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Record W2161981098 · doi:10.1039/c3cp51379c

Organic n-type materials for charge transport and charge storage applications

2013· article· en· W2161981098 on OpenAlexaff
Monika Stolar, Thomas Baumgartner

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2013
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNanotechnologyCharge (physics)Materials scienceBattery (electricity)ElectronicsEngineering physicsOrganic electronicsElectrical engineeringEngineeringPhysicsTransistor

Abstract

fetched live from OpenAlex

Conjugated materials have attracted much attention toward applications in organic electronics in recent years. These organic species offer many advantages as potential replacement for conventional materials (i.e., silicon and metals) in terms of cheap fabrication and environmentally benign devices. While p-type (electron-donating or hole-conducting) materials have been extensively reviewed and researched, their counterpart n-type (electron-accepting or electron-conducting) materials have seen much less popularity despite the greater need for improvement. In addition to developing efficient charge transport materials, it is equally important to provide a means of charge storage, where energy can be used on an on-demand basis. This perspective is focused on discussing a selection of representative n-type materials and the efforts toward improving their charge-transport efficiencies. Additionally, this perspective will also highlight recent organic materials for battery components and the efforts that have been made to improve their environmental appeal.

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: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.015
GPT teacher head0.248
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

Citations81
Published2013
Admission routes1
Has abstractyes

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