Topological descriptor of thermal conductivity in amorphous Si

Quantifying the correlation between the complex structures of amorphous materials and their physical properties has been a longstanding problem in materials science. In amorphous Si, a representative covalent amorphous solid, the presence of a medium-range order (MRO) has been intensively discussed. However, the specific atomic arrangement corresponding to the MRO and its relationship with physical properties, such as thermal conductivity, remains elusive. We solved this problem by combining topological data analysis, machine learning, and molecular dynamics simulations. Using persistent homology, we constructed a topological descriptor that can predict thermal conductivity. Moreover, from the inverse analysis of the descriptor, we determined the typical ring features correlated with both the thermal conductivity and MRO. The results could provide an avenue for controlling material characteristics through the topology of the nanostructures. (C) 2022 Author(s).

Automated summary

This study addresses the long-standing problem of quantifying the correlation between complex structures of amorphous materials and their physical properties. By combining topological data analysis, machine learning, and molecular dynamics simulations, the researchers were able to determine the relationship between the medium-range order (MRO) in amorphous Si and its thermal conductivity. The results provide a potential avenue for controlling material characteristics through the topology of nanostructures.