Quick Navigation
Topics
Trapped Ion Quantum Computing
Non-radiative energy transfer between boron vacancies in hexagonal boron nitride and other 2D materials
arXiv
Authors: Fraunié Jules, Mikhail M. Glazov, Sébastien Roux, Abraao Cefas Torres-Dias, Cora Crunteanu-Stanescu, Tom Fournier, Maryam S. Dehaghani, Tristan Clua-Provost, Delphine Lagarde, Laurent Lombez, Xavier Marie, Benjamin Lassagne, Thomas Poirier, James H. Edgar, Vincent Jacques, Cedric Robert
Year
2025
Paper ID
16244
Status
Preprint
Abstract Read
~2 min
Abstract Words
121
Citations
N/A
Abstract
Boron vacancies $VB^-$ in hexagonal boron nitride (hBN) have emerged as a promising platform for two-dimensional quantum sensors capable of operating at atomic-scale proximity. However, the mechanisms responsible for photoluminescence quenching in thin hBN sensing layers when placed in contact with absorptive materials remain largely unexplored. In this Letter, we investigate non-radiative Förster resonance energy transfer (FRET) between VB^- centers and either monolayer graphene or 2D semiconductors. Strikingly, we find that the FRET rate is negligible for hBN sensing layers thicker than 3 nm, highlighting the potential of VB^- centers for integration into ultra-thin quantum sensors within van der Waals heterostructures. Furthermore, we experimentally extract the intrinsic radiative decay rate of VB^- defects.
Why This Paper Matters
- This paper contributes to the Trapped-Ion Quantum Computing research area in the Quantum Articles archive.
- It adds a 2025 reference point for readers tracking recent quantum research.
- Boron vacancies VB^- in hexagonal boron nitride (hBN) have emerged as a promising platform for two-dimensional quantum sensors capable of operating at atomic-scale proximity.
Paper Tools
Become a member to use research tools
Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.
Show Paper arXiv Publisher Share
Cite This Paper
Copy URL
Compare
Copy DOI Add to Reading List
Category Correction Request
Category Correction Request
Help us improve classification quality by proposing a better category. Every request is reviewed by an admin.
Sign in to submit a category correction request for this paper.
Log In to SubmitReferences & Citation Signals
Community Reactions
Quick sentiment from readers on this paper.
Score:
0
Likes: 0
Dislikes: 0
Sign in to react to this paper.
Discussion & Reviews (Moderated)
Average Rating: 0.0 / 5 (0 ratings)
No written reviews yet.