Automated Fabrication of 2‐nm Solid‐State Nanopores for Nucleic Acid Analysis
Bibliographic record
Abstract
We demonstrate the automated and reproducible fabrication of sub-2-nm nanopores in 10-nm thick silicon nitride membranes, through controlled dielectric breakdown in solution. Our results reveal that under the appropriate conditions, nanopores can be fabricated with a size no larger than 2.0 ± 0.5-nm in diameter for a sample of N = 23 nanopores, with an average and standard deviation of 1.3 ± 0.6-nm. The dimensions of these nanopores are confirmed by using individual translocating DNA molecules as molecular rulers. We show that a 2.0-nm and a 2.1-nm diameter nanopore are capable of distinguishing single-stranded DNA versus double-stranded DNA, and that a 2.4-nm diameter nanopore can be used to investigate the overstretching transition in short dsDNA fragments. These results highlight the reliability and precision of the automated fabrication of nanopores via controlled dielectric breakdown, showing great promise for the manufacturing of future nanopore-based technologies.
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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 | 0.001 |
| 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) | 0.001 | 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".