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Record W2757758330 · doi:10.1021/acs.chemmater.7b03674

Patterned Phosphonium-Functionalized Photopolymer Networks as Ceramic Precursors

2017· article· en· W2757758330 on OpenAlexafffund
Vanessa A. Béland, Matthew A. S. Ross, Matthew J. Coady, Ryan Guterman, Paul J. Ragogna

Bibliographic record

VenueChemistry of Materials · 2017
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsWestern University
FundersResearch and Innovation FoundationOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and ScienceCanada Foundation for Innovation
KeywordsMaterials sciencePhosphoniumThermogravimetric analysisScanning electron microscopeX-ray photoelectron spectroscopySurface modificationPhotopolymerPolymerDifferential scanning calorimetryChemical engineeringCeramicInfrared spectroscopyPolymer chemistryPolymerizationOrganic chemistryComposite materialChemistry

Abstract

fetched live from OpenAlex

In an attempt to address the growing demand for well-defined metallized regions for electronic applications, we developed a new method of forming patterned ceramics. Using UV-curing to synthesize a phosphonium-containing semi-interpenetrating polymer network (S-IPN) followed by ion exchange on the surface with a bis(phosphino)borate molybdenum tetracarbonyl complex (2Mo) results in 71% ion exchange of 2Mo to phosphonium sites by attenuated total reflectance infrared (ATR-IR) spectroscopy. The functionalized films were pyrolyzed at temperatures ranging between 800 and 1000 °C to create Mo-containing ceramics. The polymer network can be patterned using electron beam lithography prior to the metal functionalization step. The patterns had good shape retention after metal functionalization and pyrolysis. The polymer networks were characterized using ATR-IR spectroscopy, thermogravimetric analysis, and differential scanning calorimetry, and the swellability and gel content were determined. The resulting ceramics were characterized using optical and scanning electron microscopy, energy dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, and powder X-ray diffraction.

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 score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0390.000

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 head0.010
GPT teacher head0.242
Teacher spread0.232 · 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

Citations9
Published2017
Admission routes2
Has abstractyes

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