Thionation Enhances the Electron Mobility of Perylene Diimide for High Performance n‐Channel Organic Field Effect Transistors
Bibliographic record
Abstract
Perylene diimides (PDIs) are one of the most widely studied n‐type materials, showing great promise as electron acceptors in organic photovoltaic devices and as electron transport materials in n‐channel organic field effect transistors. Amongst the well‐established chemical modification strategies for increasing the electron mobility of PDI, substitution of the imide oxygen atoms with sulfur, known as thionation, has remained largely unexplored. In this work, it is demonstrated that thionation is a highly effective means of enhancing the electron mobility of a bis‐N‐alkylated PDI derivative. Successive oxygen–sulfur substitution increases the electron mobility such that the fully thionated derivative (S4) has an average mobility of 0.16 cm2 V−1 s−1. This is two orders of magnitude larger than the nonthionated parent compound (P), and is achieved by solution deposition and without thermal or solvent vapor annealing. A combination of atomic force microscopy and 2D wide angle X‐ray scattering experiments, together with theoretical modeling of charge transport efficiency, is used to explain the strong positive correlation observed between electron mobility and degree of thionation. This work establishes thionation as a highly effective means of enhancing the electron mobility of PDI, and provides motivation for the development of thionated PDI derivatives for organic electronics applications.
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 | 0.000 |
| 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".