The synthesis of a novel titanium oxide aerogel with highly enhanced removal of uranium and evaluation of the adsorption mechanism
Bibliographic record
Abstract
A TiO2 aerogel with a high removal percentage and adsorption capacity was manufactured via template synthesis. Subsequently, the as-prepared TiO2 aerogel was characterized by various techniques and applied as an adsorbent for the removal of U(vi). The results revealed that the U(vi) adsorption was very rapid and reached apparent equilibrium within 100 min. The maximum removal percentage was 97.1%, which was calculated using the pseudo-second-order kinetic model (T = 298 K, t = 180 min, pH = 5, m/V = 0.1 g L-1 and C0 = 10 mg g-1). The Langmuir isotherm model was used to determine the maximum adsorption capacity and it achieved 638.0 mg g-1 (T = 298 K, pH = 5 and m/V = 0.1 g L-1). In addition, the removal of U(vi) on the TiO2 aerogel was relatively good in acidic solution and the removal behavior was independent of the influence of ionic strength. The removal percentage of the as-prepared TiO2 aerogel was higher than 90% after five cycles. Due to these excellent properties such as easy recovery, fast adsorption kinetics, high adsorption capacity and high removal percentage, the TiO2 aerogel might become an extremely employable adsorbent for the extraction of U(vi) in seawater.
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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 | 0.001 |
| 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 | 0.001 | 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 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".