Surface Plasmon-Driven Reversible Transformation of DNA-Bound Methylene Blue Detected In Situ by SERS
Bibliographic record
Abstract
Abstract We have reported the in situ surface–enhanced Raman spectroscopy (SERS) monitoring of repetitive surface plasmon–mediated chemical transformation cycles in a conjugate nanobiological system. The nanobiological conjugate comprised a gold-coated plasmonic substrate biofunctionalized with thiolated single–stranded DNA carrying a reduction-oxidation indicator methylthioninium chloride, which is also known as methylene blue (MB), in buffer solution at a neutral pH. Exposure to a 523-nm laser excitation produced pronounced SERS bands of oxidized MB. Continued exposure to the laser resulted in disappearance of the SERS bands, which can be interpreted as a reduction of MB. This occurred in the absence of electrochemical stimulation, chemical agents, or catalysts, suggesting a surface plasmon–mediated mechanism of the transformation. The oxidized form of MB was recovered by an addition of fresh buffer solution on the surface of the sample. Continued laser exposure with periodical addition of the buffer resulted in repetitive cycles of changes in the SERS pattern, which were monitored in situ. The chemical transformations of MB were preceded by a buildup of an intermediate SERS pattern, which was attributed to a transient form of MB created by selective surface plasmon-driven excitation.
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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 | 0.001 |
| 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".