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Record W4410581597 · doi:10.3390/ma18102412

Sustainable Alginate–Hydrochar Composite Beads for 2-Nitrophenol Adsorption in Batch and Fixed-Bed Systems

2025· article· en· W4410581597 on OpenAlexafffund
Dalia Allouss, Nicolas Abatzoglou, Inès Esma Achouri

Bibliographic record

VenueMaterials · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsUniversité de Sherbrooke
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaCentre SèveGovernment of Canada
KeywordsAdsorptionDesorptionChemical engineeringComposite numberWastewaterFreundlich equationChemistryKineticsFourier transform infrared spectroscopyMaterials scienceChromatographyNuclear chemistryOrganic chemistryWaste managementComposite material

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.227
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes2
Has abstractyes

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