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Record W3195352373 · doi:10.1002/anie.202110206

Capillary‐Bound Dense Micelle Brush Supports for Continuous Flow Catalysis

2021· article· en· W3195352373 on OpenAlexaff
Geyu Lin, Jiandong Cai, Yan Sun, Yan Cui, Qiuwen Liu, Ian Manners, Huibin Qiu

Bibliographic record

VenueAngewandte Chemie International Edition · 2021
Typearticle
Languageen
FieldChemistry
TopicNanomaterials for catalytic reactions
Canadian institutionsUniversity of Victoria
FundersScience and Technology Commission of Shanghai MunicipalityNational Natural Science Foundation of China
KeywordsBrushMicelleCapillary actionFlow (mathematics)ChemistryChemical engineeringMaterials scienceMechanicsOrganic chemistryPhysicsComposite materialEngineeringAqueous solution

Abstract

fetched live from OpenAlex

Flow reactors are appealing alternatives to conventional batch reactors for heterogeneous catalysis. However, it remains a key challenge to firmly immobilize the catalysts in a facile and flexible manner and to simultaneously maintain a high catalytic efficiency and throughput. Herein, we introduce a dense cylindrical micelle brush support in glass capillary flow reactors through a living crystallization-driven self-assembly process initiated by pre-immobilized short micelle seeds. The active hairy corona of these micellar brushes allows the flexible decoration of a diverse array of nanocatalysts, either through a direct capture process or an in situ growth method. The resulting flow reactors reveal excellent catalytic efficiency for a broad range of frequently utilized transformations, including organic reductions, Suzuki couplings, photolytic degradations, and multistep cascade reactions, and the system was both recyclable and durable. Significantly, this approach is readily applicable to long capillaries, which enables the construction of flow reactors with remarkably higher throughput.

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 categoriesInsufficient 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 score0.086
Threshold uncertainty score0.996

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)0.0050.000

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 head0.011
GPT teacher head0.247
Teacher spread0.236 · 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

Citations37
Published2021
Admission routes1
Has abstractyes

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