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Record W2570980610 · doi:10.3390/polym9010010

Pentynyl Ether of β-Cyclodextrin Polymer and Silica Micro-Particles: A New Hybrid Material for Adsorption of Phenanthrene from Water

2017· article· en· W2570980610 on OpenAlexaff
Jae Min Choi, Daham Jeong, Eunae Cho, Jae‐Hyuk Yu, M.N. Tahir, Seunho Jung

Bibliographic record

VenuePolymers · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsUniversité du Québec à Montréal
FundersNational Research Foundation of KoreaKonkuk UniversityNational Research Foundation
KeywordsPhenanthreneThermogravimetric analysisPolymerCyclodextrinAdsorptionChemistryPolymerizationAqueous solutionNuclear chemistryChemical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

A new hybrid material for the removal of polycyclic aromatic hydrocarbons (PAH) from water was prepared by the polymerization of pentynyl beta-cyclodextrin (PyβCD) and silica micro-particles (SMP). Phenanthrene, being one of the important members of the PAH family and a potential risk for environmental pollution, was selected for this study. Results show that phenanthrene removal efficiency of the SMP was improved significantly after hybridization with PyβCD-polymer. Approximately 50% of the phenanthrene was removed in the first 60 min and more than 95% was removed in less than 7 h when 25 mL of the 2 ppm aqueous phenanthrene solution was incubated with the 100 mg of SMP-PyβCD-polymer material. Infrared spectroscopy and thermal gravimetric analysis show that the enhanced efficiency of the SMP-PyβCD-polymer compared to the unmodified SMP was due to the formation of the inclusion complexation of phenanthrene with the PyβCD. These results indicate that SMP-PyβCD polymers have a potential to be applied as molecular filters in water purification systems and also for waste water treatment.

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 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 score0.011
Threshold uncertainty score0.999

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)0.0020.000

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 head0.017
GPT teacher head0.252
Teacher spread0.235 · 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.

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

Citations20
Published2017
Admission routes1
Has abstractyes

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