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Record W2167428479 · doi:10.1002/chem.200401121

The First Studies of a Tetrathiafulvalene‐σ‐Acceptor Molecular Rectifier

2005· article· en· W2167428479 on OpenAlexaff
Gregory Ho, James R. Heath, Mykola Kondratenko, Dmitrii F. Perepichka, Karin Arseneault, Michel Pézolet, Martin R. Bryce

Bibliographic record

VenueChemistry - A European Journal · 2005
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsUniversité LavalInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsRectificationMonolayerAcceptorTetrathiafulvaleneHOMO/LUMOMoleculeMolecular orbitalCrystallographyMaterials scienceMolecular electronicsSigmaChemistryStereochemistryNanotechnologyPhysicsOrganic chemistryCondensed matter physicsQuantum mechanics

Abstract

fetched live from OpenAlex

Langmuir-Blodgett monolayers of a donor-acceptor diad TTF-sigma-(trinitrofluorene) (8) with an extremely low HOMO-LUMO gap (0.3 eV) have been used to create molecular junction devices that show rectification behavior. By virtue of structural similarities and position of molecular orbitals, 8 is the closest well-studied analogue of the model Aviram-Ratner unimolecular rectifier (TTF-sigma-TCNQ). Compressing the monolayer results in aligning the molecules, and is followed by a drastic increase in the rectification ratio. The direction of rectification depends on the electrodes used and is different in n-Si/8/Ti and Au/8/C16H33S-Hg junctions. The molecular nature of such behavior was corroborated by control experiments with fatty acids and by reversing the rectification direction with changing the molecular orientation (Au/D-sigma-A versus Au/A-sigma-D).

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.009
GPT teacher head0.210
Teacher spread0.201 · 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

Citations107
Published2005
Admission routes1
Has abstractyes

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