Complex network science has contributed to extracting essential parameters from network structure and has been applied in social, geographical, computer, and biological sciences. On the other hand, in materials science, some materials possess a network structure that determines their properties. Because both connectivity and spatial distance are significant factors in materials, utilizing a combined descriptor to explain their properties could be important. In this study, we demonstrate that the descriptor with both connectivity and spatial distance prior to elongations universally represented some parameters related to mechanical properties during elongation, which enabled us to interpret the role of each node. Recently, there have been significant attempts to develop new materials by methods in data science such as materials informatics. Thus, our approaches could contribute in the future to the development of materials with network structures in an interpretable manner.
All Science Journal Classification (ASJC) codes
- Decision Sciences(all)