Application Of Monte Carlo Method In Simulation Of Grain Growth

Monte Carlo method is a very important statistical method widely used in statistical physics,material science,engineering and many other fields.The basis of the validity of Monte Carlo method is an effective sampling technology in simulation.The Monte Carlo method,based on Markov chain,as an important sampling method,is the primary method in molecular simulation and statistical physics,which can simulate the microstructure of materials and the grain growth.At the beginning of the 1980s,Exxon,the United States group,used Monte Carlo method to the simulation of the grain growth for the first time,and then certain results were achieved by scholars in this subject.In this paper,the theoretical principles of the Monte Carlo algorithm and the grain growth are briefly introduced to better understand the algorithm and the modeling of real problem.The advantages and disadvantages of the existing models are summarized in four aspects of the space partition,energy calculation,transition probability and algorithm.Then,the software,simulating the grain growth in Monte Carlo method,is developed by the existing algorithm to simulate the microstructure of the materials,the energy changes and the grain size.Then,Ni(OH)2,the precursor of NiO,are prepared by chemical precipitation,whose thermal decomposition kinetics and chemical reaction mechanism are studied.And then the relationship between roasting temperature and grain size is discussed according to the roasting test of Ni(OH)2.The size of NiO,the product of the roasting test,is calculated by XRD data.Finally,the development of Monte Carlo method the grain growth is simulated with the software,a suitable simulation parameters of NiO crystal growth is found according to repeated experiments which is proved to have a better simulation stability,be able to calculate the size of NiO crystal in simulation accurately,observe evolution process of microstructure in the process of the roasting test of Ni(OH)2 clearly and observe the energy change of the system at any moment.