论文标题
使用定制的遗传算法来调整混合等离激元纳米流体的光谱吸收系数
Tailoring the Spectral Absorption Coefficient of a Blended Plasmonic Nanofluid Using a Customized Genetic Algorithm
论文作者
论文摘要
最近,血浆纳米流体(即,基础流体中等离子体纳米颗粒的悬浮液)已被广泛用于直接吸收太阳能收集器中,因为由等离激元纳米颗粒支持的局部表面等离子体可以极大地改善直接的太阳能热转化性能。考虑到金属纳米颗粒(例如金,银和铝)的表面等离子体共振频率通常位于紫外线至可见范围,因此,在广泛的光谱中,必须将等离子纳米流体的吸收系数进行光谱调节以充分调整差异辐射。在本研究中,以遗传算法(GA)形式的现代设计过程应用于等离子纳米流体的光谱吸收系数。为此,对常规GA的主要组成部分(例如基因描述,评估的适应性函数,交叉和突变功能)被修改为适合于定制等离激元纳米流体的光谱吸收系数的反问题。通过应用自定义的GA,我们获得了混合纳米流体的最佳组合,并具有吸收系数的所需光谱分布,特别是均匀分布,太阳能光谱分布和阶跃功能分布。当将六种类型的纳米颗粒混合时,设计的等离子纳米流体的吸收系数与大约10 \%至20 \%的误差的规定光谱分布非常吻合。最后,我们还研究了由纳米颗粒的制造不确定性引起的不均匀扩张效果如何改变其最佳组合。
Recently, plasmonic nanofluids (i.e., a suspension of plasmonic nanoparticles in a base fluid) have been widely employed in direct-absorption solar collectors because the localized surface plasmon supported by plasmonic nanoparticles can greatly improve the direct solar thermal conversion performance. Considering that the surface plasmon resonance frequency of metallic nanoparticles, such as gold, silver, and aluminum, is usually located in the ultraviolet to visible range, the absorption coefficient of a plasmonic nanofluid must be spectrally tuned for full utilization of the solar radiation in a broad spectrum. In the present study, a modern design process in the form of a genetic algorithm (GA) is applied to the tailoring of the spectral absorption coefficient of a plasmonic nanofluid. To do this, the major components of a conventional GA, such as the gene description, fitness function for the evaluation, crossover, and mutation function, are modified to be suitable for the inverse problem of tailoring the spectral absorption coefficient of a plasmonic nanofluid. By applying the customized GA, we obtained an optimal combination for a blended nanofluid with the desired spectral distribution of the absorption coefficient, specifically a uniform distribution, solar-spectrum-like distribution, and a step-function-like distribution. The resulting absorption coefficient of the designed plasmonic nanofluid is in good agreement with the prescribed spectral distribution within about 10\% to 20\% of error when six types of nanoparticles are blended. Finally, we also investigate how the inhomogeneous broadening effect caused by the fabrication uncertainty of the nanoparticles changes their optimal combination.