Titania: From a waste solid catalyst to an inorganic pigment
Bibliographic record
Abstract
Abstract The aim of the present study is to recover a waste titania catalyst from α‐pinene isomerization, recycle it and use it in the production of inorganic pigments. The acid‐contaminated titania (ACT), prepared from ilmenite ore by sulphation, has the potential to function as a solid acid catalyst due to the presence of both Brønsted and Lewis acid sites, with a specific surface area of 163 m 2 g −1 . The catalytic efficiency was evaluated in the isomerization of turpentine (83.8 wt.% α‐pinene) at a reaction temperature of 120°C, using a turpentine:catalyst mass ratio of 4:1. The α‐pinene conversion was 99.6% with a camphene selectivity of 43 wt.%. The waste catalyst was recovered and subjected to calcination at a suitable temperature to remove all organic compounds and make it suitable for use in the production of inorganic pigments. The calcined product exhibits pigment properties including a pure rutile phase, an average grain size of 0.2 μm, a specific surface area of 29 m 2 g −1 and a reflectance in visible light of 95%. This study has provided a practical, simple, and cost‐effective solution for the treatment of residual acid on titania obtained from the hydration of titanyl sulphate, while also demonstrating the simultaneous application of titania in catalysis and pigment production.
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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".