Fabrication of Well-Aligned and Highly Dense Cadmium Sulfide Nanowires on DNA Scaffolds Using the Poly(dimethylsiloxane) Transfer Method
Bibliographic record
Abstract
We have developed a simple, yet highly effective and reliable, poly(dimethylsiloxane) (PDMS) transfer method to fabricate highly dense and well-aligned CdS nanowires on silica substrates, following DNA templates. CdS nanoparticles are selectively deposited and confined on DNA strings aligned on a PDMS sheet to form CdS nanowires. The nanowires are then transferred to the substrate with a low occurrence of parasitic CdS nanoparticles. The mapping of elements in the nanowires by scanning Auger electron spectroscopy reveals the dense distribution of Cd and S elements along DNA scaffolds. The width and length of the nanowires can be controlled by adjusting the incubation time on the PDMS sheet. Atomic force microscopy and field emission scanning electron microscopy show that the height and width of the nanowires reach 45 and 77 nm, respectively, after 72 h of growth. The nanowire can continuously stretch over 10 μm after 96 h of incubation. The method is easily replicable, and controllable, which makes it promising for building nanophotoelectronic devices and nanosensors.
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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) | 0.001 | 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 | 0.001 |
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".