Synthesis and Electrochemistry of Li- and Na-Fulleride Doped Mesoporous Ta Oxides
Bibliographic record
Abstract
A mesoporous tantalum oxide lithium fulleride composite was synthesized by solution intercalation of C 60 into a prefabricated Li-TaTMS material and characterized by elemental analysis, X-ray diffraction (XRD), Raman spectroscopy, nitrogen adsorption−desorption, X-ray photoelectron spectroscopy (XPS), superconducting quantum interference device (SQUID) magnetometry, and solid-state 13 C and 7 Li NMR. The room conductivity measurements of Li fulleride material showed that this material was insulating, as opposed to previously synthesized K and Na based mesoporous Ta oxide fulleride composites with similar composition, which were semiconducting or metallic. Solid-state 7 Li NMR of this lithium composite exhibited a single Li environment. XPS measurements indicated an oxidation of the tantalum oxide walls had occurred upon intercalation of the fullerene 13 C NMR, and Raman measurements were consistent with one fulleride species in the pores. Electrochemical measurements revealed largely irreversible behavior upon intercalation/deintercalation of Li + into this material. This was attributed to the insulating nature of this composite impeding charge transport through the channels. In contrast, the corresponding Na fulleride intercalate showed reversible Li insertion, possibly due to enhanced charge transport through the semiconducting structure.
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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".