Infrared-Driven Charge-Transfer in Transition Metal-Containing B<sub>12</sub>X<sub>12</sub><sup>2–</sup> (X = H, F) Clusters
Bibliographic record
Abstract
Density functional theory (DFT) calculations and infrared multiple photon dissociation (IRMPD) spectroscopy are employed to probe [TM·(B 12 H 12 )] − and [TM·(B 12 H 12 ) 2 ] 2– clusters [TM = Ag(I), Cu(I), Co(II), Ni(II), Zn(II), Cd(II)]. A comparison is made between the charge-transfer properties of the clusters containing the hydrogenated dodecaborate dianions, B 12 H 12 2–, and the fluorinated analogues, B 12 F 12 2–, for clusters containing Cd(II), Co(II), Ni(II), and Zn(II). IRMPD of the [TM·(B 12 H 12 )] − and [TM·(B 12 H 12 ) 2 ] 2– species yields B 12 H 11 – via hydride abstraction and B 12 H 12 – in all cases. To further explore the IR-induced charge-transfer properties of the B 12 X 12 2– (X = H, F) cages, mixed-cage [TM(B 12 H 12 )(B 12 F 12 )] 2– [TM = Co(II), Ni(II), Zn(II), Cd(II)] clusters were investigated. IRMPD of the mixed-cage species yielded appreciable amounts of B 12 F 12 – and B 12 H 12 – in most cases, indicating that charge-transfer to the central TM cation is a favorable process; formation of B 12 F 12 – is the dominant process for the Co(II) and Ni(II) mixed-cage complexes. In contrast, the Zn(II) and Cd(II) mixed-cage complexes preferentially produced fragments of the form B x H y F z –/2–, suggesting that H/F scrambling and/or fusion of the boron cages occurs along the IRMPD pathway.
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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".