Bio-inspired adaptive sensing through electropolymerization of organic\n electrochemical transistors
Bibliographic record
Abstract
Organic Electrochemical Transistors are considered today as a key technology\nto interact with biological medium through their intrinsic ionic-electronic\ncoupling. In this paper, we show how this coupling can be finely tuned (in\noperando) post-microfabrication via electropolymerization technique. This\nstrategy exploits the concept of adaptive sensing where both transconductance\nand impedance are tunable and can be modified on-demand to match different\nsensing requirements. Material investigation through Raman spectroscopy, atomic\nforce microscopy and scanning electron microscopy reveals that\nelectropolymerization can lead to a fine control of PEDOT microdomains\norganization, which directly affect the iono-electronic properties of OECTs. We\nfurther highlight how volumetric capacitance and effective mobility of\nPEDOT:PSS influence distinctively the transconductance and impedance of OECTs.\nThis approach shows to improve the transconductance by 150% while reducing\ntheir variability by 60% in comparison with standard spin-coated OECTs.\nFinally, we show how to the technique can influence voltage spike rate hardware\nclassificationwith direct interest in bio-signals sorting applications.\n
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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".