Ti-coated BC<sub>2</sub>N nanotubes as hydrogen storage materials
Bibliographic record
Abstract
Density functional theory (DFT) calculations have been performed to investigate Ti adsorption on BC2N nanotubes and the hydrogen adsorption capacity of Ti-coated structures. Different adsorption sites have been examined for the Ti adatom, and it is found that the most stable structure has a configuration with alternating columns of carbon and boron–nitrogen hexagons. The DFT calculations indicate that an adsorbed Ti atom on a carbon hexagon can bind four hydrogen molecules in molecular form, while Ti atoms on boron–nitride hexagons can adsorb three hydrogen molecules and two hydrogen atoms. Based on the calculations, the gravimetric efficiency corresponding to decoration of 67% of six carbon rings with Ti adatoms is estimated to be 8 wt %. Computation of the charge transfer reveals that the Ti atom on BC2N is in a cationic state. In addition, Ti adsorption has a significant influence on the electronic structure of the nanotubes and allows for the conversion of nanotubes from semiconductors in the pristine state to conductors upon doping. The interactions between the nanotubes, the Ti atom and hydrogen molecules have also been analyzed using Dewar coordination and Kubas interactions.
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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) | 0.002 | 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".