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Record W2964691042 · doi:10.1039/c9cc04851k

Formation of a thin and continuous MOF membrane with 2-D MOF nanosheets as seeds <i>via</i> layer-by-layer growth

2019· article· en· W2964691042 on OpenAlexaff
Yingnan Ma, Zhaopeng Dong, You Meng, Yufeng Zhang, Xianshe Feng, Xiaohua Ma, Jianqiang Meng

Bibliographic record

VenueChemical Communications · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsRegional Municipality of WaterlooUniversity of Waterloo
FundersNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsLayer (electronics)Layer by layerSeedingPolymerMaterials scienceChemical engineeringThin layerThin filmNanotechnologyMembraneChemistryComposite material

Abstract

fetched live from OpenAlex

Current MOF composite membranes usually suffer from unduly thick MOF layers and poor adhesion with the polymer substrate. We prepared a thin MOF film (440 nm) on a polymer support with 2-D MOF nanosheets as seeds via a layer-by-layer growth. These 2-D MOF seeds not only provided bonding between the MOF film and the polymer substrate but also facilitated the formation of a continuous and defect-free MOF membrane, which demonstrated excellent performance in gas separation.

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 score0.035
Threshold uncertainty score0.481

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 science0.0010.001
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 head0.012
GPT teacher head0.233
Teacher spread0.221 · 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

Citations71
Published2019
Admission routes1
Has abstractyes

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