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Record W2054457638 · doi:10.1063/1.3106611

Model for the injection of charge through the contacts of organic transistors

2009· article· en· W2054457638 on OpenAlexafffund
Pablo Lara Bullejos, J. A. Jiménez-Tejada, S. Rodrı́guez, M. Jamal Deen, Ognian Marinov

Bibliographic record

VenueJournal of Applied Physics · 2009
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsMcMaster University
FundersCanada Research Chairs
KeywordsTransistorOrganic semiconductorThin-film transistorOptoelectronicsMaterials scienceElectrodeCharge (physics)VoltageExtraction (chemistry)SemiconductorElectron mobilityChannel (broadcasting)Layer (electronics)ChemistryNanotechnologyElectrical engineeringPhysicsChromatography

Abstract

fetched live from OpenAlex

A compact model has been employed in organic thin film transistors (OTFTs) to study the electrical characteristics of the contacts, which are formed between the organic layer and source/drain electrodes of the OTFT. The model shows the importance of interrelating different physical phenomena: charge injection, redox reactions at the interface, and charge drift in the organic semiconductor. The model reproduces and explains several features that have been reported for current-voltage curves, ID-VC, at the contacts of OTFTs. The ID-VC curves are extracted from the experimental output characteristics by two techniques. One technique uses a set of transistors with different channel lengths and a simultaneous extraction of the ID-VC curve and the mobility of carriers in the channel of the transistor. When a set of transistors with different channel lengths is not available, we propose an iterative method for the simultaneous extraction of the ID-VC curve and the mobility by changing the gate bias voltages.

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 score0.271
Threshold uncertainty score0.207

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 head0.211
Teacher spread0.198 · 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

Citations51
Published2009
Admission routes2
Has abstractyes

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