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Record W2334569301 · doi:10.1021/am501632f

Highly Regenerable Mussel-Inspired Fe<sub>3</sub>O<sub>4</sub>@Polydopamine-Ag Core–Shell Microspheres as Catalyst and Adsorbent for Methylene Blue Removal

2014· article· en· W2334569301 on OpenAlexafffund
Yijun Xie, Bin Yan, Haolan Xu, Jian Chen, Qingxia Liu, Yonghong Deng, Hongbo Zeng

Bibliographic record

VenueACS Applied Materials & Interfaces · 2014
Typearticle
Languageen
FieldChemistry
TopicNanomaterials for catalytic reactions
Canadian institutionsNational Institute for NanotechnologyUniversity of Alberta
FundersAustralian Research CouncilNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceMethylene blueCatalysisDispersityAdsorptionChemical engineeringColloidNanoparticleReducing agentShell (structure)DesorptionMicrosphereCore (optical fiber)NanotechnologyOrganic chemistryPolymer chemistryPhotocatalysisComposite materialChemistry

Abstract

fetched live from OpenAlex

We report a facile method to synthesize Fe3O4@polydopamine (PDA)-Ag core-shell microspheres. Ag nanoparticles (NPs) are deposited on PDA surfaces via in situ reduction by mussel-inspired PDA layers. High catalytic activity and fast adsorption of a model dye methylene blue (MB) at different pH values are achieved mainly due to the presence of monodisperse Ag NPs and electrostatic interactions between PDA and MB. The as-prepared Fe3O4@PDA-Ag microspheres also show high cyclic stability (>27 cycles), good acid stability, and fast regeneration ability, which can be achieved efficiently within several minutes by using NaBH4 as the desorption agent, showing great potentials in a wide range of applications.

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 score0.001

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)0.0000.000

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 head0.012
GPT teacher head0.228
Teacher spread0.217 · 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

Citations431
Published2014
Admission routes2
Has abstractyes

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