Hybrid Organic–Inorganic Thermoelectric Materials and Devices
Why this work is in the frame
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Bibliographic record
Abstract
Hybrid organic-inorganic materials have been considered as a new candidate in the field of thermoelectric materials since the last decade owing to their great potential to enhance the thermoelectric performance by utilizing the low thermal conductivity of organic materials and the high Seebeck coefficient, and high electrical conductivity of inorganic materials. Herein, we provide an overview of interfacial engineering in the synthesis of various organic-inorganic thermoelectric hybrid materials, along with the dimensional design for tuning their thermoelectric properties. Interfacial effects are examined in terms of nanostructures, physical properties, and chemical doping between the inorganic and organic components. Several key factors which dictate the thermoelectric efficiency and performance of various electronic devices are also discussed, such as the thermal conductivity, electric transportation, electronic band structures, and band convergence of the hybrid materials.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.008 | 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 it