Module-Level Polaritonic Thermophotovoltaic Emitters via Hierarchical Sequential Learning.
Nano Lett
; 23(4): 1144-1151, 2023 Feb 22.
Article
en En
| MEDLINE
| ID: mdl-36749930
ABSTRACT
Thermophotovoltaic (TPV) generators provide continuous and high-efficiency power output by utilizing local thermal emitters to convert energy from various sources to thermal radiation matching the bandgaps of photovoltaic cells. Lack of effective guidelines for thermal emission control at high temperatures, poor thermal stability, and limited fabrication scalability are the three key challenges for the practical deployment of TPV devices. Here we develop a hierarchical sequential-learning optimization framework and experimentally realize a 6â³ module-scale polaritonic thermal emitter with bandwidth-controlled thermal emission as well as excellent thermal stability at 1473 K. The 300 nm bandwidth thermal emission is realized by a complex photon polariton based on the superposition of Tamm plasmon polariton and surface plasmon polariton. We experimentally achieve a spectral efficiency of 65.6% (wavelength range of 0.4-8 µm) with statistical deviation less than 4% over the 6â³ emitter, demonstrating industrial-level reliability for module-scale TPV applications.
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1
Colección:
01-internacional
Banco de datos:
MEDLINE
Tipo de estudio:
Guideline
Idioma:
En
Revista:
Nano Lett
Año:
2023
Tipo del documento:
Article
País de afiliación:
China