Assembling Molecular Electronic Junctions One Molecule at a Time
Bibliographic record
Abstract
Diffusion of metal atoms onto a molecular monolayer attached to a conducting surface permits electronic contact to the molecules with minimal heat transfer or structural disturbance. Surface-mediated metal deposition (SDMD) involves contact between "cold" diffusing metal atoms and molecules, due to shielding of the molecules from direct exposure to metal vapor. Measurement of the current through the molecular layer during metal diffusion permits observation of molecular conductance for junctions containing as few as one molecule. Discrete conductance steps were observed for 1-10 molecules within a monolayer during a single deposition run, corresponding to "recruitment" of additional molecules as the contact area between the diffusing Au layer and molecules increases. For alkane monolayers, the molecular conductance measured with SDMD exhibited an exponential dependence on molecular length with a decay constant (β) of 0.90 per CH(2) group, comparable to that observed by other techniques. Molecular conductance values were determined for three azobenzene molecules, and correlated with the offset between the molecular HOMO and the contact Fermi level, as expected for hole-mediated tunneling. Current-voltage curves were obtained during metal deposition showed no change in shape for junctions containing 1, 2, and 10 molecules, implying minimal intermolecular interactions as single molecule devices transitioned into several molecules devices. SDMD represents a "soft" metal deposition method capable of providing single molecule conductance values, then providing quantitative comparisons to molecular junctions containing 10(6) to 10(10) molecules.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".