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Record W2963036411 · doi:10.5360/membrane.33.130

Recent Developments in Fabrication of Giant Nanomembranes

2008· article· en· W2963036411 on OpenAlexaff
Toyoki Kunitake, Hirohmi Watanabe

Bibliographic record

VenueMEMBRANE · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsGeomembrane Technologies (Canada)
Fundersnot available
KeywordsMaterials scienceFabricationAcrylateNanometreCoatingEpoxyOxidePolymerNanotechnologySubstrate (aquarium)Composite materialElectrochemistryNanoscopic scaleElectrodeCopolymer

Abstract

fetched live from OpenAlex

Giant nanomembranes that are characterized by aspect ratios (size/thickness)of greater than one million are dis-cussed.The combination of nanometer thickness and macroscopic size facilitates important applications in materialsseparation, selective transport and electrochemical devices. Their fabrication procedure and hybridization aredescribed here. Spin coating of precursor solutions on appropriate underlayer is effectively used to prepare 10-30 nmthick nanomembranes of metal oxides, interpenetrating network of crosslinked acrylate with metal oxide, and highlycross-linked organic polymers (epoxy resin, etc.). When the underlayer is removed, self-supporting nanomembranesbecome separated from the substrate without damage. These nanomembranes are surprisingly robust and defect-free, and can be hybridized by physical and chemical means. The latter method provides mechanical properties ofnanomembranes reveal that the texture of the nanomembranes is essentially identical with those of the macroscopiccounterparts. Their application potentials as 2D materials are discussed.

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 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 score0.076
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

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 head0.022
GPT teacher head0.216
Teacher spread0.194 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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