Morphology and photocatalytic performance of nano‐sized TiO <sub>2</sub> prepared by simple hydrothermal method with different pH values
Bibliographic record
Abstract
Abstract pH value is a key factor in the preparation of nano‐sized TiO 2 with hydrothermal method. Using Ti(SO 4 ) 2 as the titanium source, H 2 O 2 as the complexing agent, NaOH and HCl as the pH value regulator, nano‐sized TiO 2 powder with various morphologies and sizes was synthesized. Changes in morphology, size and phase type with pH values of samples were characterized by X‐ray diffraction (XRD) and transmission electron microscopy (TEM) measurements. Results show that under the present preparation conditions, TiO 2 powder is an anatase phase with pH value less than 11, but is more likely to be a brookite phase with pH value more than 11. With the increase in pH value from 1 to 11 in hydrothermal environment, nano‐sized anatase TiO 2 gradually grows up in all directions. {001}, {101} and {100} groups of crystal plane are the exposed crystal planes of nano‐sized anatase TiO 2 for the (004), (101) and (200) facets found in high‐resolution TEM image. The photocatalytic performance of nano‐sized TiO 2 with different morphologies was compared by measuring their photocatalytic degradation rates for methylene blue under ultraviolet light. Results show that anatase TiO 2 prepared under the alkalescent hydrothermal environment (pH = 9, 11) has a better photocatalytic degrading performance. Different sizes and phases of nanoscaled TiO 2 powders with different photocatalytic performances can be prepared by the control of pH value of hydrothermal solutions.
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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) | 0.000 | 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 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".