Advancing the hBN Defects Database through Photophysical Characterization of Bulk hBN

TL;DR

This work expands the hBN defects database from monolayer-focused ground-state properties to a bulk, excited-state photophysical repository, addressing the mismatch between theory and bulk experiments. Using DFT/Delta-SCF with HSE06, the authors compute ZPLs, PL/absorption spectra, HR and DW factors, radiative lifetimes, and polarization for over 120 neutral defects across charge states −2 to +2 in bulk hBN, storing results in a public SQLite database with a Python API for ML integration. A key finding is that vacancies amplify lattice distortions, elevating the configuration coordinate and HR factor, which broadens phonon sidebands and PSB features, while many other properties remain largely uncorrelated. The dataset and API enable robust defect screening, cross-platform reproducibility, and data-driven discovery, contributing a practical bridge between theory and experiment in solid-state quantum emitters.

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.

Figures (4)

• Figure 1: Overview of the h-bn.info database workflow. The updated database extends our previous work on monolayer hBN by introducing a new feature: bulk hBN defect structures. Investigated defects include native vacancies, substitutional impurities (from groups III–VI), and various complexes, with charge states ranging from –2 to +2. For each defect, the most stable charge and spin configurations are identified. Ground-state properties such as defect formation energies and electronic structures are computed, followed by excited-state properties including ZPL, PL and absorption spectra, configuration coordinates, HR and DW factors, radiative lifetimes, and transition dipole polarizations. All data are compiled into a structured database with an accessible API supporting Python-based queries for integration with ML and data-driven research workflows. The color scheme is defined as follows: blue blocks represent features available only for bulk, while yellow blocks represent features available for both bulk and monolayer.
• Figure 2: Correlation matrix based on the Spearman rank correlation method among 17 properties. High absolute values indicate strong correlations, while values close to zero imply weak or no correlation. Positive values represent increasing relationships between property pairs, whereas negative values indicate inverse relationships.
• Figure 3: (a) Correlation between configuration coordinate and HR factor. (b) and (c) show histograms of the configuration coordinate between 0 and 2.5 amu$^{1/2}$Å and HR factor between 0 and 10, respectively. Defect types are color-coded as follows: blue for single-impurity defects without vacancies; purple for vacancy-free defect complexes (comprising multiple impurities); red for defects with a single vacancy; and green for defects with two vacancies. (d) displays selected but representative PL lineshapes categorized by the number of vacancies in each defect. The color stripe indicates the corresponding HR factor range for each defect category.
• Figure 4: (a) Distribution of ZPL energies. (b) Distribution of polarization misalignment angles. (c) Distribution of radiative lifetimes. Blue bins (0V) represent single-impurity defects without vacancies; purple bins (0V) represent vacancy-free defect complexes (containing more than two impurities); red bins (1V) correspond to defects with one vacancy; and green bins (2V) represent defects containing two vacancies.