MétaCan
Menu
Back to cohort
Record W2519308444 · doi:10.1021/acs.chemmater.6b02153

Installing Stable Molecular Chirality within the Walls of Periodic Mesoporous Organosilicas via Self-Assembly

2016· article· en· W2519308444 on OpenAlexafffund
Lacey M. Reid, Cathleen M. Crudden

Bibliographic record

VenueChemistry of Materials · 2016
Typearticle
Languageen
FieldMaterials Science
TopicMesoporous Materials and Catalysis
Canadian institutionsQueen's University
FundersDivision of Materials ResearchNatural Sciences and Engineering Research Council of Canada
KeywordsChirality (physics)DopantCircular dichroismMaterials scienceMesoporous organosilicaMesoporous materialMoleculeMonomerHydrothermal synthesisSelf-assemblyNanotechnologyCrystallographyHydrothermal circulationDopingChemical engineeringChemistryOrganic chemistryPolymerMesoporous silicaComposite materialCatalysisChiral symmetry

Abstract

fetched live from OpenAlex

The synthesis of highly ordered chiral periodic mesoporous organosilica (PMO) materials is described using a novel approach. Chiral dopants featuring removable chirality were combined with freely rotating bulk monomers, resulting in a bulk chiral material with handedness related to the chiral dopant. Once incorporated into the PMO, removal of the chiral-linker in the dopant is readily accomplished and occurs with complete preservation of the circular dichroism signal in the PMO material, whereas in the precursor molecule, this transformation would lead to a total loss of chirality. The chirality of the PMO material is retained even after prolonged hydrothermal treatment, indicating stable chirality induction within the walls of solid PMO.

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 score0.000
Threshold uncertainty score0.001

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 integrity0.0000.000
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 head0.007
GPT teacher head0.215
Teacher spread0.208 · 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

Citations8
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueChemistry of MaterialsSame topicMesoporous Materials and CatalysisFrench-language works237,207