High-Energy Density and Superhard Nitrogen-Rich B-N Compounds
Bibliographic record
Abstract
The pressure-induced transformation of diatomic nitrogen into nonmolecular polymeric phases may produce potentially useful high-energy-density materials. We combine first-principles calculations with structure searching to predict a new class of nitrogen-rich boron nitrides with a stoichiometry of ${\mathrm{B}}_{3}{\mathrm{N}}_{5}$ that are stable or metastable relative to solid ${\mathrm{N}}_{2}$ and $h$-BN at ambient pressure. The most stable phase at ambient pressure has a layered structure ($h{\text{\ensuremath{-}}\mathrm{B}}_{3}{\mathrm{N}}_{5}$) containing hexagonal ${\mathrm{B}}_{3}{\mathrm{N}}_{3}$ layers sandwiched with intercalated freely rotating ${\mathrm{N}}_{2}$ molecules. At 15 GPa, a three-dimensional $C22{2}_{1}$ structure with single N-N bonds becomes the most stable. This pressure is much lower than that required for triple-to-single bond transformation in pure solid nitrogen (110 GPa). More importantly, $C22{2}_{1}\text{\ensuremath{-}}{\mathrm{B}}_{3}{\mathrm{N}}_{5}$ is metastable, and can be recovered under ambient conditions. Its energy density of $\ensuremath{\sim}3.44\text{ }\text{ }\mathrm{kJ}/\mathrm{g}$ makes it a potential high-energy-density material. In addition, stress-strain calculations estimate a Vicker's hardness of $\ensuremath{\sim}44\text{ }\text{ }\mathrm{GPa}$. Structure searching reveals a new clathrate sodalitelike BN structure that is metastable under ambient conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".