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Record W2772892769 · doi:10.1002/adma.201705080

Graphene Inks as Versatile Templates for Printing Tiled Metal Oxide Crystalline Films

2017· article· en· W2772892769 on OpenAlexfundno aff
Muchun Liu, Po‐Yen Chen, Robert H. Hurt

Bibliographic record

VenueAdvanced Materials · 2017
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsnot available
FundersBayer CanadaNational Science Foundation
KeywordsMaterials scienceGrapheneOxideTemplateNanotechnologyMetalPorosityIntercalation (chemistry)Graphene oxide paperChemical engineeringComposite materialInorganic chemistryMetallurgy

Abstract

fetched live from OpenAlex

There is great interest in exploiting van der Waals gaps in layered materials as confinement reaction vessels to template the synthesis of new nanosheet structures. The gallery spaces in multilayer graphene oxide, for example, can intercalate hydrated metal ions that assemble into metal oxide films during thermal oxidation of the sacrificial graphene template. This approach offers limited control of structure, however, and does not typically lead to 2D atomic-scale growth of anisotropic platelet crystals, but rather arrays of simple particles directionally sintered into porous sheets. Here, a new graphene-directed assembly route is demonstrated that yields fully dense, space-filling films of tiled metal oxide platelet crystals with tessellated structures. The method relies on colloidal engineering to produce a printable "metallized graphene ink" with accurate control of metal loading, grain size/porosity, composition, and micro/nanomorphologies, and is capable of achieving higher metal-carbon ratio than is possible by intercalation methods. These tiled structures are sufficiently robust to create free standing papers, complex microtextured films, 3D shapes, and metal oxide replicas of natural biotextures.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.330
Teacher spread0.304 · 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

Citations28
Published2017
Admission routes1
Has abstractyes

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