Strong Magnetic Field Annealing for Improved Phthalocyanine Organic Thin‐Film Transistors
Bibliographic record
Abstract
Thin-film microstructure, morphology, and polymorphism can be controlled and optimized to improve the performance of carbon-based electronics. Thermal or solvent vapor annealing are common post-deposition processing techniques; however, it can be difficult to control or destructive to the active layer or substrates. Here, the use of a static, strong magnetic field (SMF) as a non-destructive process for the improvement of phthalocyanine (Pc) thin-film microstructure, increasing organic thin-film transistor (OTFTs) mobility by twofold, is demonstrated. Grazing incident wide-angle X-ray scattering (GIWAXS), X-ray diffraction (XRD), and atomic force microscopy (AFM) elucidate the effect of SMF on both para- and diamagnetic Pc thin-films when subjected to a magnetic field. A SMF is found to increase the concentration of oxygen-induced radical species within the Pc thin-film, lending a paramagnetic character to ordinarily diamagnetic metal-free Pc and resulting in magnetic field induced changes to its thin-film microstructures. In a nitrogen environment, without competing degradation effects of molecular oxygen, SMF processing is found to favorably improve charge transport characteristics and increase OTFT mobility. Thus, post-deposition thin-film annealing with a magnetic field is presented as an alternative and promising technique for future thin-film engineering applications.
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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 | 0.000 | 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) | 0.001 | 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".