Tailoring hydrogen adsorption and desorption properties of Li-doped SV (single vacancy) monolayer <i>h</i>-BN systems using ab initio calculations
Bibliographic record
Abstract
This study uses density functional theory (DFT) technique to examine the hydrogen molecules (H2) storage on Li-decorated h-BN monolayer. The results of DFT have proven that Li-doped h-BN system can hold up to 9H2 with the adsorption energy lying in between −0.31 eV and −0.24 eV/H2 at ambient condition. However, the calculated average adsorption energy for 9H2 is −0.240 eV/H2 with hydrogen storage capacity of 5.96 wt.%, which is according to the United States Department of Energy. Partial density of state was computed for each configuration to provide additional justifications for the H2 storage on Li-doped h-BN monolayer. The hybridization shows a significant interaction between H2 and Li atom, and most of their hybrid peaks were observed in the energy range from −7.5 to −1 eV. Moreover, the H2 desorption simulations achieved via the ab initio molecular dynamics. The computed desorption temperature TD is 306 °K, which is a suitable operating temperature. Hence, our research demonstrates that Li-doped h-BN is a thermally stable and viable hydrogen storage material for hydrogen storage systems.
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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".