Metal Cation-Induced Deformation of DNA Self-Assembled Monolayers on Silicon: Vibrational Sum Frequency Generation Spectroscopy
Bibliographic record
Abstract
Nucleic acids possess charged phosphate groups in their backbones, which require counterions to reduce the repulsive Coulombic interactions between the strands. Herein we report how different mono- and divalent metal cations influence the molecular orientations of DNA molecules on silicon surfaces upon immobilization and hybridization. Our sum frequency generation (SFG) spectroscopy studies demonstrated that the degree of conformational variation of DNA self-assembled monolayers on silicon depends on the type of metal cations present. The molecular orientation change of immobilized single-stranded oligonucleotides correlates with DNA-cation affinity (Mg(2+) > Ca(2+) > K(+) approximately Na(+)): metal cations with the strongest affinity disrupt the structure of the underlying linker monolayer the most. Upon hybridization the trend is reversed, which is attributed to the greater ability of divalent cations to mask the negative charges on the DNA backbone. These findings provide useful information for the construction of more sensitive DNA biosensors, particularly the optimization of on-chip hybridization performance.
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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".