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Record W2514822124 · doi:10.1063/1.4962009

Operation mechanism of high performance organic permeable base transistors with an insulated and perforated base electrode

2016· article· en· W2514822124 on OpenAlexfundno aff
Felix Kaschura, Axel Fischer, Markus P. Klinger, Duy Hai Doan, Thomas Koprucki, Annegret Glitzky, Daniel Kasemann, Johannes Widmer, Karl Leo

Bibliographic record

VenueJournal of Applied Physics · 2016
Typearticle
Languageen
FieldEngineering
TopicOrganic Electronics and Photovoltaics
Canadian institutionsnot available
FundersEinstein Stiftung BerlinDeutsche ForschungsgemeinschaftSeventh Framework ProgrammeCanadian Institute for Advanced Research
KeywordsTransistorCurrent (fluid)ElectrodeOptoelectronicsMaterials scienceFabricationBase (topology)Current densityDiffusionLimiting currentVoltageElectrical engineeringChemistryEngineeringPhysics

Abstract

fetched live from OpenAlex

The organic permeable base transistor is a vertical transistor architecture that enables high performance while maintaining a simple low-resolution fabrication. It has been argued that the charge transport through the nano-sized openings of the central base electrode limits the performance. Here, we demonstrate by using 3D drift-diffusion simulations that this is not the case in the relevant operation range. At low current densities, the applied base potential controls the number of charges that can pass through an opening and the opening is the current limiting factor. However, at higher current densities, charges accumulate within the openings and in front of the base insulation, allowing for an efficient lateral transport of charges towards the next opening. The on-state in the current-voltage characteristics reaches the maximum possible current given by space charge limited current transport through the intrinsic semiconductor layers. Thus, even a small effective area of the openings can drive huge current densities, and further device optimization has to focus on reducing the intrinsic layer thickness to a minimum.

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 score0.043
Threshold uncertainty score0.445

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 head0.004
GPT teacher head0.159
Teacher spread0.155 · 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

Citations26
Published2016
Admission routes1
Has abstractyes

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