Adsorption of naphthenic acids from oil sand process‐affected water with water‐insoluble poly(<i>β</i>‐cyclodextrin‐citric acid)
Bibliographic record
Abstract
Abstract With polyvinyl alcohol as the main chain, a water‐insoluble poly(β‐cyclodextrin‐citric acid) was prepared as a supramolecular adsorbent for the treatment of oil sand process‐affected water (OSPW) containing naphthenic acids (NAs). FT‐IR, TGA, and SEM were used for the characterization of adsorbent, and an automatic infrared oil analyzer was used to monitor the concentration change of NAs in the water. The adsorption behaviour and mechanism were explored by adsorption kinetics and thermodynamic studies. The results showed that the adsorption process could be described well with the Langmuir isothermal adsorption model and quasi‐second‐order kinetic model, which indicated that the host‐guest interaction of β‐cyclodextrin promoted the adsorption of NAs. The discussion regarding pH indicated that the neutral condition (pH = 7) was considered the best. In addition, a molecular dynamics simulation was carried out using a Materials Studio package purchased from Accelrys to verify that the structure with polyvinyl alcohol as main chain was beneficial to adsorption. The excellent adsorption capacity (qmax was 193.42 mg · g−1) and reusability of the poly(β‐cyclodextrin‐citric acid) indicated its potential as practical adsorbent for the treatment of OSPW.
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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) | 0.000 | 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".