Enhanced Hydrogen Storage Properties of LiAlH<sub>4</sub> by Excellent Catalytic Activity of XTiO<sub>3</sub>@<i>h</i>‐BN (X = Co, Ni)
Bibliographic record
Abstract
Abstract The high desorption temperature and slow kinetics still restrict the applications of LiAlH 4 in hydrogen storage. To solve the above problems, NiTiO 3 @ h ‐BN and CoTiO 3 @ h ‐BN prepared for the first time are introduced into LiAlH 4 by ball milling. LiAlH 4 doped with 7 wt% NiTiO 3 @ h ‐BN, selected as an optimal doping sample, starts to release hydrogen at 68.1 °C, and the total amount of hydrogen released is 7.11 wt% below 300 °C. The activation energies ( E a ) of the two‐step hydrogen release reactions are 55.93 and 59.25 kJ∙mol −1 , which are 45.8% and 69.0% lower than those of as‐received LiAlH 4 , respectively. Under 30 bar hydrogen pressure and 300 °C constant temperature, LiAlH 4 doped with 7 wt% NiTiO 3 @ h ‐BN after dehydrogenation can absorb ≈1.05 wt% hydrogen. Based on density functional theory calculations, AlNi 3 and NiTi, in situ formed nanoparticles during ball milling, can decrease the desorption energy barrier of AlH bonding in LiAlH 4 and accelerate the breakdown of AlH bonding due to the interfacial charge transfer and the dehybridization. Furthermore, NiTi can enhance the adsorption and splitting of H 2 , promoting the activation of H 2 molecules during the rehydrogenation process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".