In‐Depth Physical Mechanism Analysis of Polymer Artificial Optoelectronic Synapse with High Endurance and Applications of Visual System and Operant Conditioning
Bibliographic record
Abstract
Abstract Being capable of dealing with both electrical signals and light, artificial optoelectronic synapses are considered to be an important cornerstone of neuromorphic computing. Here, an artificial optoelectronic synapse is reported through a simple solution process using organic poly(3‐hexylthiophene) (P3HT) and a remarkable analog switching characteristic similar to synaptic behavior is observed. The endurance and data retention capability of the P3HT‐based optoelectronic synapse exhibit stable characteristics up to 5000 consecutive cycles and 104 s. Through in‐depth physical mechanism analysis, it is confirmed that the analog switching characteristics of the device are mainly caused by a tunneling mechanism and space charge limited conduction. Furthermore, characterizations such as X‐ray photoelectron spectroscopy and atomic layer deposition prove that the memristive properties of device can be attributed to ion migration. More importantly, the device can co‐modulate the optoelectronic signal and successfully implement a photo‐triggered multi‐signal mode response. Based on this, a 3 × 3 synapse array is developed to demonstrate the potential application of the proposed P3HT‐based optoelectronic synapse in constructing an artificial visual system. Finally, operant conditioning is successfully simulated in the synaptic device. This work provides a reference for the construction of optoelectronic synapses in the neuromorphic visual system.
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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".