Charge Injection and Transport in an Isoindigo‐Based Polymer Transistor
Bibliographic record
Abstract
Abstract Polymer semiconductors hold great potential as active materials in (opto)electronic, thermoelectric, and biomedical devices. Their charge transport performance has seen tremendous progress, with mobilities exceeding 1 cm 2 V −1 s −1 for a variety of donor‐acceptor copolymers. Nevertheless, charge injection at the metal/polymer interface is still rather ineffective and poorly understood. In a field‐effect transistor, this process is manifested by the contact resistance ( R c ) which, for polymers, is several orders of magnitude higher than for their inorganic counterparts. Therefore, an in‐depth investigation of the charge injection in metal/donor‐acceptor polymer systems is sought‐after. Here, the low‐temperature dependent R c and charge transport of a model isoindigo donor‐acceptor copolymer‐based transistor are studied. The metal/polymer interface is tuned by functionalizing the electrodes with different thiolated self‐assembled monolayers (SAMs). R c in devices with SAM‐functionalized electrodes is generally lower and exhibited a weak temperature dependence. Counterintuitively, electrodes functionalized with SAMs expected to lead to an apparently unfavorable energy level alignment displayed the lowest R c . The Fermi level is found to be pinned at all the encompassed interfaces. An energy‐level alignment modeling is employed to understand this behavior. The findings reveal that simply looking at the energy levels alignment of metal/polymer interface does not necessarily lead to reduced R c .
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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 | 0.000 | 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 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".