Evolutionary Computation for Parameter Extraction of Organic Thin-Film Transistors Using Newly Synthesized Liquid Crystalline Nickel Phthalocyanine
Bibliographic record
Abstract
In this work, the topic of the detrimental contact effects in organic thin-film transistors (OTFTs) is revisited. In this case, contact effects are considered as a tool to enhance the characterization procedures of OTFTs, achieving more accurate values for the fundamental parameters of the transistor threshold voltage, carrier mobility and on-off current ratio. The contact region is also seen as a fundamental part of the device which is sensitive to physical, chemical and fabrication variables. A compact model for OTFTs, which includes the effects of the contacts, and a recent proposal of an associated evolutionary parameter extraction procedure are reviewed. Both the model and the procedure are used to assess the effect of the annealing temperature on a nickel-1,4,8,11,15,18,22,25-octakis(hexyl)phthalocyanine (NiPc6)-based OTFT. A review of the importance of phthalocyanines in organic electronics is also provided. The characterization of the contact region in NiPc6 OTFTs complements the results extracted from other physical–chemical techniques such as differential scanning calorimetry or atomic force microscopy, in which the transition from crystal to columnar mesophase imposes a limit for the optimum performance of the annealed OTFTs.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".