The Kubas interaction in M(ii) (M = Ti, V, Cr) hydrazine-based hydrogen storage materials: a DFT study
Bibliographic record
Abstract
The Cr(II) binding sites of an experimentally realised hydrazine linked hydrogen storage material have been studied computationally using density functional theory. Both the experimentally determined rise in H(2) binding enthalpy upon alteration of the ancillary ligand from bis[(trimethylsilyl)methyl] to hydride, and the number of H(2) molecules per Cr centre, are reproduced reasonably well. Comparison with analogous Ti(II), V(II) and Mn(II) systems suggests that future experiments should focus on the earliest 3d metals, and also suggests that 5 and 7 wt% H(2) storage may be possible for V(II) and Ti(II) respectively. Alteration of the metal does not have a large effect on the M-H(2) interaction energy, while alteration of the ancillary ligand bound to the metal centre, from bis[(trimethylsilyl)methyl] or hydride to two hydride ligands, THF and only hydrazine based ligands, indicates that ancillary ligands that are poor π-acceptors give stronger M-H(2) interactions. Good evidence is found that the M-H(2) interaction is Kubas type. Orbitals showing σ-donation from H(2) to the metal and π-back-donation from the metal to the dihydrogen are identified, and atoms-in-molecules analysis indicates that the electron density at the bond critical points of the bound H(2) is similar to that of classical Kubas systems. The Kubas interaction is dominated by σ-donation from the H(2) to the metal for Cr(II), but is more balanced between σ-donation and π-back-donation for the Ti(II) and V(II) analogues. This difference in behaviour is traced to a lowering in energy of the metal 3d orbitals across the transition series.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".