Investigation of mechanisms of sulfamethoxazole adsorption on novel adsorbents developed from reed canary grass
Why this work is in the frame
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Bibliographic record
Abstract
In this work, reed canary grass and activated carbons developed from this biomass were used as novel adsorbents to remove sulfamethoxazole (SMX) from water. Raw biomass adsorbent with the lowest surface area demonstrated the lowest SMX adoption capacity of 20.2 ± 1.6 mg/g and the activated carbon adsorbent with the highest surface area showed the highest adsorption capacity of 160.5 ± 4.2 mg/g. π-π, hydrogen bonding, Lewis acid base, and hydrophobic interactions are the possible mechanisms that could be responsible for adsorption of SMX on the adsorbents. Methanol, hydrochloric acid solution, sodium hydroxide solution, and deionized water were used to desorb SMX from the adsorbent. The results of using 20 mL of solvent at 35 °C showed that methanol could desorb loaded SMX with a higher desorption efficiency (80.1 ± 2%) than the aqueous solvents (9.5-46.5%). Decreasing the temperature to 25 °C decreased the desorption efficiency of methanol to 58.5 ± 1%. By decreasing the methanol volume to 5 mL, SMX desorption efficiency could remain comparable (59.1 ± 1.2%). Reusing the adsorbent in 4 adsorption desorption cycles showed that SMX adsorption capacity reduced from 124.9 ± 3.8 mg/g in the first adsorption cycle to 82.1 ± 2.2 mg/g in the second adsorption cycle and was stable in the third and fourth cycles.
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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