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Record W4416900502 · doi:10.1039/d5cp02560e

Enhanced Cr( <scp>vi</scp> ) adsorption on nitrogen and sulfur functionalized granular activated carbon

2025· article· en· W4416900502 on OpenAlexafffund
Ali Bakhshi-Zadeh, Janelle Balzer, Negar Fahimi, Nael Yasri, Linda J Eastcott, Krista Stevenson, Anne M. Benneker, Sathish Ponnurangam

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsImperial Oil (Canada)University of Calgary
FundersAlberta Innovates - Technology Futures
KeywordsAdsorptionChemisorptionSulfurX-ray photoelectron spectroscopyActivated carbonHexavalent chromiumDesorptionNitrogen

Abstract

fetched live from OpenAlex

on the heterogeneous GAC surface (Sips model), whereas N/S-functionalized GAC follows the Freundlich model, indicating heterogeneous adsorption through the formation of Cr(III) hydroxides near functional groups. Kinetic studies indicated that the adsorption follows a revised pseudo-second order kinetic model on both surfaces, where chemisorption is the rate-controlling step. The rate of adsorption is similar for both types of GAC in the initial regime with fast kinetics. However, after 200 min, N/S functionalized GAC exhibits a higher uptake, likely associated with the additional Cr(VI) adsorption through a reduction process. Regeneration experiments revealed that NaOH and KOH solutions achieved significantly higher desorption efficiencies (>90% for unmodified GAC and >70% for N/S functionalized GAC) compared to acidic regeneration using HCl solution (<40% for GAC and <25% for N/S-GAC).

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.007
GPT teacher head0.221
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2025
Admission routes2
Has abstractyes

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