Facile synthesis of thermally stable anatase titania with a high-surface area and tailored pore sizes
Bibliographic record
Abstract
Abstract Both affordability and stability are important for commercial-scale production and industrial applications of TiO2. In addition, the ability to tailor nanostructure and physicochemical properties can provide advantages for future applications. Herein a facile sol‒gel process was investigated by using titanyl sulfate as an inexpensive feedstock reacting with water in the media of acetic acid and isopropanol. An anatase phase was readily produced at 65 °C, followed by drying at 80 °C. The anatase was stable up to 800 °C due to the residual sulfate and nitrogen, where sulfate and ammonium slowly decomposed when heating beyond 400 °C. The monolithic TiO2 xerogels were composed of agglomerated TiO2 spherical particles with diameters of ca. 50 or 100 nm. The TiO2 spherical particles were built by anatase crystallites with a diameter of ca. 5 nm. As a result, the TiO2 exhibited both bimodal mesopores and macropores: Large mesopores (10‒30 nm) were present due to the void spaces between the TiO2 spherical particles, while the smaller mesopores (ca. 3 nm) were due to the void spaces between the anatase crystallites within each TiO2 particle. There were also larger macropores (a few micrometers), which were caused by gas bubbles generated during the sol‒gel reactions. From a mass transfer viewpoint, these large pores within TiO2 xerogels could have advantages in their potential applications for catalysis and/or filtration processes. Graphical Abstract
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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".