Internal Electric Field Modulation in Molecular Electronic Devices by Atmosphere and Mobile Ions
Bibliographic record
Abstract
The internal potential profile and electric field are major factors controlling the electronic behavior of molecular electronic junctions consisting of ∼1–10 nm thick layers of molecules oriented in parallel between conducting contacts. The potential profile is assumed linear in the simplest cases, but can be affected by internal dipoles, charge polarization, and electronic coupling between the contacts and the molecular layer. Electrochemical processes in solutions or the solid state are entirely dependent on modification of the electric field by electrolyte ions, which screen the electrodes and form the ionic double layers that are fundamental to electrode kinetics and widespread applications. The current report investigates the effects of mobile ions on nominally solid-state molecular junctions containing aromatic molecules covalently bonded between flat, conducting carbon surfaces, focusing on changes in device conductance when ions are introduced into an otherwise conventional junction design. Small changes in conductance were observed when a polar molecule, acetonitrile, was present in the junction, and a large decrease of conductance was observed when both acetonitrile (ACN) and lithium ions (Li + ) were present. Transient experiments revealed that conductance changes occur on a microsecond–millisecond time scale, and are accompanied by significant alteration of device impedance and temperature dependence. A single molecular junction containing lithium benzoate could be reversibly transformed from symmetric current–voltage behavior to a rectifier by repetitive bias scans. The results are consistent with field-induced reorientation of acetonitrile molecules and Li + ion motion, which screen the electrodes and modify the internal potential profile and provide a potentially useful means to dynamically alter junction electronic behavior.
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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".