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Record W3142296670 · doi:10.1002/cite.202000238

Reassessing the Physicochemical Properties of Ordered Mesoporous Polymer and Copolymer Nanocasts

2021· article· en· W3142296670 on OpenAlexafffund
Simon Bilodeau, Justyna Florek, Freddy Kleitz

Bibliographic record

VenueChemie Ingenieur Technik · 2021
Typearticle
Languageen
FieldMaterials Science
TopicMesoporous Materials and Catalysis
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaUniversität Wien
KeywordsMesoporous materialCopolymerMaterials scienceDivinylbenzeneStyrenePolymerSurface modificationPolymerizationChemical engineeringNanotechnologyPorosityMesoporous organosilicaStructuringCatalysisOrganic chemistryMesoporous silicaChemistryComposite material

Abstract

fetched live from OpenAlex

Abstract Nanocasting is a convenient way for preparing highly porous, nanostructured soft materials. Mesoporous polymer nanocasts have been reported for over a decade, however, several aspects remain to be explored further. To do so, we report a comprehensive investigation of the physicochemical characteristics of high surface area functional organic polymers and copolymers obtained by nanocasting. Divinylbenzene, styrene and chloromethyl styrene were selectively polymerized within the pores of mesoporous SBA‐15 or KIT‐6 silicas. Following template removal, the resulting materials were characterized. The nanocast mesoporous polymers were also modified to introduce functional groups. The success of the functionalization was assessed analytically and by model catalytic tests. The study points to the advantages of the hard templating method for structuring organic materials but also its limitations.

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 score0.010
Threshold uncertainty score0.578

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 head0.016
GPT teacher head0.227
Teacher spread0.211 · 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

Citations5
Published2021
Admission routes2
Has abstractyes

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