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Record W4246414681 · doi:10.1002/ange.202014893

Analogous Mixed Matrix Membranes with Self‐Assembled Interface Pathways

2020· article· en· W4246414681 on OpenAlex
Haozhen Dou, Mi Xu, Baoyu Wang, Zhen Zhang, Dan Luo, Benbing Shi, Guobin Wen, Mahboubeh Mousavi, Aiping Yu, Zhengyu Bai, Zhongyi Jiang, Zhongwei Chen

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.

Bibliographic record

VenueAngewandte Chemie · 2020
Typearticle
Languageen
FieldMaterials Science
TopicCovalent Organic Framework Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMembraneSelectivityChemistryEthylene glycolCovalent bondIonic bondingIonic liquidGrapheneEthyleneNanotechnologyChemical engineeringMaterials scienceChemical physicsIonOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The implementation of mixed matrix membranes (MMMs) for sub‐angstrom scale gas separations remains a grand challenge. Herein, a series of analogous mixed matrix membrane (AMMMs) were constructed via molecular‐level hybridization by utilizing a reactive ionic liquid (RIL) as the continuous phase and graphene quantum dots (GQD) as nanofiller for sub‐angstrom scale ethylene/ethane (0.416 nm/0.443 nm) separation. With a small number of GQDs (3.5 wt%) embedded in GQD/RIL AMMMs, ethylene permeability soared by 3.1‐fold, and ethylene/ethane selectivity simultaneously boosted by nearly 60 % and reached up to 99.5, which outperformed most previously reported state‐of‐the‐art membranes. Importantly, the interfacial pathway structure was visualized and their self‐assembly mechanism was revealed, where the non‐covalent interactions between RIL and GQDs induced the local arrangement of IL chains to self‐assemble into plenty of compact and superfast interfacial pathways, contributing to the combination of superhigh permeability and selectivity.

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 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 score0.009
Threshold uncertainty score0.851

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)0.0010.001

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 head0.021
GPT teacher head0.247
Teacher spread0.226 · 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