MétaCan
Menu
Back to cohort
Record W2124696918 · doi:10.1002/adfm.200500151

Hybrid Periodic Mesoporous Organosilicas

2005· article· en· W2124696918 on OpenAlexaff
Wesley Whitnall, Tewodros Asefa, Geoffrey A. Ozin

Bibliographic record

VenueAdvanced Functional Materials · 2005
Typearticle
Languageen
FieldMaterials Science
TopicMesoporous Materials and Catalysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSilsesquioxaneMesoporous organosilicaMesoporous materialMaterials scienceMoietyHybrid materialMesoporous silicaMonolayerNanotechnologyChemical engineeringOrganic chemistryComposite materialCatalysisPolymerChemistry

Abstract

fetched live from OpenAlex

Abstract In this study we report the synthesis of a new class of materials called hybrid periodic mesoporous organosilicas (HPMOs). By coupling a silsesquioxane precursor through at least two chemical linkages to the mesopore walls of a pre‐existing periodic mesoporous silica (PMS) or periodic mesoporous organosilica (PMO). Many of the problems of a conventional PMO material can be avoided while ensuring efficient use of the bridging organic functional groups of the silsesquioxane. We demonstrate this concept for PMS by anchoring various silsesquioxanes, such as ethene and ethane silsesquioxanes, to the mesopore walls of the PMS. The addition of anchored silsesquioxane monolayers and multilayers to the mesopore walls also allows for the strict control of the diameter of the mesopore as well as the mesopore wall thickness in the final HPMO material. Additionally it is shown that having the silsesquioxane located solely on the surface of the mesopores in HPMOs gives increased chemical accessibility of the organic bridge‐bonded moiety when compared with their PMO counterparts containing the bridge‐bonded organic both on the surface and within the pore walls.

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 categoriesMeta-epidemiology (narrow), Insufficient 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 score0.044
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0520.008

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 head0.009
GPT teacher head0.222
Teacher spread0.213 · 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

Citations50
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueAdvanced Functional MaterialsSame topicMesoporous Materials and CatalysisFrench-language works237,207