A general procedure to synthesize highly crystalline metal oxide and mixed oxide nanocrystals in aqueous medium and photocatalytic activity of metal/oxide nanohybrids
Bibliographic record
Abstract
A conventional and general route has been exploited to the high yield synthesis of many kinds of highly crystalline metal oxide and mixed oxide nanocrystals with different morphologies including belt, rod, truncated-octahedron, cubic, sphere, sheet via the hydrothermal reaction of inorganic precursors in aqueous solution in the presence of bifunctional 6-aminohexanoic acid (AHA) molecules as a capping agent. This method is a simple, reproducible and general route for the preparation of a variety of high-crystalline inorganic nanocrystals in scale-up. The shape of inorganic nanocrystals such as CoWO(4), La(2)(MoO(4))(3) can be controlled by simply adjusting the synthesis conditions including pH solution and reaction temperature. Further, by tuning precursor monomer concentration, the mesocrystal hierarchical aggregated microspheres (e.g., MnWO(4), La(2)(MoO(4))(3)) can be achieved, due to the spontaneous assembly of individual AHA-capped nanoparticles. These obtained AHA-capped nanocrystals are excellent supports for the synthesis of a variety of hybrid metal/oxide nanocrystals in which noble metal particles are uniformly deposited on the surface of each individual nanosupport. The photocatalytic activity of Ag/TiO(2) nanobelts as a typical hybrid photocatalyst sample for Methylene Blue degradation was also studied.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".