Detection and sizing of nanoparticles and DNA on PDMS nanofluidic chips based on differential resistive pulse sensing
Bibliographic record
Abstract
The RPS (Resistive Pulse Sensing) technique is a popular tool for the label-free detection of particles. This paper describes a simple, cost-effective PDMS nanofluidic chip for the detection and characterization of nanoparticles based on the differential RPS technique with high resolution and sensitivity. The chip is composed of two layers of PDMS slabs. Microchannel systems fabricated by the photolithography method on the top layer are used for sample loading and differential signal acquisition, and a straight nanochannel on the bottom layer fabricated by an unconventional approach bridging the gap between the microchannels works as an RPS sensing gate. A single-stage differential amplifier is used to amplify the RPS signals when particles or DNA pass through the sensing gate. It was demonstrated that this nanofluidic RPS chip can detect nanoparticles as small as 23 nm with a high SNR (Signal-to-Noise Ratio). The experimental results also show that the device is able to distinguish nanoparticles of smaller size differences such as 60 nm and 83 nm with high resolution, showing superior performance in comparison with the results obtained from DLS (Dynamic Light Scattering). This differential nano-RPS chip was also applied to detect the translocation of dsDNA molecules.
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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".