The oxidation of nanoscale 3C-SiC involving four polar faces（C（100）, Si（100）, C（111）, and Si（111）） is studied by means of a reactive force field molecular dynamics（Reax FF MD） simulation. It is shown that ...The oxidation of nanoscale 3C-SiC involving four polar faces（C（100）, Si（100）, C（111）, and Si（111）） is studied by means of a reactive force field molecular dynamics（Reax FF MD） simulation. It is shown that the consistency of 3C-SiC structure is broken over 2000 K and the low-density carbon chains are formed within SiC slab. By analyzing the oxygen concentration and fitting to rate theory, activation barriers for C（100）, Si（100）, C（111）, and Si（111） are found to be 30.1,35.6, 29.9, and 33.4 k J·mol^-1. These results reflect lower oxidative stability of C-terminated face, especially along [111] direction. Compared with hexagonal polytypes of SiC, cubic phase may be more energy-favorable to be oxidized under high temperature, indicating polytype effect on SiC oxidation behavior.展开更多
The prediction equations formulated in the existing prediction methods toy using the empirical orthogonal function are generally based upon field resolution according to the statistical relation among the predictands....The prediction equations formulated in the existing prediction methods toy using the empirical orthogonal function are generally based upon field resolution according to the statistical relation among the predictands. The influence of external factors is seldom to be considered. The present paper attempts to introduce the influence factors into the empirical orthogonal prediction method. There are five different approaches to be proposed for this purpose, what the field prediction method with optimum factors is studied with emphasis. In this method we consider not only the internal correlation among the predictands but also the influence of external factors, and the optimal prediction equation which is suitable for predicting both values and grades that may he formulated by the selected optimum factors from the combinational factors.The conception of weighting correlation coefficient is suggested here. The obvious difference between it and other correlation coefficients is that the former has the field charactor. Several practical examples corresponding to the previous mentioned prediction methods are also presented in this paper.展开更多
基金Project supported by the 111 Project(Grant No.B07050)the National Natural Science Foundation of China(Grant No.11402206)
文摘The oxidation of nanoscale 3C-SiC involving four polar faces（C（100）, Si（100）, C（111）, and Si（111）） is studied by means of a reactive force field molecular dynamics（Reax FF MD） simulation. It is shown that the consistency of 3C-SiC structure is broken over 2000 K and the low-density carbon chains are formed within SiC slab. By analyzing the oxygen concentration and fitting to rate theory, activation barriers for C（100）, Si（100）, C（111）, and Si（111） are found to be 30.1,35.6, 29.9, and 33.4 k J·mol^-1. These results reflect lower oxidative stability of C-terminated face, especially along [111] direction. Compared with hexagonal polytypes of SiC, cubic phase may be more energy-favorable to be oxidized under high temperature, indicating polytype effect on SiC oxidation behavior.
文摘The prediction equations formulated in the existing prediction methods toy using the empirical orthogonal function are generally based upon field resolution according to the statistical relation among the predictands. The influence of external factors is seldom to be considered. The present paper attempts to introduce the influence factors into the empirical orthogonal prediction method. There are five different approaches to be proposed for this purpose, what the field prediction method with optimum factors is studied with emphasis. In this method we consider not only the internal correlation among the predictands but also the influence of external factors, and the optimal prediction equation which is suitable for predicting both values and grades that may he formulated by the selected optimum factors from the combinational factors.The conception of weighting correlation coefficient is suggested here. The obvious difference between it and other correlation coefficients is that the former has the field charactor. Several practical examples corresponding to the previous mentioned prediction methods are also presented in this paper.
