FABRICATING WELL-DISPERSED NANOSIZED GOLD CATALYST ON TITANATE NANOWIRES SURFACE FOR 4-NITROPHENOL REDUCTION
Bibliographic record
Abstract
In this paper, homogenous gold nanoparticles ( AuNPs ) with a high density and a narrow size distribution were successfully fabricated on titanate nanowires (TNWs) scaffolds in the absence of organic capping agents. An ameliorated low-temperature hydrothermal method was used to prepare the TNWs scaffolds like bird's nest on the Ti substrate, and the nanowires diameter was about 30–80nm. Then, AuNPs were synthesized on the TNWs scaffolds with a deposition–precipitation urea (DPU) method. The TEM and XRD measurements indicated that well-crystallized face-centered cubic (fcc) AuNPs were homogeneously dispersed on TNWs, and AuNPs with average sizes of 2.7 nm and 4 nm were obtained, respectively for the theoretical gold loading 5 wt.% and 8 wt.%. Inspiringly, the 8%- AuNPs /TNWs catalyst could reduce 4-nitrophenol (4-NP) to 4-aminophenol (4-AP) within 210 s, and exhibited better catalytic reduction performance than that of 5%- AuNPs /TNWs.
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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".