Room-temperature alignment-free magnetometry with boron vacancies in hot-pressed hexagonal boron nitride
Abstract
Abstract Magnetic-field sensing is essential for applications ranging from communication and environmental monitoring to biomedical diagnostics. Quantum sensors based on solid-state spin defects, such as nitrogen-vacancy centers in diamond and boron vacancies (V B - ) in hexagonal boron nitride (hBN), typically require precise alignment between the external magnetic field and the defect spin quantization axis, limiting their practical deployment. Here, we demonstrate room-temperature optically detected magnetic resonance (ODMR) from negatively charged boron vacancies in commercially available hot-pressed polycrystalline hBN. The random orientation of crystallites gives rise to an ensemble of defect quantization axes, enabling magnetic-field detection without the need for precise sensor alignment. The resulting orientation-averaged ODMR response exhibits broadened linewidths and reduced contrast compared with single-crystal hBN, while retaining clear magnetic-field-dependent signatures. Numerical simulations incorporating hyperfine interactions, anisotropic broadening, and preferential defect alignment accurately reproduce the experimental ODMR spectra across different magnetic-field strengths and orientations. Although the ensemble response does not permit unambiguous reconstruction of the magnetic-field vector, it enables robust alignment-free (scalar) magnetometry under ambient conditions. These results establish hot-pressed polycrystalline hBN as a scalable platform for room-temperature quantum magnetic-field sensing and highlight the potential of disordered spin ensembles for practical quantum sensing applications.
Fields of Study & Subjects
Diamond and Carbon-based Materials Research
Graphene research and applications
Boron and Carbon Nanomaterials Research
Publication details
- Journal / source
- Communications Materials
- Publisher
- Springer Science and Business Media LLC
- Volume
- 7
- Issue
- 1
- Publication date
- 12 August 2026
- Language
- EN