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Record W2002927196 · doi:10.1109/ivnc.2014.6894758

Localized light induced thermionic emission from intercalated carbon nanotube forests

2014· article· en· W2002927196 on OpenAlexaff
Amir H. Khoshaman, Harrison D. E. Fan, Andrew T. Koch, Nathanael H. Leung, Alireza Nojeh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsThermionic emissionCarbon nanotubeCommon emitterMaterials scienceWork functionOptoelectronicsCarbon fibersCathodeCurrent densityCurrent (fluid)VoltageVoltage dropNanotechnologyChemistryElectronElectrical engineeringComposite materialPhysics

Abstract

fetched live from OpenAlex

In this work, we studied light induced thermionic emission from potassium intercalated carbon nanotube forests. Several recipes were developed for the intercalation process. The intercalated CNT forest was employed as the emitter of a light activated thermionic emission device. The resulting thermionic device was characterized by studying its current-voltage characteristics when illuminated by a focused laser beam. Based on the amount of current drop vs time, the value of workfunction reduction was estimated to be about 0.7 eV. Current-voltage characteristics were obtained at several incident light powers. Thermionic emission of potassium ions from the surface of the forest was observed at lower biases. In another set of experiments, in-situ intercalation of carbon nanotube forests was accomplished. The current-voltage characteristics were captured at different times during a period of 72 hours. It was observed that the workfunction has been reduced by 1.1 eV.

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 score0.000
Threshold uncertainty score0.002

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)0.0000.000

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 head0.011
GPT teacher head0.244
Teacher spread0.233 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

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