Efficient Removal of Ammonium, Heavy Metals, and Scale-Forming Cations from Oilfield Produced Water by Sulfonated Biochar
Why this work is in the frame
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Bibliographic record
Abstract
The treatment of oilfield produced water (OPW), which contains complex pollutants, such as scale-forming cations, heavy metals, ammonia, and organic matter, presents a significant challenge. In this study, we utilized low-cost sulfonated biochar (SBC), produced through in situ sulfonation of alkylated waste sulfuric acid with waste rice husk, to remove these pollutants from actual OPW. Treatment with 60 g/L of SBC achieved removal rates of 65.7% for COD, 66.1% for DOC, 89.6% for NH 4 + –N, and over 96.3% for scale-forming cations (Ba 2+, Ca 2+, and Mg 2+ ), with heavy metals (Cd 2+ and Cu 2+ ) being completely removed (100%). SBC effectively adsorbed cationic pollutants via surface functional groups (−SO 3 H, −OH, and −COOH) and removed diverse organic pollutants (highly unsaturated compounds, polyphenols, and polycyclic aromatics) through pore-filling, electrostatic interactions, and π–π interaction mechanisms. SBC released substantial quantities of sulfur- and oxygen-containing compounds, inducing a pH decrease in OPW from 6.97 to 3.05. Approximately 30% of these compounds are microbially bioactive molecules (H/C ≥ 1.5). Moreover, SBC proved effective for OPW treatment, maintaining a stable adsorption performance through six consecutive cycles. These findings suggest that SBC holds great potential for large-scale applications as an adsorbent in the pretreatment stages of OPW treatment processes.
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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 it