Depth Gradient Reduced Graphene Oxide Layer via Intense Pulsed Light Annealing Process for the Flexible Resistive Random Access Memory Device
Why this work is in the frame
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Bibliographic record
Abstract
Abstract In this study, an intense pulsed light (IPL) is irradiated for reducing graphene oxide (GO) to form a flexible resistive random access memory (ReRAM). The reduced‐GO (r‐GO) thin semiconductor layer is coated using spin coating method with distilled‐water and ethanol‐based solution on the flexible bottom electrode (Cu). The irradiation conditions are optimized to obtain high retention and switching characteristics. A top electrode (Al) is formed by deposition process and the electrical characteristics of the ReRAM are measured using a parameter analyzer. The optimally reduced GO‐based ReRAM shows write‐once read‐many times (WORM) characteristics and high electrical performances such as on/off ratio (≈10 3 ), operation voltage (−4.2–4.5 V), and excellent retention properties (retention time: 10 8 ). The effect of the IPL annealing on GO layer is analyzed using X‐ray photoelectron spectroscopy (XPS) and transmission electron microscope (TEM). In the analysis results, the depth gradient reduced GO layer is clearly observed. In addition, the switching mechanism of ReRAM is investigated using energy band diagram of ReRAM structure(Cu/GO/r‐GO/Al). This ReRAM device fabricated on flexible substrate (PI substrate) does not show the degradation in switching characteristics even after bending the substrate in 1000 times with a 5 mm bending radius, demonstrating excellent mechanical endurance of ReRAM device.
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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) | 0.001 | 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 it