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Record W2889055884 · doi:10.14447/jnmes.v18i3.365

Synthesis and Properties of Electrochemically Deposited Vertical Mesoporous Silica Thin Films

2015· article· en· W2889055884 on OpenAlexvenueno aff
Yuan Zhou, Qiming Liu, Feng Ye, Min Tan

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2015
Typearticle
Languageen
FieldMaterials Science
TopicMesoporous Materials and Catalysis
Canadian institutionsnot available
Fundersnot available
KeywordsTetraethyl orthosilicateMesoporous materialMaterials scienceThin filmAmmonium bromideChemical engineeringMesoporous silicaSiliconAmorphous solidMesoporous organosilicaElectrodeElectrochemistryAmorphous siliconSol-gelNanotechnologyCatalysisCrystalline siliconOrganic chemistryOptoelectronicsChemistry

Abstract

fetched live from OpenAlex

Electrochemical deposition was successfully used to prepare mesoporous silica thin films with highly ordered and vertically oriented pores. Tetraethyl orthosilicate was used as the inorganic silicon source and cetyltrimethyl ammonium bromide was the template. A negative potential was applied to the working electrode, which was initially immersed in collosol and then in hydroxyl at the electrode/solution interface. Hydroxyl ion served as the catalyst that promoted the polycondensation and self-assembly of the silicon precursor, as well as the formation of thin films with pores which are highly ordered and vertically oriented with respect to the panel.The pore arrangement of the mesoporous film was hexagonal, and its aperture was 2 nm to 3 nm. The verticality of the thin film pore was demonstrated through permeability and transmission electron microscopy analyses. The prepared mesoporous film possessed good optical amorphous antireflective property with ordered and vertically oriented pores.

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 head0.021
GPT teacher head0.233
Teacher spread0.212 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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Same venueJournal of New Materials for Electrochemical SystemsSame topicMesoporous Materials and CatalysisFrench-language works237,207