Photocurrent Experiments as Probes and Prods in Large-Area Molecular Electronic Junctions
Bibliographic record
Abstract
Since its experimental realization in the late 1990s, molecular electronics (ME) has received significant attention due to its unique charge transport behavior that occurs over nanoscale dimensions. The molecular junction (MJ), wherein single molecules or arrays of parallel molecules are oriented between two metallic electrodes is the fundamental building block of ME. Specifically, temperature-independent quantum mechanical tunneling across a few nanometers in MJs is distinct from transport in organic or inorganic semiconductors and may be valuable for next-generation electronics. Although molecular tunneling junctions have been introduced commercially, fundamental questions remain about the control of charge transport in various MJs, including those containing proteins and DNA. Examples include: (i) Does molecular structure play an important role in charge transport? (ii) What is the effective barrier (tunneling or any other) for transport in MJs? (iii) Does the molecular structure remain intact during junction fabrication and operation? (iv) What charge transport mechanisms are present beyond the range of quantum tunneling? We propose a simple yet effective approach to resolve the important questions mentioned above through photocurrent experiments. In this perspective, we are showcasing various capabilities of photocurrent experiments to probe, prod, and investigate various features in MEs including internal energy barriers, in situ monitoring of the molecular structure, activationless transport over long distances, and biological charge transport.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".