In-Situ Optical Absorbance Spectroscopy of Molecular Layers in Carbon Based Molecular Electronic Devices
Bibliographic record
Abstract
In-situ optical absorbance spectroscopy was used to monitor transparent carbon based molecular electronic junctions with various molecular and metal oxide layers. Junctions with molecular layers consisting of N -decylamine (C 10 N) and fluorene (FL) did not show absorbance changes upon the application of voltage pulses. Junctions with molecular layers consisting of 4-nitroazobenzene (NAB) and 9,10-anthraquinone (AQ) showed absorbance changes upon the application of voltage pulses which were reversible for at least tens of cycles. For NAB junctions, a negative voltage pulse caused an increase in absorbance at 410 nm and a decrease in absorbance at 360 nm. For AQ junctions, a negative voltage pulse caused an absorbance increase at 395 nm and a decrease in absorbance at 320−350 nm. These absorbance changes are consistent with the reduction of the NAB and AQ layers when the carbon substrate is biased negative. Positive voltage pulses reversed the absorbance changes observed during a negative pulse which is consistent with the reoxidation of the molecular layer. The persistence of the absorbance changes depended strongly on the molecule, with absorbance changes persisting for tens of minutes for NAB junctions but only several seconds for AQ junctions. The in-situ optical absorption results are supported with solution based electrochemistry of both free molecules and chemisorbed molecular layers and time-dependent density functional theory. We have shown that in-situ optical absorbance spectroscopy can be used to probe changes in energy levels through absorption changes in biased molecular junctions, which should be useful for deducing structural and electronic changes that strongly effect electron transfer in molecular electronic devices.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".