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Record W3156977953 · doi:10.1038/s41598-021-87894-5

Systematic THz study of the substrate effect in limiting the mobility of graphene

2021· article· en· W3156977953 on OpenAlexafffund
Samantha Scarfe, Wei Cui, Adina Luican‐Mayer, Jean‐Michel Ménard

Bibliographic record

VenueScientific Reports · 2021
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsGrapheneElectron mobilityMaterials scienceSubstrate (aquarium)PhotodetectionCharge carrierOptoelectronicsTerahertz radiationNanotechnologySemiconductorGraphene nanoribbonsDopingPhotodetector

Abstract

fetched live from OpenAlex

We explore the substrate-dependent charge carrier dynamics of large area graphene films using contact-free non-invasive terahertz spectroscopy. The graphene samples are deposited on seven distinct substrates relevant to semiconductor technologies and flexible/photodetection devices. Using a Drude model for Dirac fermions in graphene and a fitting method based on statistical signal analysis, we extract transport properties such as the charge carrier density and carrier mobility. We find that graphene films supported by substrates with minimal charged impurities exhibit an enhanced carrier mobility, while substrates with a high surface roughness generally lead to a lower transport performance. The smallest amount of doping is observed for graphene placed on the polymer Zeonor, which also has the highest carrier mobility. This work provides valuable guidance in choosing an optimal substrate for graphene to enable applications where high mobility is required.

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)0.008
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 score0.015
Threshold uncertainty score0.267

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.020
GPT teacher head0.284
Teacher spread0.265 · 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.

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

Citations33
Published2021
Admission routes2
Has abstractyes

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