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Radiative properties of quantum emitters in boron nitride from excited state calculations and Bayesian analysis

Gao, Shiyuan and Chen, Hsiao-Yi and Bernardi, Marco (2021) Radiative properties of quantum emitters in boron nitride from excited state calculations and Bayesian analysis. npj Computational Materials, 7 . Art. No. 85. ISSN 2057-3960. doi:10.1038/s41524-021-00544-2.

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Point defects in hexagonal boron nitride (hBN) have attracted growing attention as bright single-photon emitters. However, understanding of their atomic structure and radiative properties remains incomplete. Here we study the excited states and radiative lifetimes of over 20 native defects and carbon or oxygen impurities in hBN using ab initio density functional theory and GW plus Bethe-Salpeter equation calculations, generating a large data set of their emission energy, polarization and lifetime. We find a wide variability across quantum emitters, with exciton energies ranging from 0.3 to 4 eV and radiative lifetimes from ns to ms for different defect structures. Through a Bayesian statistical analysis, we identify various high-likelihood charge-neutral defect emitters, among which the native VNNB defect is predicted to possess emission energy and radiative lifetime in agreement with experiments. Our work advances the microscopic understanding of hBN single-photon emitters and introduces a computational framework to characterize and identify quantum emitters in 2D materials.

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URLURL TypeDescription Paper
Chen, Hsiao-Yi0000-0003-1962-5767
Bernardi, Marco0000-0001-7289-9666
Alternate Title:Radiative Properties and Excitons of Candidate Defect Emitters in Hexagonal Boron Nitride
Additional Information:© The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit Received 18 November 2020; Accepted 23 April 2021; Published 04 June 2021. We acknowledge valuable discussions with Hamidreza Akbari. This work was supported by the Department of Energy under Grant No. DE-SC0019166. The radiative lifetime code development was partially supported by the National Science Foundation under Grant No. ACI-1642443. H.-Y.C. was partially supported by the J. Yang Fellowship. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231. Data availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Information. Additional data related to this paper may be requested from the authors. Author Contributions: S.G. and M.B. conceived and designed the research. S.G. performed calculation and analysis. H.-Y.C. provided theoretical support. M.B. supervised the entire research project. All authors discussed the results and contributed to the manuscript. The authors declare no competing interests.
Funding AgencyGrant Number
Department of Energy (DOE)DE-SC0019166
J. Yang FellowshipUNSPECIFIED
Department of Energy (DOE)DE-AC02-05CH11231
Subject Keywords:Electronic structure; Nanophotonics and plasmonics; Two-dimensional materials
Record Number:CaltechAUTHORS:20200818-145940249
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Official Citation:Gao, S., Chen, HY. & Bernardi, M. Radiative properties of quantum emitters in boron nitride from excited state calculations and Bayesian analysis. npj Comput Mater 7, 85 (2021).
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:105008
Deposited By: Tony Diaz
Deposited On:18 Aug 2020 22:05
Last Modified:07 Jun 2021 23:12

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