Electro–optic coupling modulation on persistent photoconductivity and memristive states in thin-film devices with MoOx/ZnO heterostructured electrodes
Bibliographic record
Abstract
Persistent photoconductivity (PPC)-based devices that utilize light regulation for non-volatile memristors not only enable biological neural functions and integrate memory and computing capabilities, thereby eliminating energy consumption for signal conversion, but also mitigate Joule heating through optical control, thus promising higher energy efficiency. However, the PPC-based devices are limited to write-only operations because the photoconductivity state cannot be erased by physical means, such as applied bias voltage. In this study, we introduced a concise thin-film device with an asymmetric MoOx/ZnO heterojunction electrode structure (HES) fabricated using an economical solution process. The PPC and memristive states of the HES device can be activated via photoexcitation to a high-conductivity state and subsequently erased or reactivated by modulating the applied voltage for read/write and erasure operations. This functionality enables potential applications in flash memory with switchable memory states, thereby addressing the limitations of PPC-based devices in write-only memory. The memristive mechanism in the HES device was investigated with respect to the charge reconfiguration at the asymmetric MoOx/ZnO type-II heterointerfaces. In practical applications, the programmatically electro-optic manipulation of the HES device for read/write and erasure operations, as well as its advancement in artificial neuron image processing, were demonstrated. The modulated PPC and memristive states observed from the HES device present a new pathway for future fabrication of next-generation information storage and non-volatile logic devices.
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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) | 0.000 | 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 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".