Bibliographic record
Abstract
Organic semiconductors are promising materials for future generations of light-weight and flexible electronic devices. Several distinct functional organic semiconducting layers are usually stacked together to create a variety of devices such as organic light emitting diodes and organic solar cells. The relative alignment of each layer’s frontier molecular orbital energies with those in its adjacent layers is critical in dictating a device’s performance and functionality. With a rapidly increasing number of new functional organic semiconducting layers in modern devices, the energy level alignment (ELA) at organic-organic interfaces is becoming an increasingly crucial aspect in material selections and device design. Despite of this, there is still lack of a general scientific guideline in charting interface energy levels at such interfaces. In this thesis, a comprehensive experimental study is conducted on several dozens of organic heterointerfaces by using photoelectron spectroscopy. Broad sets of molecules having a diverse range of electronic and geometric structures were carefully selected. After correcting variables such as molecular orientation-dependent ionization energies, a general energy level alignment rule for charting interface energy levels (energy offsets and charge-transfer dipoles) over three distinct regions was found. This universal energy level alignment rule covers a wide achievable range of frontier orbital energies at organic heterojunctions, and is expected to provide a master guide in selection of new materials for fabricating future generations of superior organic semiconductor devices.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".