MétaCan
Menu
Back to cohort
Record W1964850653 · doi:10.1002/clen.201000027

Removal of Brilliant Green Dye from Aqueous Solutions Using Home Made Activated Carbons

2010· article· en· W1964850653 on OpenAlexfundno aff
Tatiana Calvete, Éder C. Lima, Natali F. Cardoso, Sı́lvio L.P. Dias, Emerson Schwingel Ribeiro

Bibliographic record

VenueCLEAN - Soil Air Water · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsnot available
FundersPartenariat Canadien Contre Le CancerConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsActivated carbonAdsorptionBrilliant greenAqueous solutionEnthalpyChemistryChromatographyEffluentChemical engineeringNuclear chemistryVolume (thermodynamics)PorosityMaterials scienceOrganic chemistryEnvironmental engineeringEnvironmental scienceThermodynamics

Abstract

fetched live from OpenAlex

Abstract Activated carbon materials were prepared from the Brazilian pine‐fruit shell ( Araucaria angustifolia ) by chemically activated carbon (CAC) and chemically and physically activated carbon (CPAC), and tested as adsorbents for the removal of brilliant green (BG) dye from aqueous effluents. The mixed activation process leads to increases in the specific surface area, average porous volume, and average porous diameter of the adsorbent CPAC when compared to CAC. The effects of shaking time, adsorbent dosage and pH on the adsorption capacity were studied. BG uptake was favorable at pH values ranging from 2.0 to 10.0 for both CAC and CPAC. The contact time required to obtain the equilibrium using CAC and CPAC as adsorbents was 4 h at 298 K, respectively. The fractionary‐order kinetic model provided the best fit to experimental data compared with other models. Equilibrium data were better fit to the Sips and Redlich‐Peterson isotherm models using CAC and CPAC as adsorbents. The enthalpy and entropy of adsorption of BG were obtained from adsorption experiments ranging from 298 to 323 K.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.156
Threshold uncertainty score1.000

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)0.0050.001

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 head0.017
GPT teacher head0.218
Teacher spread0.201 · 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; both teacher heads agree on what is shown here.

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

Citations107
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueCLEAN - Soil Air WaterSame topicAdsorption and biosorption for pollutant removalFrench-language works237,207