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深度学习授权选择性太阳能吸收器的设计

Wenzhuang Ma¹, Wei Chen², Degui Li³

¹National Engineering Research Center of Electromagnetic Radiation Control Materials, Key Laboratory of Multi-spectral Absorbing Materials and Structures of Ministry of Education, University of Electronic Science and Technology of China, Chengdu, 611731, China.

Nanophotonics (Berlin, Germany)

|December 5, 2024

概括

研究人员使用深度学习和炼算法开发了一种新的选择性吸收器. 这种高性能太阳能吸收器最大限度地捕获太阳能,同时最大限度地减少热损失,为高效的太阳能热能收集铺平了道路.

科学领域:

材料科学材料科学材料科学
纳米技术纳米技术
可再生能源可再生能源是可再生能源.

背景情况:

选择性宽带吸收器对于太阳能应用至关重要.
设计吸收器以吸收太阳光谱和最小的红外辐射是具有挑战性的.
目前的设计缺乏在太阳和红外区域的快速和精确优化.

研究的目的:

为选择性吸收器开发一个高性能设计范式.
优化多层纳米结构,以提高太阳吸收和减少红外辐射.
为了证明设计的吸收器的实际应用和节能潜力.

主要方法:

结合深度学习与多目标双算法.
针对特定光学特性优化多层纳米结构.
实验性地制造并描述了设计的纳米结构吸收器.

主要成果:

取得了特殊的太阳光谱吸收 (计算/测量 = 0.98/0.94).
证明了低的平均红外辐射率 (计算/测量 = 0.08/0.19).
有可能每年节省大量能源 (高达1743千瓦时/米2/年).

结论:

这项研究提出了一种用于采集太阳能热能的强大设计方法.
开发的吸收器在将太阳辐射转化为热量方面表现出高效率.
这种方法促进了太阳能和其他工程领域的更广泛应用.

关键词:

这是深度学习.metasurface 地表的表面是什么太阳能吸收器可以吸收太阳能

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