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Record W1978624337 · doi:10.1080/09593330.2011.556149

Converting poultry litter to activated carbon: optimal carbonization conditions and product sorption for benzene

2011· article· en· W1978624337 on OpenAlexfundno aff
Mingxin Guo, Weiping Song

Bibliographic record

VenueEnvironmental Technology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsnot available
FundersMemorial University of Newfoundland
KeywordsSorptionCarbonizationActivated carbonPoultry litterBenzeneWaste managementChemistryCarbon fibersProduct (mathematics)LitterEnvironmental scienceBy-productEnvironmental chemistryPulp and paper industryOrganic chemistryAdsorptionMaterials scienceMathematicsEngineering

Abstract

fetched live from OpenAlex

To promote utilization of poultry litter as a source material for manufacturing low-cost activated carbon (AC) that can be used in wastewater treatment, this study investigated optimal production conditions and water-borne organic sorption potential of poultry litter-based AC. Pelletized broiler litter was carbonized at different temperatures for varied time periods and activated with steam at a range of flow rate and time. The AC products were examined for quality characteristics using standard methods and for organic sorption potentials using batch benzene sorption techniques. The study shows that the yield and quality of litter AC varied with production conditions. The optimal production conditions for poultry litter-based AC were carbonization at 700 degrees C for 45 min followed by activation with 2.5 ml min(-1) steam for another 45 min. The resulting AC possessed an iodine number of 454 mg g(-1) and a specific surface area of 403 m2 g(-1). It sorbed benzene in water following sigmoidal kinetic and isothermal patterns. The sorption capacity for benzene was 23.70 mg g(-1), lower than that of top-class commercial AC. The results, together with other reported research findings, suggest that poultry litter is a reasonable feedstock for low-cost AC applicable to pre-treat wastewater contaminated by organic pollutants and heavy metals.

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 score0.130
Threshold uncertainty score0.646

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 head0.011
GPT teacher head0.216
Teacher spread0.205 · 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

Citations5
Published2011
Admission routes1
Has abstractyes

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