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Record W2504048461 · doi:10.1063/1.4960155

Transport properties of a highly conductive 2D Ti3C2Tx MXene/graphene composite

2016· article· en· W2504048461 on OpenAlexaff
Brahim Aïssa, Khaled A. Mahmoud, Thomas Haddad, Mourad Nedil

Bibliographic record

VenueApplied Physics Letters · 2016
Typearticle
Languageen
FieldMaterials Science
TopicMXene and MAX Phase Materials
Canadian institutionsUniversité du Québec en Abitibi-TémiscamingueMcGill UniversityUniversité TÉLUQInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsGrapheneMaterials scienceComposite numberElectron mobilityElectrical conductorElectrical resistivity and conductivityGraphene nanoribbonsComposite materialNanotechnologyOptoelectronics

Abstract

fetched live from OpenAlex

We report on the elaboration and transport properties of a sandwich like 2-dimensional Ti3C2Tx MXene/Graphene composite through alternating electrospray of MXene and graphene materials. The structural and electrical properties were systematically investigated with respect to the graphene content. The surface roughness of the samples has found to decrease considerably after the graphene integration. Electrical measurements show a clear trend to increase in both electrical conductance and Hall carrier mobility with respect to the graphene concentrations, and even reach the values of 9.5 × 104 S/cm and 54.58 cm2/V s, respectively, for only 2.5 wt. % of graphene, rendering this MXene based composite one of the most electrically conductive to date.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.021
GPT teacher head0.212
Teacher spread0.190 · 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 source (direct Gemma or distilled Codex), 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

Citations109
Published2016
Admission routes1
Has abstractyes

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