Evolving random fractal Cantor superlattices for the infrared using a genetic algorithm

Jeremy A. Bossard, Lan Lin, Douglas H. Werner

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

Ordered and chaotic superlattices have been identified in Nature that give rise to a variety of colours reflected by the skin of various organisms. In particular, organisms such as silvery fish possess superlattices that reflect a broad range of light from the visible to the UV. Such superlattices have previously been identified as 'chaotic', but we propose that apparent 'chaotic' natural structures, which have been previously modelled as completely random structures, should have an underlying fractal geometry. Fractal geometry, often described as the geometry of Nature, can be used to mimic structures found in Nature, but deterministic fractals produce structures that are too 'perfect' to appear natural. Introducing variability into fractals produces structures that appear more natural. We suggest that the 'chaotic' (purely random) superlattices identified in Nature are more accurately modelled by multigenerator fractals. Furthermore, we introduce fractal random Cantor bars as a candidate for generating both ordered and 'chaotic' superlattices, such as the ones found in silvery fish. A genetic algorithm is used to evolve optimal fractal random Cantor bars with multiple generators targeting several desired optical functions in the mid-infrared and the near-infrared. We present optimized superlattices demonstrating broadband reflection as well as single and multiple pass bands in the near-infrared regime.

Original languageEnglish (US)
Article number20150975
JournalJournal of the Royal Society Interface
Volume13
Issue number114
DOIs
StatePublished - Jan 1 2016

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Biophysics
  • Bioengineering
  • Biomaterials
  • Biochemistry
  • Biomedical Engineering

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