Unveiling the Miniband Structure of Graphene Moir\'e Superlattices via Gate-dependent Terahertz Photocurrent Spectroscopy
Juan A. Delgado-Notario, Stephen R. Power, Wojciech Knap, Manuel Pino, JinLuo Cheng, Daniel Vaquero, Takashi Taniguchi, Kenji Watanabe, Jes\'us E. Vel\'azquez-P\'erez, Yahya M. Meziani, Pablo Alonso-Gonz\'alez, Jos\'e M. Caridad

TL;DR
This study introduces gate-dependent terahertz photocurrent spectroscopy to probe and quantify the complex electronic miniband structure of graphene moiré superlattices, revealing tiny energy gaps and optoelectronic responses linked to Berry phase effects.
Contribution
The paper demonstrates a novel spectroscopic technique to detect and analyze intricate miniband features in graphene moiré superlattices, providing insights inaccessible by traditional methods.
Findings
Detection of avoided band crossings and tiny energy gaps (~1-20 meV)
Observation of enhanced responsivities in off-resonance regimes
Identification of bulk photocurrents related to Berry phase effects
Abstract
Moir\'e superlattices formed at the interface between stacked two-dimensional atomic crystals offer limitless opportunities to design materials with widely tunable properties and engineer intriguing quantum phases of matter. However, despite progress, precise probing of the electronic states and tantalizingly complex band textures of these systems remain challenging. Here, we present gate-dependent terahertz photocurrent spectroscopy as a robust technique to detect, explore and quantify intricate electronic properties in graphene moir\'e superlattices. Specifically, using terahertz light at different frequencies, we demonstrate distinct photocurrent regimes evidencing the presence of avoided band crossings and tiny (~1-20 meV) inversion-breaking global and local energy gaps in the miniband structure of minimally twisted graphene and hexagonal boron nitride heterostructures, key…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
