Unusual Conductivity Patterns in Reduced Mesoporous Titanium, Niobium, and Tantalum Oxides with One-Dimensional Potassium Fulleride Wires in the Channels
Bibliographic record
Abstract
Recent results in our group demonstrated that K n C 60 ( n = 3), a much-studied superconductor and molecular metal, can be encapsulated in the channels of mesoporous niobium oxide to make pseudo-one-dimensional alkali fulleride wires. The oxidation state of the encapsulated fulleride phase can be tuned by addition of potassium naphthalene to the mesostructured composite. Surprisingly, the conductivity of this series of composites has maxima at n = 2.6 and n = 4.1, rather than n = 3 as in the bulk material. In this work, we report a study on the effect of changing the pore size and wall composition of the mesoporous host lattice on the conductivity and electronic behavior of the corresponding potassium fulleride composites. Samples of mesoporous niobium oxide with a 32-Å pore size, mesoporous tantalum oxide with a 22-Å pore size, and mesoporous titanium oxide with a 22-Å pore size were treated with K 3 C 60 and characterized by elemental analysis, nitrogen adsorption, X-ray diffraction (XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), electron spin resonance spectroscopy (ESR), and superconducting quantum interference device (SQUID) magnetometry. These materials were then further reduced with small aliquots of potassium naphthalene in sequential steps up to a fulleride oxidation state of n = 4.5, and each material was fully characterized as described above. For each series of materials, two conductivity maxima were observed, the first at approximately n = 2.5 and the second at roughly n = 4.0, indicating that this double-maxima behavior is general to other one-dimensional alkali fulleride mesostructures. There was no clear pattern in the effect of changing pore size and wall composition on the electronic properties; however, all materials near n = 4.0 showed a greater degree of reduction of the mesostructure and a greater density of states near the Fermi level as determined by XPS, consistent with the high levels of conductivity of the fulleride at this oxidation state.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".