Evidence map›Paper›PMID 26763335›Full record

ArticleJournal of the Royal Society, Interface2016

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

Jeremy A Bossard, Lan Lin, Douglas H Werner

Erratum issuedAbstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. The Role of Periodic Structures in Light Harvesting.Plants (Basel, Switzerland) · 2021
    Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Jeremy A BossardDepartment of Electrical Engineering, The Pennsylvania State University, 211A Electrical Engineering East, University Park, PA 16802, USA jab678@psu.edu.
Lan LinDepartment of Electrical Engineering, The Pennsylvania State University, 211A Electrical Engineering East, University Park, PA 16802, USA.
Douglas H WernerDepartment of Electrical Engineering, The Pennsylvania State University, 211A Electrical Engineering East, University Park, PA 16802, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 multi-generator 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.

Indexed as

AlgorithmsFractalsModels, BiologicalAnimalsButterfliesFishesCantor barchaotic superlatticegenetic algorithminfrared filterrandom fractal

Identifiers

PMID26763335
PMCPMC4759801

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.