Bibliographic record
Abstract
The hypothetical spinel carbon nitride (γ-C3N4) has received a large amount of attention due to its predicted hardness being comparable to that of diamond. The group 14 spinel binary nitrides that have been synthesized are limited so far to: γ-Si3N4, γ-Ge3N4 and γ-Sn3N4. However, there still remains significant interest in γ-C3N4 in the hope that it will eventually be synthesized, but there are no successful reports, thus making the study of γ-C3N4 strictly theoretical. Through an empirical relationship that correlates hardness, crystal structure and the electronic band gap, we examine a series of group 14 spinel nitrides: γ-C3N4 γ-Si3N4, γ-Ge3N4 and γ-Sn3N4, as well as their ternary compounds. The hardness and electronic band gap of these materials are calculated using ab initio density functional theory. These results show that in the case of the solid solutions, γ-(Si,Ge)3N4 and γ-(Ge,Sn)3N4, the tetrahedral site is filled first by the larger cation, Ge and Sn, respectively. Furthermore, the deviation of carbon containing group 14 spinel nitrides from the expected hardness and bandgap trend suggests that γ-Si3N4 may remain the hardest known group 14 spinel nitride. Additionally, an improved method to calculate the hardness using the nitrogen bonding tetrahedron provides more unambiguous results and the trend of the hardness agrees with experimental measurements.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".