Self‐assembled gold nanoparticle–molecular electronic networks
Bibliographic record
Abstract
Electronic transport through self‐assembled networks consisting of colloidal gold particles interconnected with thiolated alkane molecules is studied using a combination of broad area and scanning probe microscope‐based measurements. The molecule–gold nanoparticle ratio and/or type of molecules is used to alter electronic transport paths through the network and allow the resistance to be controllably tuned by several orders of magnitude (∼105–1011 ohms for the structures studied). Local probing and imaging of the colloidal gold networks via atomic force microscopy is able to detect the presence of molecular connections and also indicates that the number of molecules is important for achieving good network packing with a minimum ratio of molecules to particles between 1:1 and 5:1 found to be needed in order to form well‐connected molecular electronic circuits. Circuit simulations used to model the electrical behavior of the self‐assembled nanoscale networks based on different morphologies and dimensions show good agreement with experiment and provide a guide for engineering network properties using superstructures of different molecules. These results demonstrate directed self‐assembly as a potential avenue for the creation of molecular integrated circuits.
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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".