Titanium dioxide-based nanoparticles and their applications in water remediation
Bibliographic record
Abstract
Water is an essential component of life. Only 2.5% of the total percentage of water available on earth is fresh. As the world’s population is increasing, water pollution is becoming more complex and difficult to remove. Due to change in climatic conditions globally, many regions of the world are facing multiple challenges in sustainable supply of water, and their magnitude is rapidly increasing. Therefore, reuse of waste water is becoming a common necessity. However, due to the presence of water contaminants, such as heavy metals, organic pollutants and many other complex compounds, treatment of contaminated waste water is essential for a healthy life. Nanotechnology offers opportunities to provide efficient, cost-effective and environmentally sustainable solutions for supplying potable water for human use and clean water for agricultural and industrial uses. Photocatalytic processes have shown great potential as a low-cost, environmentally friendly and sustainable treatment technology for water purification. Photocatalytic degradation has been used efficiently for the degradation and removal of toxic and harmful chemicals to improve water quality. Titanium-based semiconductors have been employed as photocatalysts in degradation of organic molecules. In this review, titanium dioxide-based nanoparticles and their applications in water remediation are discussed.
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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".