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Record W2325072021 · doi:10.1021/sc400540f

Synthesis of β-Cyclodextrin-Modified Cellulose Nanocrystals (CNCs)@Fe<sub>3</sub>O<sub>4</sub>@SiO<sub>2</sub> Superparamagnetic Nanorods

2014· article· en· W2325072021 on OpenAlexafffund
Li Chen, Richard M. Berry, Kam Chiu Tam

Bibliographic record

VenueACS Sustainable Chemistry & Engineering · 2014
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsCelluForce (Canada)University of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsProcaine HydrochlorideSuperparamagnetismChemical engineeringMaterials scienceCyclodextrinThermal stabilityThermal decompositionCoatingNanorodAdsorptionNanoparticleDispersion (optics)Organic chemistryChemistryNanotechnologyMagnetizationProcaine

Abstract

fetched live from OpenAlex

This paper reports on the synthesis of β-cyclodextrin-modified CNC@Fe 3 O 4 @SiO 2 superparamagnetic nanorods for the removal of two model compounds: procaine hydrochloride and imipramine hydrochloride. During the synthetic process, sustainable natural materials and low-cost chemicals were used, and mild reaction conditions were adopted. TEM and SEM images indicated good dispersion of Fe 3 O 4 nanoparticles with uniform silica coating on CNCs. The thickness of the silica coating was controlled by manipulating the amounts of precursor solution used. TGA data confirmed that the silica coating significantly enhanced the thermal stability of CNCs. The onset decomposition temperature of CNC@Fe 3 O 4 @SiO 2 hybrids increased by 60 °C compared to pure CNCs. XRD, EDS, and FT-IR analyses confirmed the structure of CNC@Fe 3 O 4 @SiO 2 and the successful grafting of β-cyclodextrin. The CNC@Fe 3 O 4 @SiO 2 @β-CD hybrids displayed good adsorption toward the model pharmaceutical residues: procaine hydrochloride and imipramine hydrochloride.

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)0.0000.000
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)0.0010.000

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 head0.006
GPT teacher head0.210
Teacher spread0.204 · 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

Citations134
Published2014
Admission routes2
Has abstractyes

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Same venueACS Sustainable Chemistry & EngineeringSame topicAdvanced Cellulose Research StudiesFrench-language works237,207