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Record W2095914868 · doi:10.1002/adfm.201404304

Magnesiothermic Reduction of Thin Films: Towards Semiconducting Chiral Nematic Mesoporous Silicon Carbide and Silicon Structures

2015· article· en· W2095914868 on OpenAlexafffund
Thanh‐Dinh Nguyen, Joel A. Kelly, Wadood Y. Hamad, Mark J. MacLachlan

Bibliographic record

VenueAdvanced Functional Materials · 2015
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsFPInnovationsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceMesoporous materialLiquid crystalSilicon carbideChemical engineeringSiliconNanotechnologyPorosityPorous siliconComposite materialOrganic chemistryOptoelectronicsCatalysis

Abstract

fetched live from OpenAlex

There is a growing demand for new methods to prepare porous Si‐based materials for applications in optoelectronic and microelectronic devices. In this work, the preparation of SiC and Si from magnesiothermic reduction of chiral nematic SiO 2 /C composites and mesoporous SiO 2 , respectively, is reported. The SiO 2 /C composites are prepared by cocondensing SiO 2 with cellulose nanocrystals (CNCs) followed by pyrolysis. The magnesiothermic reduction of the composites produces SiC after prolonged solid‐state reaction, with mixed MgC 2 /SiC intermediates. Iridescent mesoporous tetragonal MgC 2 /SiC structures that retain the long‐range twisted organization of the starting composites transform to mesoporous cubic SiC with a chiral nematic hierarchical structure, but with some loss of order. On the other hand, the magnesiothermic reduction of the chiral nematic mesoporous SiO 2 templated from CNCs affords mesoporous Si materials with a layered hierarchical structure. The structural properties and the conductivity of the products, as well as the reaction pathways by analysis of the materials at intermediate stages, are investigated. These experimental results show that the magnesiothermic reduction is a promising way to obtain new porous semiconducting materials with chiral nematic structures.

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 categoriesMeta-epidemiology (narrow), Insufficient 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 score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.024
GPT teacher head0.259
Teacher spread0.236 · 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

Citations32
Published2015
Admission routes2
Has abstractyes

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