Simple Protocol for Generating TiO<sub>2</sub> Nanofibers in Organic Media
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Titania nanofibers in high yields can be accessed by treating titanium isopropoxide (Ti(O i Pr) 4 ) with acetic acid (AcOH) in heptanes when R ≥ 4.2, where R = mol of AcOH/mol of Ti(O i Pr) 4 . Electron microscopic (SEM and TEM) images of the samples confirmed that high-aspect-ratio nanofibers with diameters in the 10−20 nm range are produced under these conditions, whereas agglomerated spherical nanoparticles are produced at R ≤ 3.8. Powder X-ray diffraction and UV-vis data confirm the anatase crystalline phase after calcination at 400 °C, with the progressive formation of the rutile phase upon heating to higher temperatures. N 2 physisorption analyses showed the calcined fibers prepared at R = 5.5 have surface areas of 95 m 2 /g. The self-assembly pathway leading to the nanofibers was delineated by in situ attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy in tandem with electrospray ionization mass spectrometry (ESI-MS). It was found that the hexanuclear building block, Ti 6 O 6 (OAc) 6 (O i Pr) 6 ( TAC1 ), is formed during the initial stages of the reactions, and that the axially ligated isopropoxide ligands of this complex are subsequently hydrolyzed to facilitate the one-dimensional condensation of the macromolecules at R ≥ 4.2. Incomplete hydrolysis at lower acid ratios impedes this axial growth, resulting in spherical nanoparticles.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it