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Record W2065774682 · doi:10.3390/ma4091528

Sorption of Aromatic Compounds with Copolymer Sorbent Materials Containing β-Cyclodextrin

2011· article· en· W2065774682 on OpenAlexafffund
Lee D. Wilson, Mohamed H. Mohamed, Christopher L. Berhaut

Bibliographic record

VenueMaterials · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSorbentSorptionCopolymerPentachlorophenolAqueous solutionActivated carbonChemistryAcetic acidAdsorptionNuclear chemistryPolymer chemistryChemical engineeringMaterials scienceOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

Urethane copolymer sorbent materials that incorporate β-cyclodextrin (CD) have been prepared and their sorption properties with chlorinated aromatic compounds (i.e., pentachlorophenol, 2,4-dichlorophenol and 2,4-dichlorophenoxy acetic acid) have been evaluated. The sorption properties of granular activated carbon (GAC) were similarly compared in aqueous solution at variable pH conditions. The sorbents displayed variable BET surface areas as follows: MDI-X copolymers (< 10¹ m²/g), CDI-X copolymers (< 10¹ m²/g), and granular activated carbon (GAC ~10³ m²/g). The sorption capacities for the copolymers sorbents are listed in descending order, as follows: GAC > CDI-3 copolymer ≈ MDI-3 copolymer. The sorption capacity for the aromatic adsorbates with each sorbent are listed in descending order, as follows: 2,4-dichlorophenol > 2,4-dichlorophenoxy acetic acid > pentachlorophenol. In general, the differences in the sorption properties of the copolymer sorbents with the chlorinated organics were related to the following factors: (i) surface area of the sorbent; (ii) CD content and accessibility; and (iii) and the chemical nature of the sorbent material.

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 score0.001
Threshold uncertainty score0.003

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 integrity0.0000.000
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 head0.022
GPT teacher head0.211
Teacher spread0.190 · 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

Citations32
Published2011
Admission routes2
Has abstractyes

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