Models of electron transport through organic molecular monolayers self-assembled on nanoscale metallic contacts
Bibliographic record
Abstract
We propose a model of electrical conduction through self-assembled monolayers (SAM's) of organic molecules that bridge the gap between a pair of nanoscale metallic contacts. In this model each molecule bonds chemically to only one of the contacts. For dense SAM's the dominant electric current path is through two overlapping molecules each bonded to a different metal contact whereas for dilute SAM's the current flows through a single molecule. The model accounts quantitatively for the experimental data of M. A. Reed et al. [Science 278, 252 (1997)] on gold break junctions containing benzene-dithiol (BDT) SAM's, including the magnitude of the measured differential conductance. It also accounts for the striking differences between the data on the Au/BDT system and the recent measurements of J. Reichert et al. [cond-mat/0106219, 2001 (unpublished)] on a somewhat different system, namely, the strong asymmetry of the current-voltage characteristic and the larger size of the differential conductance found in latter experiments. We also present calculations of electron transport through dense and dilute SAM's of ${\mathrm{SC}}_{6}{\mathrm{H}}_{4}\mathrm{S}\ensuremath{-}{\mathrm{CH}}_{3}$ molecules. Experiments on these systems should test the validity of the proposed model.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".