PMMA Polymer Membrane-Based Single Cylindrical Submicron Pores: Electrical Characterization and Investigation of Their Applicability in Resistive-Pulse Biomolecule Detection
Bibliographic record
Abstract
Single cylindrical submicron pores in PMMA polymer membranes are micropatterned by electron beam lithography and integrated into all PMMA-based electrophoretic flow detector systems. Pore dimensions are 450 nm in diameter and 1 μm in length. The pores are electrically characterized in aqueous KCl electrolyte, exhibiting a stable time-independent ionic current through the pore with a noise level of less than 1% of the open-pore current. The current-voltage curves are linear and scale with electrolyte concentration. The negative surface charge of the membrane over-proportionally decreases pore conductance at low electrolyte concentrations (≤0.1 M) that are still beyond those typically applied in biological experiments. Pores do not exhibit rectification of current flowing through them, allowing for operation with either polarity. To allow for detection of yet much smaller particles, the described PMMA-based system also was successfully equipped with pores of 1.5 nm instead of 450 nm in diameter. This was achieved by introducing naturally occurring biological protein pores of α-hemolysin on a lipid bilayer into the prepatterned PMMA membrane of an assembled PMMA-based electrophoretic flow detector system. Characteristics of translocation events of single-stranded linear plasmid DNA molecules through the pores were recorded, and ionic current deductions during biomolecule translocation were clear and distinguished. Based on the presented submicron scale open pore ionic current transport properties, as well as the observed passage of DNA molecules through protein pores inserted into PMMA membranes, our current research proposes that all PMMA electrophoretic flow detectors exhibit an excellent potential for future use as biomedical resistive-pulse sensors, as long as pore dimensions match those of biomolecules to be detected.
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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 | 0.001 |
| 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".