Solid-State <sup>23</sup>Na and <sup>7</sup>Li NMR Investigations of Sodium- and Lithium-Reduced Mesoporous Titanium Oxides
Bibliographic record
Abstract
Mesoporous titanium oxide synthesized using a dodecylamine template was treated with 0.2, 0.6, and 1.0 equiv of Li- or Na-naphthalene. The composite materials were characterized by nitrogen adsorption, powder X-ray diffraction, X-ray photoelectron spectroscopy, elemental analysis, thermogravimetric analysis, and solid-state 23Na and 7Li NMR spectroscopy. In all cases the wormhole mesoporosity was retained as evidenced by BET surface areas from 400 to 700 m(2)/g, Horvath-Kawazoe pore sizes in the 20 Angstroms range, and a lack of hysteresis in the nitrogen adsorption isotherms. Variable-temperature conductivity studies show that the Li-reduced materials are semiconductors, with conductivity values 3 orders of magnitude higher than those of the Na-reduced materials. Electrochemical measurements demonstrate reversible intercalation/deintercalation of Li+ ions into pristine mesoporous Ti oxides with good cycling capacity. Solid-state 23Na NMR reveals two distinct Na environments: one corresponding to sodium ions in the mesoporous channels and the other corresponding to sodium ions intercalated into the metal framework. 23Na NMR spectra also indicate that the relative population of the framework site increases with increased reduction levels. Solid-state 7Li NMR spectra display a single broad resonance, which increases in breadth with increased reduction levels, though individual resonances inferring the presence of channel and framework Li species are not resolved. Comparisons of the lithium chemical shifts with published values suggests an "anatase-like structure" with no long-range order in the least-reduced samples but a "lithium titanate-like structure" with no long-range order in the higher reduced materials.
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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".