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Record W2069082990 · doi:10.1021/cm051900n

Controlling the Morphology of Methylsilsesquioxane Monoliths Using a Two-Step Processing Method

2005· article· en· W2069082990 on OpenAlexaff
Hanjiang Dong, John D. Brennan

Bibliographic record

VenueChemistry of Materials · 2005
Typearticle
Languageen
FieldMaterials Science
TopicSilicone and Siloxane Chemistry
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMaterials scienceMacroporePolymerizationMorphology (biology)ShrinkageFabricationChemical engineeringPhase (matter)MicrostructurePorosityKineticsSol-gelCapillary actionNanotechnologyComposite materialPolymerCatalysisOrganic chemistryChemistry

Abstract

fetched live from OpenAlex

A new method for fabricating methylsilsesquioxane (MSQ) materials with similar chemical composition yet easily tailored pore morphology is described. MSQ materials were formed using an acid/base two-step processing method (B2). By varying the duration of the initial acidic step, it is possible to control the size and distribution of the clusters resulting from the polymerization of methtrimethoxysilane, which affect the gelation and phase separation time in the second basic step. As a result, the microstructure of the resultant MSQ monoliths, including pore volume, pore size, and distribution of meso- and macropores, can be varied over a wide range. The origin of this phenomenon is discussed based on the sol−gel polymerization kinetics and growth models for MSQ materials. Macroporous materials show minimal shrinkage, allowing for the fabrication of monolithic columns in a 100 μm fused silica capillary with no pullaway, and indicating the potential of this highly stable material as a new chromatographic stationary phase.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.315
Teacher spread0.289 · 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 source (direct Gemma or distilled Codex), 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

Citations37
Published2005
Admission routes1
Has abstractyes

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