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Record W2193036383 · doi:10.1260/0263-6174.33.10.881

Adsorption of Model Naphthenic Acids in Water with Granular Activated Carbon

2015· article· en· W2193036383 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdsorption Science & Technology · 2015
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryAdsorptionActivated carbonNaphthenic acidCarbon fibersChemical engineeringEnvironmental chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

This work evaluated the adsorption performance of a commercial granular activated carbon (GAC) for three naphthenic acids (NAs) model compounds. In single-compound adsorption, the saturation capacity ( q m ) at pH 4 was 452.6 mg/g (1,4-cyclohexanedicarboxylic acid) > 357.9 mg/g (2-naphthoic acid) > 317.7 mg/g (diphenylacetic acid). Of all model NAs, adsorption of 1,4-cyclohexanedicarboxylic acid was the most negatively affected in multi-component adsorption at pH 4. The q m decreased significantly with increasing pH due to its effect on both carbon surface charge and dissociation of the NAs. An important finding was that the total amount of NAs adsorbed in multi-component adsorption at pH 4 (326 mg/g) was almost the same as that adsorbed at pH 8 (324 mg/g), indicating the potential of activated carbon adsorption for removal of mixture of NAs from the real oil sand process water, which is basic (pH∼8) in nature.

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.

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 score0.059
Threshold uncertainty score0.431

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
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 head0.019
GPT teacher head0.257
Teacher spread0.238 · 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