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Record W2023948221 · doi:10.1021/nn102929t

Water Repellent Periodic Mesoporous Organosilicas

2011· article· en· W2023948221 on OpenAlexafffund
Wendong Wang, D. Grozea, Sandeep Kohli, Douglas D. Perovic, Geoffrey A. Ozin

Bibliographic record

VenueACS Nano · 2011
Typearticle
Languageen
FieldMaterials Science
TopicMesoporous Materials and Catalysis
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMesoporous organosilicaWater repellentMaterials scienceNanotechnologyMesoporous materialMesoporous silicaChemistryOrganic chemistryCatalysisComposite material

Abstract

fetched live from OpenAlex

This paper demonstrates for the first time thermally induced gradual hydrophobization, monitored quantitatively by ellipsometric porosimetry, of four prototypical periodic mesoporous organosilicas (PMOs) that are tailored through materials chemistry for use as low-dielectric-constant (low k) materials in microprocessors. Theoretical aspects of this quantification are briefly discussed. A comparison of structural, mechanical, dielectric, and hydrophobic properties of ethane, methane, ethene, and 3-ring PMOs is made. Particularly, ethane, methane, and 3-ring PMOs show impressive water repellency at post-treatment temperatures as low as 350 °C, with corresponding Young's modulus values greater than 10 GPa and k values smaller than 2, a figure of merit that satisfies the technological requirements of future generation microchips.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.017
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0260.009

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 head0.216
Teacher spread0.195 · 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; both teacher heads agree on what is shown here.

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

Citations47
Published2011
Admission routes2
Has abstractyes

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