The increasing demand for versatile and high-quality near-field radiative heat transfer(NFRHT) has created a critical need for a design approach that can handle numerous candidate structures. In this work, we employ a...The increasing demand for versatile and high-quality near-field radiative heat transfer(NFRHT) has created a critical need for a design approach that can handle numerous candidate structures. In this work, we employ and develop an adaptive hybrid Bayesian optimization(AHBO) algorithm to design the high-quality quasi-monochromatic NFRHT. The candidate materials include hexagonal boron nitride, silicon carbide, and doped silicon. The high-quality quasi-monochromatic NFRHT is optimized over 1.0 × 10^(8) candidate structures to maximize the evaluation factor. It is worth noting that only 2.6% of the candidate structures needed to be calculated to identify the optimal structure. The optimal structure of quasi-monochromatic NFRHT is an aperiodic multilayer metamaterial that differs from conventional periodic multilayer structures. Moreover, we investigate the robustness and mechanisms of the optimal quasi-monochromatic NFRHT with respect to the vacuum gap distance and the temperature difference between the emitter and receiver. In addition, the high-quality multi-peak NFRHT is designed using the AHBO algorithm by improving the definition of the evaluation factor. The results demonstrate that the AHBO algorithm is efficient in designing high-quality quasi-monochromatic and multi-peak NFRHT, and it can be further expanded to other structural designs in the field of energy conversion.展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos. 52120105009 and 51906144)the Science and Technology Commission of Shanghai Municipality (Grant Nos. 20JC1414800 and 22ZR1432900)the Open Fund of Key Laboratory of Thermal Management and Energy Utilization of Aircraft of Ministry of Industry and Information Technology (Grant No. CEPE2020015)。
文摘The increasing demand for versatile and high-quality near-field radiative heat transfer(NFRHT) has created a critical need for a design approach that can handle numerous candidate structures. In this work, we employ and develop an adaptive hybrid Bayesian optimization(AHBO) algorithm to design the high-quality quasi-monochromatic NFRHT. The candidate materials include hexagonal boron nitride, silicon carbide, and doped silicon. The high-quality quasi-monochromatic NFRHT is optimized over 1.0 × 10^(8) candidate structures to maximize the evaluation factor. It is worth noting that only 2.6% of the candidate structures needed to be calculated to identify the optimal structure. The optimal structure of quasi-monochromatic NFRHT is an aperiodic multilayer metamaterial that differs from conventional periodic multilayer structures. Moreover, we investigate the robustness and mechanisms of the optimal quasi-monochromatic NFRHT with respect to the vacuum gap distance and the temperature difference between the emitter and receiver. In addition, the high-quality multi-peak NFRHT is designed using the AHBO algorithm by improving the definition of the evaluation factor. The results demonstrate that the AHBO algorithm is efficient in designing high-quality quasi-monochromatic and multi-peak NFRHT, and it can be further expanded to other structural designs in the field of energy conversion.
