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Record W4220921167 · doi:10.1149/2162-8777/ac6340

A Simple, Semiclassical Mechanism for Activationless, Long RangeCharge Transport in Molecular Junctions

2022· article· en· W4220921167 on OpenAlexafffund
Mustafa Supur, Richard L. McCreery

Bibliographic record

VenueECS Journal of Solid State Science and Technology · 2022
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesUniversity of Alberta
KeywordsQuantum tunnellingPhotocurrentMaterials scienceSemiclassical physicsChemical physicsMolecular orbitalMolecular wireNanowireMolecular physicsRange (aeronautics)OptoelectronicsNanotechnologyCondensed matter physicsMoleculePhysicsQuantum

Abstract

fetched live from OpenAlex

Past reports on photocurrents in molecular junctions consisting of aromatic oligomers between electrical contacts reveal very low activation energies (<1 meV) and weak distance dependence for molecular layer thicknesses of 20–60 nm. Photocurrent transport mediated by sequential tunneling between adjacent subunit orbitals represents a “super highway” for charge transport with low activation barrier, field dependence and long range of at least 60 nm. In addition to photocurrents, such transport may be involved in dark currents for distances >10 nm, previously reported biological transport across μ m in bacterial nanowires, and >1 cm in cable bacteria.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.006
GPT teacher head0.228
Teacher spread0.223 · 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 designTheoretical or conceptual
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

Citations3
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueECS Journal of Solid State Science and TechnologySame topicMolecular Junctions and NanostructuresFrench-language works237,207