Adsorption for perfluorooctanoic acid with graphitic‐phase carbon nitride and its HPLC fluorescence determination
Bibliographic record
Abstract
Abstract In this paper, graphitic‐phase carbon nitride (g‐C3N4) was prepared from urea and detected by FTIR, XRD, SEM, TEM, Boehm titration, zeta potential, and N2 adsorption‐desorption analyzes, demonstrating that g‐C3N4 possesses a thin sheet structure, negative surface, and strong alkalinity. Considering the alkaline groups and huge areas, g‐C3N4 was employed to adsorb perfluorooctanoic acid (PFOA). The adsorption capacity of g‐C3N4 towards PFOA was evaluated by batch adsorption experiments, indicating the considerable adsorption capacity of 120.879 mg g−1. The isothermal models and kinetic models were also performed in order to study the adsorption process, proving that PFOA adsorption was fitted by the Langmuir isothermal model and pseudo second‐order model. In addition, residual PFOA concentration after adsorption was determined by high performance liquid chromatography (HPLC) with a fluorescence detector after being derived with 3‐(2‐bromoacetyl) coumarin (3‐BrAC). The HPLC fluorescent detection showed satisfied linearity from 0.5 to 20.0 ug mL−1 with a sound R 2 of 0.9992. This is the first time that g‐C3N4 was applied to PFOA adsorption from aqueous solutions with outstanding adsorption capacity.
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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 | 0.001 | 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".