Electrical Resistance of Ag<sup>TS</sup>–S(CH<sub>2</sub>)<sub><i>n</i>−1</sub>CH<sub>3</sub>//Ga<sub>2</sub>O<sub>3</sub>/EGaIn Tunneling Junctions
Bibliographic record
Abstract
Tunneling junctions having the structure Ag TS –S(CH 2 ) n −1 CH 3 //Ga 2 O 3 /EGaIn allow physical–organic studies of charge transport across self-assembled monolayers (SAMs). In ambient conditions, the surface of the liquid metal electrode (EGaIn, 75.5 wt % Ga, 24.5 wt % In, mp 15.7 °C) oxidizes and adsorbs―like other high-energy surfaces―adventitious contaminants. The interface between the EGaIn and the SAM thus includes a film of metal oxide, and probably also organic material adsorbed on this film; this interface will influence the properties and operation of the junctions. A combination of structural, chemical, and electrical characterizations leads to four conclusions about Ag TS –S(CH 2 ) n −1 CH 3 //Ga 2 O 3 /EGaIn junctions. (i) The oxide is ∼0.7 nm thick on average, is composed mostly of Ga 2 O 3, and appears to be self-limiting in its growth. (ii) The structure and composition (but not necessarily the contact area) of the junctions are conserved from junction to junction. (iii) The transport of charge through the junctions is dominated by the alkanethiolate SAM and not by the oxide or by the contaminants. (iv) The interface between the oxide and the eutectic alloy is rough at the micrometer scale.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".