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Tailoring the Spectral Absorption Coefficient of aBlended Plasmonic Nanofluid Using a CustomizedGenetic Algorithm.

Junyong Seo1,2, Caiyan Qin1,2, Jungchul Lee1,2

  • 1Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, South Korea.

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|June 3, 2020
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Summary

This study uses a genetic algorithm to optimize plasmonic nanofluids for solar collectors. The tailored nanofluids show improved spectral absorption, enhancing solar thermal conversion efficiency.

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Area of Science:

  • Materials Science
  • Nanotechnology
  • Renewable Energy

Background:

  • Plasmonic nanofluids enhance solar thermal conversion in direct-absorption solar collectors.
  • Tuning nanoparticle absorption spectra is crucial for efficient solar energy utilization.

Purpose of the Study:

  • To tailor the spectral absorption coefficient of plasmonic nanofluids using a genetic algorithm.
  • To achieve desired absorption profiles (uniform, solar-spectrum-like, step-function-like).

Main Methods:

  • A modified genetic algorithm (GA) was developed for inverse design.
  • GA components (gene description, fitness, crossover, mutation) were adapted.
  • Blended nanofluids with six nanoparticle types were designed.

Main Results:

  • Optimal nanoparticle combinations were found for desired spectral absorption.
  • Designed nanofluids achieved target absorption distributions with 10-20% error.
  • Inhomogeneous broadening effects on optimal combinations were investigated.

Conclusions:

  • Genetic algorithms effectively tailor plasmonic nanofluid absorption spectra.
  • Optimized nanofluids show potential for improved solar thermal energy conversion.
  • Fabrication uncertainties necessitate consideration in nanoparticle selection.