ADSORPTION OF CIPROFLOXACIN FROM WATER BY ADSORBENTS DEVELOPED FROM OAT HULLS
Bibliographic record
Abstract
Water contamination with antibiotics is a serious threat for human health as the presence of antibiotics in water can cause antibiotics resistance in pathogens. Ciprofloxacin (CIP) is one of the most frequently detected antibiotics in water. Adsorption has shown to be one of the promising methods for removal of antibiotics from water. Although a number of adsorbents were investigated previously for removal of CIP from water, precursors in use were expensive, and scarce in some parts of the world. As such, development of adsorbents made of abundantly available and inexpensive raw materials, which can simultaneously offer high CIP adsorption capacity, is needed. In this work, for removal of ciprofloxacin (CIP) from water, adsorbents were developed from raw oat hulls. Raw oat hulls were pretreated by using phosphoric acid impregnation and microwave heating, respectively. Surface morphology and surface area of raw and pretreated oat hulls were investigated by Scanning Electron Microscopy (SEM) and surface area analysis, respectively. Results indicated substantial enhancement in adsorbents’ porosity and remarkable increase in surface area after the pretreatment procedure. Effects of influential parameters such as solution pH, adsorbents dose and temperature on CIP adsorption capacity were studied. Results revealed that the optimum adsorbents dose was 0.3 mg/L and the optimum pH value was 7. CIP adsorption equilibrium and kinetic were investigated at three temperatures of 288, 298 and 318 K. The results were modeled using adsorption isotherms, and kinetic models. The maximum adsorption capacity obtained was 83 mg/g at the pH of 7 and a temperature of 318 K. The Freundlich model was the best to simulate the experimental data at all the three temperatures among the tested models. This suggested that adsorption of CIP took place on heterogeneous sites on the surface of the adsorbents. The pseudo second order model was the best fit to the kinetic data. This indicated that adsorption step may be the rate controlling mechanism of the process. Desorption experiments showed low desorption efficiency, hence implying strong interactions existing between CIP molecules and the adsorbent surface. Thermodynamic analysis revealed that CIP adsorption on pretreated oat hulls was spontaneous, endothermic along with an increase in entropy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".