Rapidly prototyped multi-scale electrodes to minimize the voltage requirements for bacterial cell lysis
Bibliographic record
Abstract
Lab-on-a-chip systems used for nucleic acid based detection of bacteria rely on bacterial lysis for the release of cellular material. Although electrical lysis devices can be miniaturized for on-chip integration and reagent-free lysis, they often suffer from high voltage requirements, and rely on the use of off-chip voltage supplies. To overcome this barrier, we developed a rapid prototyping method for creating multi-scale electrodes that are structurally tuned for lowering the voltage needed for electrical bacterial lysis. These three-dimensional multi-scale electrodes – with micron scale reaction areas and nanoscale features – are fabricated using benchtop methods including craft cutting, polymer-induced wrinkling, and electrodeposition, which enable a lysis device to be designed, fabricated, and optimized in a matter of hours. These tunable electrodes show superior behaviour compared to lithographically-prepared electrodes in terms of lysis efficiency and voltage requirement. Successful extraction of nucleic acids from bacterial samples processed by these electrodes demonstrates the potential for these rapidly prototyped devices to be integrated within practical lab-on-a-chip systems.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".