Making sense out of sulfated tin dioxide mesostructures
Bibliographic record
Abstract
An in-depth investigation into the synthesis, characterization and sensor response of mesoporous SnO2 materials formed utilizing tin(IV) chloride, sodium dodecylsulfonate, and urea is described. The structures have been stabilized towards calcination by increasing the condensation of the tin oxide network utilizing urea as a slow-release base. PXRD, FT-Raman, N2 gas adsorption, thermal gravimetric analysis, and pyrolysis mass spectroscopy were used to monitor the two-step surfactant decomposition in which a sulfated tin oxide surface is formed followed by removal of the sulfate groups at elevated calcination temperatures. In situ a.c. impedance measurements of the materials in dry air and 2000 ppm carbon monoxide showed that the sensitivity of these materials towards carbon monoxide was inhibited by the presence of sulfate groups on the surface, whereas after the sulfate groups were removed the materials became much more sensitive towards carbon monoxide. These materials could find promising applications as gas-selective chemical sensors, super-acid catalysts, and anode materials for lithium battery applications.
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How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".