Oxygen vacancy engineering of TaO x -based resistive memories by Zr doping for improved variability and synaptic behavior
Why this work is in the frame
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Bibliographic record
Abstract
Resistive switching devices are promising emerging non-volatile memories.\nHowever, one of the biggest challenges for resistive switching (RS) memory\napplications is the device-to-device (D2D) variability which is related to the\nintrinsic stochastic formation and configuration of oxygen vacancy (VO)\nconductive filaments. In order to reduce D2D variability, the control of oxygen\nvacancy formation and configuration is paramount. We report in this study Zr\ndoping of TaOx-based RS devices prepared by pulsed laser deposition (PLD) as an\nefficient mean to reduce VO formation energy and increase conductive filament\n(CF) confinement, thus reducing D2D variability. Such findings were supported\nby X-ray photoelectron spectroscopy (XPS), spectroscopic ellipsometry (SE) and\nelectronic transport analysis. Zr doped films presented increased VO\nconcentration, and more localized VO thanks to the interaction with Zr.\nAccording to DC and pulse mode electrical characterization, D2D variability was\ndecreased by a factor of 7, resistance window was doubled and a more gradual\nand monotonic long-term potentiation/depression (LTP/LTD) in pulse switching\nwas achieved in forming-free Zr:TaOx devices thus displaying promising\nperformance for artificial synapse applications.\n
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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) | 0.000 | 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 it