Revealing an Unexpected Chemical Reactivity of Boron Nitride to H <sub>2</sub> O and Alkane Molecules
Herein, substantial experimental evidence reveals the unexpected chemical reactivity of inert hexagonal boron nitride (<i>h</i>-BN) to H<sub>2</sub>O, CH<sub>4</sub>, and C<sub>2</sub>H<sub>6</sub> under mild conditions. H<sub>2</sub>O molecules dissociate at B-N edge sites and insert into the B-N bond even under ambient conditions. Detailed spectroscopic characterization shows this process protonates nitrogen sites and hydroxylates boron sites, forming N-H and B-OH groups. Ultimately, the NH<sub>4</sub><sup>+</sup> and B(OH)<sub>4</sub><sup>-</sup> ions are released into water as the final products of nitrogen protonation and boron hydroxylation. This reactivity is significantly enhanced at the oxygen-doped B-N edges. Theoretical simulations reveal that strong orbital interactions between the H (1s) orbitals of H<sub>2</sub>O and the B (2p)/N (2p) orbitals of the B-N edge produce significant chemical stress at the adsorption sites, promoting the dissociation and subsequent insertion of H<sub>2</sub>O into the B-N bonds. Furthermore, we show that CH<sub>4</sub> and C<sub>2</sub>H<sub>6</sub> can be oxidized to CO and trace CH<sub>3</sub>OH in water over boron nitride at mild temperatures without an additional oxidant. The <sup>18</sup>O isotope-tracing experiment confirms that the oxygen in the boron nitride matrix is responsible for the activation and oxidation of the C-H bond of CH<sub>4</sub> and C<sub>2</sub>H<sub>6</sub>. Simultaneously, the released NH<sub>4</sub><sup>+</sup> and B(OH)<sub>4</sub><sup>-</sup> ions provide a reaction microenvironment enabling the thermodynamically spontaneous hydration of formed CO to formate. These findings fundamentally challenge the long-standing paradigm of <i>h</i>-BN as a chemically inert material under mild conditions.
Authors
- Lei Hua (ORCID: https://orcid.org/0000-0002-2696-3521)
- Zhankai Liu (ORCID: https://orcid.org/0000-0003-0115-5867)
- An‐Hui Lu (ORCID: https://orcid.org/0000-0003-1294-5928)
- Jie Fan (ORCID: https://orcid.org/0000-0002-8380-6338)
- Wen‐Cui Li (ORCID: https://orcid.org/0000-0001-8066-7144)
- Yuenan Zheng (ORCID: https://orcid.org/0009-0006-8950-2251)
- Weixi Chen (ORCID: https://orcid.org/0009-0003-7758-370X)
- Jichun Jiang
- Dongqi Wang (ORCID: https://orcid.org/0000-0001-9415-1173)
- Yifan Zhang (ORCID: https://orcid.org/0000-0002-8977-0305)
- Lei He
Institutions
- Dalian Institute of Chemical Physics (CN)
- Chinese Academy of Sciences (CN)
- Dalian University of Technology (CN)
- Dalian University (CN)
Publication Details
- Journal
- Journal of the American Chemical Society
- Published
- 2025-10-22
- DOI
- https://doi.org/10.1021/jacs.5c14440
- Citations
- 3
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 1.55