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Record W2969573617 · doi:10.1002/anie.201907773

Boron Nitride Membranes with a Distinct Nanoconfinement Effect for Efficient Ethylene/Ethane Separation

2019· review· en· W2969573617 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAngewandte Chemie International Edition · 2019
Typereview
Languageen
FieldChemical Engineering
TopicAmmonia Synthesis and Nitrogen Reduction
Canadian institutionsUniversity of Waterloo
FundersNational Key Research and Development Program of ChinaNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsBoron nitrideMembraneMaterials scienceEthyleneBoronChemical engineeringSeparation (statistics)NanotechnologyChemistryOrganic chemistryEngineeringComputer scienceCatalysisBiochemistry

Abstract

fetched live from OpenAlex

Abstract A BN membrane with a distinct nanoconfinement effect toward efficient ethylene/ethane separation is presented. The horizontal and inclined self‐assembly of 2D BN nanosheets endow the BN membrane with abundant percolating nanochannels, and these nanochannels are further decorated by reactive ionic liquids (RILs) to tailor their sizes as well as to achieve nanoconfinement effect. The noncovalent interactions between RIL and BN nanosheets favor the ordered alignment of the cations and anions of RIL within BN nanochannels, which contributes to a fast and selective ethylene transport. The resultant membranes exhibit an unprecedented separation performance with superhigh C 2 H 4 permeance of 138 GPU and C 2 H 4 /C 2 H 6 selectivity of 128 as well as remarkably improved long‐term stability for 180 h, outperforming reported state‐of‐the‐art membranes.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.847
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
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 head0.026
GPT teacher head0.312
Teacher spread0.286 · 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