Kubo Atsushi, Umeno Yoshitaka
Institute of Industrial Science, The University of Tokyo, Tokyo 113-8654, Japan.
Materials (Basel). 2021 Mar 25;14(7):1597. doi: 10.3390/ma14071597.
Ceramic matrix composites (CMCs) based on silicon carbide (SiC) are used for high-temperature applications such as the hot section in turbines. For such applications, the mechanical properties at a high temperature are essential for lifetime prediction and reliability design of SiC-based CMC components. We developed an interatomic potential function based on the artificial neural network (ANN) model for silicon-carbon systems aiming at investigation of high-temperature mechanical properties of SiC materials. We confirmed that the developed ANN potential function reproduces typical material properties of the single crystals of SiC, Si, and C consistent with first-principles calculations. We also validated applicability of the developed ANN potential to a simulation of an amorphous SiC through the analysis of the radial distribution function. The developed ANN potential was applied to a series of creep test for an amorphous SiC model, focusing on the amorphous phase, which is expected to be formed in the SiC-based composites. As a result, we observed two types of creep behavior due to different atomistic mechanisms depending on the strain rate. The evaluated activation energies are lower than the experimental values in literature. This result indicates that an amorphous region can play an important role in the creep process in SiC composites.
基于碳化硅（SiC）的陶瓷基复合材料（CMC）用于高温应用，如涡轮机的热段。对于此类应用，高温下的机械性能对于基于SiC的CMC部件的寿命预测和可靠性设计至关重要。我们基于人工神经网络（ANN）模型开发了一种用于硅 - 碳系统的原子间势函数，旨在研究SiC材料的高温机械性能。我们证实，所开发的ANN势函数能够再现与第一性原理计算一致的SiC、Si和C单晶的典型材料特性。我们还通过分析径向分布函数验证了所开发的ANN势对非晶SiC模拟的适用性。所开发的ANN势应用于非晶SiC模型的一系列蠕变试验，重点关注预计会在基于SiC的复合材料中形成的非晶相。结果，我们观察到由于取决于应变率的不同原子机制而导致的两种蠕变行为。评估的活化能低于文献中的实验值。这一结果表明，非晶区域在SiC复合材料的蠕变过程中可能起重要作用。
