Electronic Properties and Solid-State <sup>87</sup>Rb and <sup>13</sup>C NMR Studies of Mesoporous Tantalum Oxide Rubidium Fulleride Composites
Bibliographic record
Abstract
Mesoporous tantalum oxide rubidium fulleride composites were synthesized by solution impregnation and characterized by elemental analysis, X-ray diffraction, Raman spectroscopy, nitrogen adsorption/desorption, X-ray photoelectron spectroscopy, superconducting quantum interference device magnetometry, room- and variable-temperature electron transport measurements, and solid-state 87 Rb and 13 C NMR. The room-temperature conductivity pattern, as a function of the oxidation state of C 60 n -, displayed a conductivity minimum at n = 3.0 and a single maximum at n = 4.0, while variable-temperature conductivity measurements indicated that the n = 1.0 composite is a semiconductor and the n = 4.0 material is a narrow band gap semiconductor or a semimetal. Solid-state 87 Rb NMR of the composite materials indicated the presence of two Rb environments associated with the walls or channels of the mesostructure as well as several resonances associated with various fulleride species. The n = 3.0 and n = 4.0 samples showed a substantial increase of Rb ions confined into the walls of mesostructure as well as the buildup of a Rb environment associated with a fulleride species. Solid-state 13 C NMR experiments showed the presence of multiple fulleride species as well as pure fullerene, depending on the level of reduction.
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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".