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Record W2501515694 · doi:10.1021/acs.jpcc.6b07602

Intermediate Coherent–Incoherent Charge Transport: DNA as a Case Study

2016· article· en· W2501515694 on OpenAlexafffund
Hyehwang Kim, Michael Kilgour, Dvira Segal

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2016
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsUniversity of Toronto
FundersUniversity of TorontoNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsDelocalized electronQuantum decoherenceCharge (physics)PhysicsHamiltonian (control theory)Thermal conductionQuantumMolecular physicsQuantum mechanicsChemical physicsStatistical physics

Abstract

fetched live from OpenAlex

We study an intermediate quantum coherent-incoherent charge transport mechanism in metal-molecule-metal junctions using Büttiker’s probe technique. This tool allows us to include incoherent effects in a controlled manner, and thus to study situations in which partial decoherence affects charge transfer dynamics. Motivated by recent experiments on intermediate coherent-incoherent charge conduction in DNA molecules, we focus on two representative structures: alternating (GC) n and stacked G n C n sequences; the latter structure is argued to support charge delocalization within G segments and, thus, an intermediate coherent–incoherent conduction. We begin our analysis with a highly simplified one-dimensional tight-binding model while introducing environmental effects through Büttiker’s probes. This minimal model allows us to gain fundamental understanding of transport mechanisms and derive analytic results for molecular resistance in different limits. We then use a more detailed ladder-model Hamiltonian to represent double-stranded DNA structures, with environmental effects captured by Büttiker’s probes. We find that hopping conduction dominates in alternating sequences, while in stacked sequences charge delocalization (visualized directly through the electronic density matrix) supports significant resonant-ballistic charge dynamics reflected by an even–odd effect and a weak distance dependence for resistance. Our analysis illustrates that lessons learned from minimal models are helpful for interpreting charge dynamics in DNA.

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 score0.003
Threshold uncertainty score0.290

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 head0.006
GPT teacher head0.220
Teacher spread0.214 · 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

Citations31
Published2016
Admission routes2
Has abstractyes

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