terrace. The averaged coordination number of atom constituting of islands decreases and the shape of island is less compact. The growth behavior on the strained substrate is same as at lower temperature.

Area-selective growth for patterning and separation of molecules at allocated sites: Designed kinetic Monte Carlo simulation for anisotropic molecules

This report presents an accelerated kinetic Monte Carlo (KMC) method to compute the diffusivity of hydrogen in hcp metals and alloys, considering both thermally activated hopping and quantum tunneling. The acceleration is achieved by replacing regular KMC jumps in trapping energy basins formed by neighboring tetrahedral interstitial sites, with analytical solutions for basin exiting time and probability. Parameterized by density functional theory (DFT) calculations, the accelerated KMC method is shown to be capable of efficiently calculating hydrogen diffusivity in α-Zr and Zircaloy, without altering the kinetics of long-range diffusion. Above room temperature, hydrogen diffusion in α-Zr and Zircaloy is dominated by thermal hopping, with negligible contribution from quantum tunneling. The diffusivity predicted by this DFT + KMC approach agrees well with that from previous independent experiments and theories, without using any data fitting. The diffusivity along <c> is found to be slightly higher than that along <a>, with the anisotropy saturated at about 1.20 at high temperatures, resolving contradictory results in previous experiments. Demonstrated using hydrogen diffusion in α-Zr, the same method can be extended for on-lattice diffusion in hcp metals, or systems with similar trapping basins.

In this study, the growth of nano-sized surface step structures was examined using the Kinetic Monte Carlo (KMC) simulation technique. The step growth and correlation function on the nano surfaces were analyzed at surface energy values of Eb = 100 meV, Ed = 80 meV, Eds = 150 meV, and Ek = 80 meV, where Eb is the bonding enegy, Eds is the step edge diffusion , Ed is the surface diffusion and Ek Schwoebel energy barrier values , with a surface flux of 1 atom every 10 ns directed towards the pre-formed stepped surfaces on the nano surfaces. The simulation temperature was set to T = 250 K. In this case, step growth was limited, but cluster structures played an important role in stepped surface growth. In a different scenario, at T = 300 K, the amplitude increased at a constant rate, and there were no step fluctuations. Surface growth increased, and the surface fluctuation amplitude also grew. At T = 350 K, when the temperature was raised further, step fluctuations has become dominant, the step fluctuation continued to increase at a constant rate, the step amplitude grew, and the number of islands decreased compared to the other two cases. In addition the correlation of steps is investigated for each temperature. According to these results, the dynamics of step growth can be controlled by selecting an appropriate temperature and balancing the surface energy parameters.

The previously developed ab initio model and the kinetic Monte Carlo method (KMCM) are used to simulate precipitation in a number of iron-copper alloys with different copper concentrations x and temperatures T. The same simulations are also made using an improved version of the previously suggested stochastic statistical method (SSM). The results obtained enable us to make a number of general conclusions about the dependences of the decomposition kinetics in Fe-Cu alloys on x and T. We also show that the SSM usually describes the precipitation kinetics in good agreement with the KMCM, and using the SSM in conjunction with the KMCM allows extending the KMC simulations to the longer evolution times. The results of simulations seem to agree with available experimental data for Fe-Cu alloys within statistical errors of simulations and the scatter of experimental results. Comparison of simulation results with experiments for some multicomponent Fe-Cu-based alloys allows making certain conclusions about the influence of alloying elements in these alloys on the precipitation kinetics at different stages of evolution.

Mechanisms of ethanol dehydration to ethylene on γ-Al2O3（100）and (110C): A combined DFT and KMC study

Simulations of bi-direction pedestrian flow using kinetic Monte Carlo methods

Kinetic Monte Carlo (KMC) method realizes the millisecond or second order atomistic thin film growth. Twenty five kinds of events which may occur on Al (111) surface were classified. An attempt frequency and an activation energy of each event were defined using vibration analyses and nudged elastic band (NEB) method by which the minimum energy path (MEP) can be reasonably predicted. Temperature and deposition rate dependences of Al (111) film growth were intensively investigated in the present paper. The higher temperature and the lower rate drive the layer-by-layer film structural change. Two types of islands (fcc and hcp) were seen by modeling without considering the events of diffusion of dimer and trimer, while only fcc islands remain with considering such events. Thus, we find that the primitive events of diffusion of dimer and trimer take important roles in determination of surface morphology.