Facile, eco-friendly, ultrasonic-assisted synthesis of functionalized Co₅₀Ni₅₀-LDH for enhanced pharmaceutical adsorption: Mechanistic insights using carprofen as a model drug
Bibliographic record
Abstract
The efficient removal of pharmaceutical contaminants like carprofen (CPF) from aqueous systems is crucial due to their persistence and environmental risks. This investigation sought to create an eco-friendly adsorbent with a simplified preparation process with high CPF removal efficiency, addressing the need for cost-effective materials in pharmaceutical wastewater treatment. A Ni 50 Co 50 -layered double hydroxide (LDH) was fabricated and surface-modified with AEAMP-TMS, a silane coupling agent bearing amine and phenyl groups, via a facile, scalable, and eco-friendly route. The AEAMP-LDH adsorbent (functionalized LDH) was structurally characterized using XRD and FTIR, and its morphology and porosity were examined by FESEM/FESEM mapping and N 2 adsorption–desorption isotherms. The resulting AEAMPS-LDH exhibited a well-defined macroporous-mesoporous structure, as confirmed by N₂ adsorption–desorption analysis, with a surface area of 65.2 m² g⁻¹ . Adsorption experiments were carried out to evaluate the capacity, pH dependence, and reusability of the material. AEAMPS-LDH achieved a Langmuir maximum adsorption capacity of 742 mg g⁻¹ for CPF, driven by π–π interactions, hydrogen bonding, electrostatic attraction, and interlayer anion exchange. Optimal removal occurred at pH 5–8, where CPF exists in an anionic form. The material retained over 90 % efficiency after eight reuse cycles. Compared to Fe 3 O 4 @ZIF-67@Co-Ni LDH, the only previously reported LDH-based adsorbent for CPF removal from water, AEAMPS-LDH demonstrated comparable performance with a simpler, more sustainable synthesis process. • AEAMPS-LDH synthesized via a green ultrasonic-assisted reflux method. • Dual-function AEAMPS-LDH adsorbent captures carprofen via surface and interlayer interactions. • Carprofen uptake occurs through electrostatic, H-bonding, π–π stacking, ion exchange. • High adsorption capacity (742 mg/g) validated by Langmuir isotherm. • Adsorbent maintained > 92 % removal efficiency across 8 regeneration cycles.
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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 | 0.000 | 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".