MétaCan
Menu
Back to cohort

Liquid Crystal Assisted Selective Separation of Large Graphene Oxide and its Size Dependent Oxygen Reduction Catalytic Effect

2014· article· en· W1981147466 on OpenAlex
Kyung Eun Lee, Ji Eun Kim, Joon Won Lim, Sang Ouk Kim

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

VenueAdvances in science and technology · 2014
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsGrapheneMaterials scienceOxideLiquid crystalPhase (matter)DopingChemical physicsChemical engineeringCatalysisAqueous solutionDispersion (optics)NanotechnologyOrganic chemistryOpticsOptoelectronicsChemistry

Abstract

fetched live from OpenAlex

We introduce a new self-separation of graphene oxide flakes exploiting liquid crystalline phase formation. Moderately concentrated discotic GO aqueous solution spontaneously phase separates into isotropic phase and nematic phase. According to Onsager theory, larger flakes with higher aspect ratio tends to form nematic phase, while smaller flakes remain in isotropic phase. Simple isolation of bottom nematic phase (large graphene oxide; LGO) resulted in the LGO dominant dispersion preparation. We employed this size selection principle to investigate the influence of GO flake size upon the material properties of reduced graphene oxide. The electrical properties of spin cast rGO films are thoroughly investigated in terms of the GO flake sizes in the precursor aqueous dispersions. Interestingly, nitrogen doping in order to inject more electron charge carrier exhibit different behavior following flake size. Therefore, it was experimentally confirmed that quaternary nitrogen doping site acts as the dominant catalytic site in oxygen reduction reaction.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.007
Threshold uncertainty score0.282

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.006
GPT teacher head0.309
Teacher spread0.303 · 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