Preparation of ideal molecular junctions: depositing non-invasive gold contacts on molecularly modified silicon
Bibliographic record
Abstract
Recent advances in creating rectifying gold|monolayer|silicon (Au-M-Si) junctions (namely, molecular silicon diodes) are reviewed. It is known that direct deposition of gold contacts onto molecular monolayers covalently bonded to silicon surfaces causes notable disruption to the junction structure, resulting in deteriorated performance and poor reproducibility that are unsuitable for practical applications. In the past few years, several new experimental approaches have been explored to minimize or eliminate such damage, including the "indirect" evaporation method and the pre-deposition of a protective "non-penetrating" metal. To enhance the interactions at the gold-monolayer interface, head-groups that allow bonding to gold are used to maintain the monolayer integrity. Construction of the device via flip-chip lamination and the modified polymer-assisted lift-off techniques also prohibits monolayer damage. Refining the fabrication and design techniques towards reliable molecular junctions is crucial if they are to be used in nanoelectronics for the purpose of miniaturization.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".