Hardware implementation of tunable fractional-order capacitors by morphogenesis of conducting polymer dendrites
Bibliographic record
Abstract
Conventional electronics is founded on a paradigm where shaping perfect electrical elements is done at the fabrication plant, so as to make devices and systems identical, “eternally immutable.” In nature, morphogenic evolutions are observed in most living organisms and exploit topological plasticity as a low-resource mechanism for in operando manufacturing and computation. Often fractal, the resulting topologies feature an inherent disorder: a property that is never exploited in conventional electronics manufacturing, while necessary for data generation and security in software. In this study, we present how such properties can be exploited to implement long-term and evolvable synaptic plasticity in an electronic hardware. The rich topology of conducting polymer dendrites (CPDs) is exploited to program the non-ideality of their electrochemical capacitances containing constant-phase-elements. Their evolution through structural changes alters the characteristic time constants for them to charge and discharge with the applied voltage stimuli. Under a train of voltage spikes, the evolvable current relaxation of the electrochemical systems promotes short-term plasticity, with timescales ranging from milliseconds to seconds. This large window depends not only on the temporality of the voltage pulses used for reading but also on the structure of a pair of CPDs on two electrodes, grown by voltage pulses. This study demonstrates how relevant physically transient and non-ideal electrochemical components can be exploited for unconventional electronics, with the aim to mimic a universal property of living organisms, which could barely be replicated in a silicon monocrystal.
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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 | 0.000 | 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".