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Record W2595447695 · doi:10.14447/jnmes.v13i4.143

Influence of the Functionalization Degree of Multiwalled Carbon Nanotubes on the Immobilization of Polyoxometalates and Its Effect on their Electrochemical Behavior

2010· article· en· W2595447695 on OpenAlexvenueno aff
Ana Karina Cuentas-Gallegos, Sandra Jimenez-Penaloza, Dulce A. Baeza-Rostro, Andrea German-Garcia

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2010
Typearticle
Languageen
FieldMaterials Science
TopicPolyoxometalates: Synthesis and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPolyoxometalateElectrochemistryMaterials scienceDispersion (optics)Carbon nanotubeChemical engineeringHybrid materialAdsorptionSurface modificationNanotechnologyChemistryElectrodePhysical chemistryOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

Hybrid materials based on the anchoring polyoxometalate particles POM on several multiwalled carbon nanotubes (NTs) matrices with different oxidation degree are characterized and electrochemically studied, in order to correlate the dispersion degree of POM particles on these matrices with their electrochemical behavior. These hybrids synthesized with soluble PMo12 particles resulted in truly homogenous hybrids and are analyzed by XRD, SEM, EDS, TEM, and N2 adsorption isotherms in order to confirm the presence of their components and their dispersion properties. Higher dispersion of PMo12 nanoparticles is the main factor contributing to an improved electrochemical behavior in these types of hybrid materials, making hybrid NT-S-PMo12 with this property the one resulting in the best electrochemical performance where the redox contribution of PMo12 particles are clearly observed as well as the improved double layer contribution of its nanotube matrix (NT-S, highly oxidized).

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)0.001
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.435

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.015
GPT teacher head0.244
Teacher spread0.229 · 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.

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

Citations6
Published2010
Admission routes1
Has abstractyes

Explore more

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