Charge transport in molecular junctions: From tunneling to hopping with\n the probe technique
Bibliographic record
Abstract
We demonstrate that a simple phenomenological approach can be used to\nsimulate electronic conduction in molecular wires under thermal effects induced\nby the surrounding environment. This "Landauer-B\\"uttiker's probe technique"\ncan properly replicate different transport mechanisms: phase coherent\nnonresonant tunneling, ballistic behavior, and hopping conduction, to provide\nresults consistent with experiments. Specifically, our simulations with the\nprobe method recover the following central characteristics of charge transfer\nin molecular wires: (i) The electrical conductance of short wires falls off\nexponentially with molecular length, a manifestation of the tunneling\n(superexchange) mechanism. Hopping dynamics overtakes superexchange in long\nwires demonstrating an ohmic-like behavior. (ii) In off-resonance situations,\nweak dephasing effects facilitate charge transfer. Under large dephasing the\nelectrical conductance is suppressed. (iii) At high enough temperatures,\n$k_BT/\\epsilon_B>1/25$, with $\\epsilon_B$ as the molecular-barrier height, the\ncurrent is enhanced by a thermal activation (Arrhenius) factor. However, this\nenhancement takes place for both coherent and incoherent electrons and it does\nnot readily indicate the underlying mechanism. (iv) At finite-bias, dephasing\neffects impede conduction in resonant situations. We further show that memory\n(non-Markovian) effects can be implemented within the Landauer-B\\"uttiker's\nprobe technique to model the interaction of electrons with a structured\nenvironment. Finally, we examine experimental results of electron transfer in\nconjugated molecular wires and show that our computational approach can\nreasonably reproduce reported values to provide mechanistic information.\n
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".