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Record W2129687648 · doi:10.1002/cjce.21796

Adsorption and catalytic ozonation performance of activated carbon and cobalt‐supported activated carbon derived from brewing yeast

2013· article· en· W2129687648 on OpenAlexvenueno aff
Guiping Wu, Wei Wei, Longzhe Cui

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsnot available
Fundersnot available
KeywordsActivated carbonAdsorptionCobaltChemistryCatalysisNuclear chemistryReaction rate constantLangmuir adsorption modelMethylene blueKineticsYeastLangmuirInorganic chemistryOrganic chemistryPhotocatalysisBiochemistry

Abstract

fetched live from OpenAlex

Abstract Activated carbon (AC) was prepared from brewing yeast by Na CO activation, and cobalt was supported on activated carbon (Co/AC) by the adsorption–activation method. The XPS test indicated that supported cobalt was Co(II). The total BET surface areas of prepared AC and Co/AC were 957.7 and 847.9 m /g, with total pore volumes of 0.81 and 0.80 cm /g, respectively. The average pore diameters of AC and Co/AC were found to be 3.8 and 3.3 nm. The contact time required for equilibrium of methylene blue (MB) adsorption onto prepared AC and Co/AC was about 120 min. The maximum uptake of MB by AC and Co/AC was estimated to be 372.1 and 213.5 mg/g, respectively. The presence of prepared AC or Co/AC was advantageous for TOC reduction compared with UV/O system, and the greatest TOC removal was obtained in the presence of Co/AC. The kinetics of the degradation of MB fitted the Langmuir‐first‐order model well. The rate constants of Langmuir first‐order were determined to be 0.0096 min−1 for UV/O /AC and 0.0143 min−1 for UV/O /Co/AC, respectively.

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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.006
GPT teacher head0.166
Teacher spread0.160 · 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

Citations8
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicAdsorption and biosorption for pollutant removalFrench-language works237,207