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Record W1970580084 · doi:10.1063/1.3211958

Photocurrent generation in random networks of multiwall-carbon-nanotubes grown by an “all-laser” process

2009· article· en· W1970580084 on OpenAlexaff
My Alı El Khakani, Vincent Le Borgne, Brahim Aïssa, Federico Rosei, C. Scilletta, E. Speiser, Manuela Scarselli, P. Castrucci, M. De Crescenzi

Bibliographic record

VenueApplied Physics Letters · 2009
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsPhotocurrentCarbon nanotubeMaterials scienceOptoelectronicsPhotoconductivitySchottky diodeUltravioletVoltageBiasingLaserSchottky barrierNanotechnologyOpticsElectrical engineering

Abstract

fetched live from OpenAlex

We report photocurrent generation in entangled networks of multiwall-carbon nanotubes (MWCNTs) grown on TiN/Si substrates by an all-laser process. By integrating these MWCNTs into planar devices, we demonstrate that they generate photocurrent over all the visible and near-ultraviolet range, with maximum efficiency around 420 nm. Photocurrent is obtained even at zero applied voltage, pointing to a true photovoltaic (PV) effect. The extracted photocurrent as a function of applied voltage exhibits nonlinear behavior for voltages ≥2 V, suggesting that the devices do not behave as pure photoresistances. Other mechanisms (e.g., Schottky barriers imbalance) are invoked to describe current flow in these PV devices.

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 categoriesMeta-epidemiology (narrow)
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 score0.031
Threshold uncertainty score1.000

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 head0.013
GPT teacher head0.250
Teacher spread0.237 · 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

Citations27
Published2009
Admission routes1
Has abstractyes

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