A platform for high-bandwidth nanopore sensing with thermal control and low electrical noise
Bibliographic record
Abstract
We present an instrument capable of performing high-bandwidth (1 MHz) solid-state nanopore measurements in a temperature-controlled environment ranging from ambient to 95 °C while maintaining low electrical noise. In previous systems, the ability to control the temperature of the analyte solution during nanopore sensing has come at the expense of significantly greater electrical noise. As a consequence, increased filtering requirements or, equivalently, reduced bandwidths ultimately decrease the utility of such instruments for biosensing applications. Here, we describe in detail the system we have developed that overcomes these difficulties. In particular, we are able to precisely control the temperature of the solution in which a nanopore sensor is immersed by using a closed-loop fluidics system. The ultra-low electrical conductivity heat transfer fluid is used to bring heat from outside of the Faraday cage to the nanopore sensor within the cage, resulting in minimal electrical noise during high-bandwidth measurements while maintaining localized temperature control. As proof-of-concept, we characterize silicon nitride nanopore stability over time at elevated temperatures using electrical measurements and present single-molecule data showing the impact of temperature on capture rate, dwell time, and blockage depth. This tool can unlock the ability to perform a wide range of temperature-sensitive biophysical experiments with solid-state nanopores.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".