Simple hybrid current-voltage source for the characterization of organic light-emitting devices
Bibliographic record
Abstract
Some organic light-emitting devices (OLEDs) behave better and longer when driven with alternating bias. It is believed that the reverse bias helps to remove the trapped charges and prevents permanent drift of ionic dopants or ion migration from electrodes. OLEDs behave much like diodes. When driven with a voltage source, the highly asymmetrical exponential I-V curve of diodes makes the accurate control of the forward current difficult. Using a voltage-controlled current source, the voltage can constantly adjust to maintain the desired current through the device. The reverse resistance of a diode is large. Using a current source to reverse bias can produce a large reverse voltage that would destroy the junction. In this article we present an electronic device used to drive and characterize organic light-emitting devices. It consists of a high voltage (±225V) hybrid source, which alternatively generates direct voltage-controlled current pulses, up to 200 mA, and reverse voltage-controlled voltage pulses. Furthermore, it allows simultaneous measurement of both, direct and reverse, current and voltage. This hybrid source, driven by an arbitrary wave form generator, makes possible the dynamical characterization of OLED when submitted to a wide variety of current and voltage signals.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".