Precise parameter extraction technique for organic thin-film transistors operating in the linear regime
Bibliographic record
Abstract
We demonstrate a precise parameter extraction for organic thin-film transistors (OTFTs) operating in the linear regime. The precision is achieved by utilizing the mathematical functions YVG and HVG that are derived from measured current-voltage (I–V) characteristics, in a proper sequence. The YVG function compensates for the impact of the contact resistance Rc on the I–V characteristics of the OTFT. The HVG function applied on the YVG function is used to determine the mobility enhancement factor γ > 0, which allows for defining the γYVG function for OTFT that is linearly proportional to the gate-overdrive voltage (VG–VT). The linearity of the γYVG function allows for extraction of the threshold voltage VT and the mobility μ in the OTFT. Using the extracted parameters, the reduction of the experimental data for drain-source resistance with the resistance model for the intrinsic channel allows for accurate determination of RC. The precision of the extraction technique is verified by re-simulation that uses the extracted values of the parameters, and the re-simulation accurately replicates the measurement of the current and the transconductance of the OTFT.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".