5 papers
Emergent Noncollinearity and Near-Degenerate Magnetic Superlattices in AT6X6 Kagome Metals
Weiyi Xia, Wei-Shen Tee, Peter Minch +3
Ferromagnetic AT6X6 Kagome compounds are a popular class of systems in which quantum magnetism with topological features has been observed. These systems allow easy chemical substi…
Discovery of novel magnetic Y-Mn-B compounds via advanced machine learning guided framework
Weiyi Xia, Wei Shen Tee, Maxim Moraru +2
Rare-earth transition-metal borides offer critical structural motifs for permanent-magnet design; however, the manganese-rich regions within these compositional phase spaces remain…
Antiferromagnetic Phases in Zr-Fe-Ge Kagome Systems
Peter Minch, Shiya Chen, Weiyi Xia +4
A wide variety of chemical substitutions in ferromagnetic Kagome systems can lead to diverse magnetic phases with electronic structures suitable for topological or quantum material…
Machine learning accelerated prediction of Ce-based ternary compounds involving antagonistic pairs
Weiyi Xia, Wei-Shen Tee, Paul C. Canfield +6
The discovery of novel quantum materials within ternary phase spaces containing antagonistic pair such as Fe with Bi, Pb, In, and Ag, presents significant challenges yet holds grea…
Search for stable and low-energy Ce-Co-Cu ternary compounds using machine learning
Weiyi Xia, Wei-Shen Tee, Paul Canfield +2
Cerium-based intermetallics have garnered significant research attention as potential new permanent magnets. In this study, we explore the compositional and structural landscape of…