Experimental Investigation of Dielectrophoretic Behavior of Myoglobin and Silica Particles on a Microelectrode Chip
Bibliographic record
Abstract
Dielectrophoresis (DEP) is one of the nondestructive electrokinetic techniques that has immense capability for manipulating nano-sized biomolecules like myoglobin. The present study investigates the behavior of myoglobin molecules on a microelectrode surface under the influence of dielectrophoresis. Microelectrodes are fabricated in transparent borofloat glass wafers with a sequence of microfabrication steps like piranha cleaning, metal deposition, optical lithography and etching. A detailed description of experimental setup to conduct DEP experiments on myoglobin is presented with a brief overview of myoglobin preparation. Silica particles are used to mimic the myoglobin molecules. Both positive DEP and negative DEP effects on silica particles is observed and positive DEP effect on myoglobin is also observed. Positive DEP on silica particles is observed at applied voltage range of 5–10V and frequency range of DC to 1KHz. Negative DEP effect on silica particles is observed at 10V applied voltage and 10KHz to 40KHz frequency range. The positive DEP effect of myoglobin is observed at applied voltage of 5V and frequency of 5kHz.
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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 | 0.001 | 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".