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Record W2587653276 · doi:10.1063/1.4981022

Controlling charge transport mechanisms in molecular junctions: Distilling thermally induced hopping from coherent-resonant conduction

2017· article· en· W2587653276 on OpenAlexafffund
Hyehwang Kim, Dvira Segal

Bibliographic record

VenueThe Journal of Chemical Physics · 2017
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsQuantum tunnellingCondensed matter physicsDelocalized electronSuperexchangeConductanceThermal conductionVariable-range hoppingElectronMaterials scienceChemistryPhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

The electrical conductance of molecular junctions may depend strongly on the temperature and weakly on molecular length, under two distinct mechanisms: phase-coherent resonant conduction, with charges proceeding via delocalized molecular orbitals, and incoherent thermally assisted multi-step hopping. While in the case of coherent conduction, the temperature dependence arises from the broadening of the Fermi distribution in the metal electrodes, in the latter case it corresponds to electron-vibration interaction effects on the junction. With the objective to distill the thermally activated hopping component, thus exposing intrinsic electron-vibration interaction phenomena on the junction, we suggest the design of molecular junctions with "spacers," extended anchoring groups that act to filter out phase-coherent resonant electrons. Specifically, we study the electrical conductance of fixed-gap and variable-gap junctions that include a tunneling block, with spacers at the boundaries. Using numerical simulations and analytical considerations, we demonstrate that in our design, resonant conduction is suppressed. As a result, the electrical conductance is dominated by two (rather than three) mechanisms: superexchange (deep tunneling) and multi-step thermally induced hopping. We further exemplify our analysis on DNA junctions with an A:T block serving as a tunneling barrier. Here, we show that the electrical conductance is insensitive to the number of G:C base-pairs at the boundaries. This indicates that the tunneling-to-hopping crossover revealed in such sequences truly corresponds to the properties of the A:T barrier.

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 score0.118
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 head0.013
GPT teacher head0.217
Teacher spread0.204 · 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

Citations32
Published2017
Admission routes2
Has abstractyes

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