Transverse dielectrophoretic-based DNA nanoscale confinement
Bibliographic record
Abstract
Abstract Confinement of single molecules within nanoscale environments is crucial in a range of fields, including biomedicine, genomics, and biophysics. Here, we present a method that can concentrate, confine, and linearly stretch DNA molecules within a single optical field of view using dielectrophoretic (DEP) force. The method can convert an open surface into one confining DNA molecules without a requirement for bonding, hydrodynamic or mechanical components. We use a transverse DEP field between a top coverslip and a bottom substrate, both of which are coated with a transparent conductive material. Both layers are attached using double-sided tape, defining the chamber. The nanofeatures lie at the “floor” and do not require any bonding. With the application of an alternating (AC) electric field (2 Vp-p) between the top and bottom electrodes, a DEP field gradient is established and used to concentrate, confine and linearly extend DNA in nanogrooves as small as 100-nm in width. We also demonstrate reversible loading/unloading of DNA molecules into nanogrooves and nanopits by switching frequency (between 10 kHz to 100 kHz). The technology presented in this paper provides a new method for single-molecule trapping and analysis.
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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) | 0.001 | 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".