Achieving Ultrahigh n‐Type Thermoelectric Power Factor in an Intrinsically Large Transport‐Fermi Energy Gap Conjugated Polymer
Bibliographic record
Abstract
Abstract The conductivity of organic thermoelectric materials has seen significant improvements in the past few years, but often at the expense of the Seebeck coefficient. Consequently, the thermoelectric performance, especially for n‐type materials, remains considerably lower than that of their inorganic counterparts. Herein, a high‐performance n‐type thermoelectric polymer, P(TDPP‐BT‐LEG) is reported, with an unexpectedly high Seebeck coefficient and ultrahigh power factor, driven by its intrinsically large energy gap between the Fermi and transport energy levels and high charge carrier mobility. Notably, it is shown that strong electrostatic interactions induced by the ethylene glycol side chains facilitate charge transfer between the dopants and the polymer. This enables effective doping of polymers with high LUMO levels. Furthermore, efficient charge transport, arising from favorable molecular packing, allows the polymer to maintain high electrical conductivity even at low charge carrier concentrations. Ultimately, this polymer achieves a record‐high n‐type power factor of 397 µW m −1 K −2 , with a high Seebeck coefficient of −420 µV K ‒1 . This study highlights the potential of enhancing the Seebeck coefficient through precise energy level tuning and molecular design, fundamentally advancing the rational design of high‐performance organic thermoelectric materials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".