Transport Properties of Thiophenes: Insights from Density-Functional Theory Modeling Using Dispersion-Correcting Potentials
Bibliographic record
Abstract
Thiophenes are an important class of materials in optoelectronics. We report on the binding energies and orbital splittings in dimers of oligothiophenes composed of monomers containing up to six rings. These data were computed using density-functional theory with dispersion-correcting potentials. Orbital splittings, obtained using the splitting-in-dimer approach, provide insight into the electronic transport character of the thiophene material. We demonstrate that the proper accounting of dispersion interactions between thiophene monomers is critical for predicting correct intermonomer separations and, therefore, accurate orbital splittings. We also show that orbital splittings increase as intermonomer distances are reduced but decrease when the monomers approach each other too closely. Oligothiophene dimers have several low-energy conformations within room-temperature thermal energy range of the minimum energy structures. Despite small differences in the energies and geometries of dimers within an oligothiophene family, large differences in orbital splitting were found. Our modeling results also revealed that orbital splittings can vary by as much as 10% as a result of low-energy vibration modes that change the relative positions of monomers within dimers. The molecular level understanding derived from this work will lead to a more rational approach to engineering organic thin film devices that will provide better device performance.
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 | 0.001 |
| 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 | 0.000 |
| 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".