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Record W2902947355 · doi:10.1002/pssb.201800456

Combined Ultra High Vacuum Raman and Electronic Transport Characterization of Large‐Area Graphene on SiO<sub>2</sub>

2018· article· en· W2902947355 on OpenAlexaff
Martin Hell, Yannic Falke, Andrea Bliesener, Niels Ehlen, Boris V. Senkovskiy, Thomas Szkopek, A. Grüneis

Bibliographic record

Venuephysica status solidi (b) · 2018
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsMcGill University
FundersUniversität zu Köln
KeywordsGrapheneRaman spectroscopyMaterials scienceCharacterization (materials science)Ultra-high vacuumDopingElectron mobilityOptoelectronicsAnalytical Chemistry (journal)NanotechnologyChemistryOptics

Abstract

fetched live from OpenAlex

An original experimental setup which allows for simultaneous sample characterization by Raman spectroscopy and electronic tranport in ultra‐high vacuum at low temperatures is presented. We show the applicability of this setup for the case of graphene that is transferred from an Ir(111) single crystal onto SiO 2 . The transfer of graphene is carried out using a water‐promoted electrochemical bubbling technique which is applied to graphene/Ir for the first time. The characterization prior to the transfer includes electron diffraction, photoemission spectroscopy and Raman spectroscopy using ultraviolet excitation. Following the transfer procedure, the graphene layer is electrically contacted and mounted onto a special sample carrier. This carrier allows for combined Raman and transport measurements inside an ultra high vacuum (UHV) system. UHV Raman mapping reveals a large area homogeneous graphene quality over several mm 2 characterized by a D/G intensity ratio less than 0.1. UHV electrical characterization of transferred graphene in a field effect transistor geometry yields a carrier mobility of 675 cm 2 V −1 s −1 . Upon alkali metal doping in UHV conditions using a Cs getter, a decrease of the 4‐point resistance from above 2500 Ω to below 10 Ω is observed. The presented approach paves the way for future combined UHV Raman and transport characterization of two‐dimensional materials that are doped into superconducting or charge‐density‐wave ground states.

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)0.000
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 score0.053
Threshold uncertainty score0.711

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)0.0000.000

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 head0.009
GPT teacher head0.244
Teacher spread0.236 · 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

Citations5
Published2018
Admission routes1
Has abstractyes

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