Advancing the hBN defects database through photophysical characterization of bulk hBN
Issued Date
2025-01-01
Resource Type
ISSN
20507526
eISSN
20507534
Scopus ID
2-s2.0-105018787898
Journal Title
Journal of Materials Chemistry C
Rights Holder(s)
SCOPUS
Bibliographic Citation
Journal of Materials Chemistry C (2025)
Suggested Citation
Cholsuk C., Suwanna S., Vogl T. Advancing the hBN defects database through photophysical characterization of bulk hBN. Journal of Materials Chemistry C (2025). doi:10.1039/d5tc02805a Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/112708
Title
Advancing the hBN defects database through photophysical characterization of bulk hBN
Author(s)
Corresponding Author(s)
Other Contributor(s)
Abstract
Quantum emitters in hexagonal boron nitride (hBN) have gained significant attention due to a wide range of defects that offer high quantum efficiency and single-photon purity at room temperature. Most theoretical studies on hBN defects simulate monolayers, as this is computationally cheaper than calculating bulk structures. However, most experimental studies are carried out on multilayer to bulk hBN, which creates additional possibilities for discrepancies between theory and experiment. In this work, we present an extended database of hBN defects that includes a comprehensive set of bulk hBN defects along with their excited-state photophysical properties. The database features over 120 neutral defects, systematically evaluated across charge states ranging from −2 to +2 (600 defects in total). For each defect, the most stable charge and spin configurations are identified and used to compute the zero-phonon line, photoluminescence spectrum, absorption spectrum, Huang-Rhys (HR) factor, interactive radiative lifetimes, transition dipole moments, and polarization characteristics. Our analysis reveals that the electron-phonon coupling strength is primarily influenced by the presence of vacancies, which tend to induce stronger lattice distortions and broaden phonon sidebands. Additionally, correlation analysis shows that while most properties are independent, the HR factor strongly correlates with the configuration coordinates. All data are publicly available at https://h-bn.info, along with a new application programming interface (API) to facilitate integration with machine learning workflows. This database is therefore designed to bridge the gap between theory and experiment, aid in the reliable identification of quantum emitters, and support the development of machine-learning-driven approaches in quantum materials research.