Monitoring of Energy Conservation and Losses in Molecular Junctions through Characterization of Light Emission
Bibliographic record
Abstract
Emission of visible light from large area molecular junctions provides a direct measure of the energy of carriers when they encounter a conducting contact and stimulate photon emission. For carbon/molecule/carbon molecular junctions containing aromatic molecular layers with thicknesses less than 5 nm, transport is elastic, and the maximum emitted photon energy (i.e., “cut‐off” energy, hvco) is equal to eVapp, where Vapp is the bias across the molecular junction. hvco increases monotonically with Vapp, is symmetric with polarity, but is weakly dependent on the nature of the contact material. Light emission from molecular junctions containing oligomeric films of anthraquinone, nitroazobenzene, naphthalene diimide, and bis‐thienyl benzene with thicknesses of 4.5–59 nm is observed as a function of bias. For layers thicker than 5–7 nm, hvco < eVapp, indicating loss of energy and therefore inelastic transport. The energy loss depends strongly on molecular structure and is linear with molecular layer thickness. When the molecular layer thickness exceeds 5–7 nm, the results provide strong evidence for a transition from elastic to inelastic transport and for stepwise, activationless transport up to 65 nm molecular layer thicknesses. Such information proves valuable for determining transport mechanisms and ultimately designing molecular junctions with desirable electronic properties.
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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 | 0.000 |
| 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".