Bibliographic record
Abstract
This thesis creates a numerical simulation scheme for a coupled ionic electronic device and uses it to simulate a memristor based on an organic conductor called poly(3,4 ethylenedioxythiophene):polystyrenesulfonate (PEDOT:PSS).The modeled memristor consists of a thin PEDOT:PSS strip with a metal contact on both sides and a drop of an electrolyte solution with lithium and perchlorate ions.The conductivity of the memristor changes when the lithium ions in the electrolyte dedopes the PEDOT:PSS by bonding with PSS polymers.A numerical drift diffusion and a Poisson solver was implemented with special features to model the physical properties of the memristor.The developed simulation algorithm was tested using analytical solutions to the drift diffusion equations and Poisson's equation.1-D and 2-D simulations were able to capture the essential physical effects.The comparison of 2-D simulations and the experimental results showed that proposed model worked as expected and produced results that were similar to an actual memristor.The work presented in this thesis showed promising results for the simulation of a memristor which can be improved in the future by additional modeling of the charge transport mechanisms.υ Drift Speed m/sx
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".