Energy Conversion by Nanomaterial-Based Trapezoidal-Shaped Leg of Thermoelectric Generator Considering Convection Heat Transfer Effect
Why this work is in the frame
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Bibliographic record
Abstract
Thermoelectric generators (TEGs) can harvest energy without any negative environmental impact using low potential sources, such as waste heat, and subsequently convert that energy into electricity. Different shaped leg geometries and nanostructured thermoelectric materials have been investigated over the last decades in order to improve the thermal efficiency of the TEGs. In this paper, a numerical study on the performance analysis of a nanomaterial-based (i.e., p-type leg composed of BiSbTe nanostructured bulk alloy and n-type leg composed of Bi2Te3 with 0.1 vol % SiC nanoparticles) trapezoidal-shaped leg geometry has been investigated considering the Seebeck effect, Peltier effect, Thomson effect, Fourier heat conduction, and surface to surrounding irreversible heat transfer loss. Different surface convection heat transfer losses (h) are considered to characterize the current output, power output, and thermal efficiency at various hot surface (TH) and cold surface (TC) temperatures. Good agreement has been achieved between the numerical and analytical results. Moreover, current numerical results are compared with previous related works. The designed nanomaterial-based TEG shows better performance in terms of output current and thermal efficiency with the thermal efficiency increasing from 7.3% to 8.7% using nanomaterial instead of traditional thermoelectric materials at h = 0 W/m2K while TH is 500 K and TC is 300 K.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it