Sustainable Alginate–Hydrochar Composite Beads for 2-Nitrophenol Adsorption in Batch and Fixed-Bed Systems
Bibliographic record
Abstract
Addressing the removal of hazardous phenolic pollutants from water, this study introduces an eco-friendly adsorbent composed of waste-derived hydrochar immobilized in alginate beads (Alg/HC). The physicochemical properties of the Alg/HC beads were characterized using SEM, XRD, and FTIR, confirming hydrochar encapsulation and partial structural preservation. Batch studies revealed a maximum 2-nitrophenol (2-NP) adsorption capacity of 15.80 ± 0.62 mg/g at 30 mg/L of 2-NP, with kinetics best described by the Elovich and pseudo-second-order models. Freundlich isotherm fitting indicated multilayer adsorption on heterogeneous surfaces, likely governed by hydrogen bonding and π-π interactions. In a fixed-bed column system, Alg/HC beads demonstrated a continuous adsorption capacity of 6.84 ± 0.45 mg/g at 10 mg/L of 2-NP, with breakthrough behavior modeled by the Yoon-Nelson and Thomas equations. The beads maintained stable performance across four regeneration cycles using a mild water/ethanol desorption method. This work represents the first study to explore Alg/HC composites for 2-NP removal in both batch and continuous modes, demonstrating their potential as low-cost, regenerable adsorbents for tertiary treatment of phenolic industrial wastewater.
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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) | 0.000 | 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 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".