Removal of Petroleum Aromatic Hydrocarbons by Surfactant‐modified Natural Zeolite: The Effect of Surfactant
Bibliographic record
Abstract
Abstract Monoaromatic hydrocarbons including benzene, toluene, ethylbenzene and xylene isomers (BTEX) are a very important category of water pollutants. These volatile compounds are very hazardous because of their fast migration in soil and water bodies and their acute and chronic toxicities when inhaled or ingested, especially benzene which is a known carcinogenic molecule. In this study, a natural zeolite (i. e., clinoptilolite‐rich tuffs) was modified by two cationic surfactants (i. e., hexadecyltrimethyl ammonium chloride (HDTMA‐Cl), and N ‐cetylpyridinium bromide (CPB)). The prepared adsorbents were then characterized, and their adsorptive capabilities for BTEX examined at different experimental conditions. The results of adsorption tests at 24 h revealed that the adsorption capacity of the modified zeolites improved by increasing the surfactant loading (i. e., less than the critical micelle concentration (CMC), to higher than the CMC), which caused an increase in sorption capacity from 60 to 70% for HDTMA‐modified samples, and from 47 to 99% for CPB‐modified zeolite. Adsorption kinetic tests showed the optimum contact time was 48 h with an average BTEX removal of 90 and 93% for HDTMA‐modified and CPB‐modified zeolite, respectively. Results showed that by increasing of pH from 3 to 11, the sorption capacity of the adsorbent decreased markedly from 97 to 75%. Analyzing the influence of temperature showed that the adsorption efficiency of adsorbents for benzene reduced from 93% at 20°C to 10% at 4°C. However, the influence of temperature on other compounds was not remarkable. Overall, CPB‐modified zeolite exhibited higher selectivity toward BTEX compounds at optimum experimental conditions. Although commercial powder activated carbon (PAC) showed a higher capacity for all BTEX compounds and faster adsorption kinetics, the adsorption capacity of the CPB‐modified zeolite at optimized conditions was competitive with PAC results.
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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 | 0.001 | 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 | 0.001 |
| 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 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".