Measuring and Controlling the Local Environment of Surface-Bound DNA in Self-Assembled Monolayers on Gold When Prepared Using Potential-Assisted Deposition
Bibliographic record
Abstract
DNA self-assembled monolayers (SAMs) were prepared using potential-assisted deposition on clean gold single-crystal bead electrodes under a number of conditions (constant or square-wave potential perturbations in TRIS or phosphate immobilization buffers with and without Cl – ). The local environment around the fluorophore-labeled DNA tethered to the electrode surface was characterized using in situ fluorescence microscopy during electrochemical measurements as a function of the underlying surface crystallography. Potential-assisted deposition from a TRIS buffer containing Cl – created DNA SAMs that were uniformly distributed on the surface with little preference to the underlying crystallography. A constant (+0.4 V/SCE) or a square-wave potential perturbation (+0.4 to −0.3 V/SCE, 50 Hz) resulted in similar DNA-modified surfaces in TRIS immobilization buffer. Deposition using a square-wave potential without Cl – resulted in lower DNA surface coverage. Despite this, the local environment around the DNA in the SAM appears to be densely packed. This implies the formation of clusters of densely packed DNA in the SAM. This effect was also demonstrated when depositing from a phosphate buffer. DNA clusters were significantly reduced when Cl – was present in the buffer. Clusters were most prevalent on the low-index plane surfaces (e.g., {111} and {100}) and less on the higher-index planes (e.g., {210} or {311}). A mechanism is proposed to rationalize the formation of DNA-clustered regions for deposition using a square-wave potential perturbation. The conditions for creating clusters of DNA in a SAM or for preventing these clusters from forming provide an approach for tailoring the surfaces used for biosensing.
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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) | 0.000 | 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".