In silico design of metal-dielectric nanocomposites for solar energy applications

Justin Trice, Hernando Garcia, Radhakrishna Sureshkumar, Ramki Kalyanaraman

Research output: Chapter in Book/Entry/PoemConference contribution

7 Scopus citations


Recently, a homogenization procedure has been proposed, based on the tight lower bounds of the BergmanMilton formulation, and successfully applied to dilute ternary nanocomposites to predict optical data without using any fitting parameters [Garcia et al. Phys. Rev. B, 75, 045439 (2007)]. The procedure has been extended and applied to predict the absorption coefficient of a quaternary nanocomposite consisting of Cu, Ag, and Au nanospheres embedded in a SiO 2 host matrix. Significant enhancement of the absorption coefficient is observed over the spectral range 350-800 nm. The magnitude of this enhancement can be controlled by varying the nanosphere diameter and the individual metal volume fraction with respect to the host matrix. We have determined the optimal composition resulting in enhanced broadband (350nm-800nm) absorption of the solar spectrum using a simulated annealing algorithm. Fabricating such composite materials with a desired optical absorption has potential applications in solar energy harvesting.

Original languageEnglish (US)
Title of host publicationInstrumentation, Metrology, and Standards for Nanomanufacturing
StatePublished - 2007
Externally publishedYes
EventInstrumentation, Metrology, and Standards for Nanomanufacturing - San Diego, CA, United States
Duration: Aug 29 2007Aug 30 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherInstrumentation, Metrology, and Standards for Nanomanufacturing
Country/TerritoryUnited States
CitySan Diego, CA


  • Absorption coating
  • Nanocomposite
  • Optimization
  • Simulated annealing
  • Solar

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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