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Artificial Intelligence for High-Throughput Discovery of Topological Insulators: the Example of Alloyed Tetradymites
Guohua Cao, Runhai Ouyang, Luca M. Ghiringhelli +4
Significant advances have been made in predicting new topological materials using high-throughput empirical descriptors or symmetry-based indicators. To date, these approaches have…
Analysis of Topological Transitions in Two-dimensional Materials by Compressed Sensing
Carlos Mera Acosta, Runhai Ouyang, Adalberto Fazzio +3
Quantum spin-Hall insulators (QSHIs), i.e., two-dimensional topological insulators (TIs) with a symmetry-protected band inversion, have attracted considerable scientific interest i…
New Tolerance Factor to Predict the Stability of Perovskite Oxides and Halides
Christopher J. Bartel, Christopher Sutton, Bryan R. Goldsmith +4
Predicting the stability of the perovskite structure remains a longstanding challenge for the discovery of new functional materials for many applications including photovoltaics an…