Nanosilver Particle Formation on a High Surface Area Titanate
Bibliographic record
Abstract
Titanium based molecular sieves, such as ETS-10, have the ability to exchange silver ions and subsequently support self assembly of stable silver nanoparticles when heated. We report that a high surface area sodium titanate (resembling ETS-2) displays a similar ability to self template silver nanoparticles on its surface. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) show high concentrations of silver nanoparticles on the surface of this sodium titanate, formed by thermal reduction of exchanged silver cations. The nanoparticles range in size from 4 to 12 nm, centered at around 6 nm. In addition to SEM and TEM, XRD and surface area analysis were used to characterize the material. The results indicate that this sodium titanate has a high surface area (>263 m2/g), and high ion exchange capacity for silver (30+ wt%) making it an excellent substrate for the exchange and generation of uniform, high-density silver nanoparticles.
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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".