Preprint

FZJ-2026-02079

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Tailoring spontaneous symmetry breaking in engineered van der Waals superlattices

Jin, K. (First author)FZJ* ; Klebl, L. ; Goodwin, Z. A. H. ; Zhao, J. ; Lüpke, F.FZJ* ; Kennes, D. M. ; Martinez-Castro, J.FZJ* ; Ternes, M. (Corresponding author)FZJ*

2026
arXiv

This record in other databases:  

Please use a persistent id in citations: doi:10.48550/ARXIV.2603.15787  doi:10.48550/arXiv.2603.15787

Abstract: Superlattice engineering in van der Waals heterostructures (e.\,g.\ by moiré engineering) provides a powerful platform for designing electronic bands and realising correlated and topological quantum phenomena. Here, we pioneer a scheme to tailor superpotentials based on intrinsic substrate electronic orders. We show that this establishes a robust, self-aligned, and highly versatile route to band-structure control as we demonstrate in graphene by engineering two distinct, nearly commensurate superlattices using the charge density waves of 1T-NbSe$_2$. In these superlattices the graphene's Dirac cones are folded either to the $Γ$-point or to the K-points of the mini-Brillouin zone. Using scanning tunnelling microscopy, we observe that the $Γ$-folded system preserves C$_3$ symmetry, while the K-folded system exhibits spontaneous symmetry breaking. Combining density functional theory with an interlayer interaction model, we reveal that this difference is not electronically driven but originates from a structural instability. Our work establishes superlattice engineering for designer quantum states and unveils a structural mechanism for controlled emergent symmetry breaking.

Keyword(s): Mesoscale and Nanoscale Physics (cond-mat.mes-hall) ; FOS: Physical sciences

---

Contributing Institute(s):

1. Quantum Nanoscience (PGI-3)

Research Program(s):

1. 5213 - Quantum Nanoscience (POF4-521) (POF4-521)
2. ML4Q - Machine Learning for Quantum (101120240) (101120240)

---