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Evolutionary algorithms converge towards evolved biological photonic structures.

ABSTRACT: Nature features a plethora of extraordinary photonic architectures that have been optimized through natural evolution in order to more efficiently reflect, absorb or scatter light. While numerical optimization is increasingly and successfully used in photonics, it has yet to replicate any of these complex naturally occurring structures. Using evolutionary algorithms inspired by natural evolution and performing particular optimizations (maximize reflection for a given wavelength, for a broad range of wavelength or maximize the scattering of light), we have retrieved the most stereotypical natural photonic structures. Whether those structures are Bragg mirrors, chirped dielectric mirrors or the gratings on top of Morpho butterfly wings, our results indicate how such regular structures might have spontaneously emerged in nature and to which precise optical or fabrication constraints they respond. Comparing algorithms show that recombination between individuals, inspired by sexual reproduction, confers a clear advantage that can be linked to the fact that photonic structures are fundamentally modular: each part of the structure has a role which can be understood almost independently from the rest. Such an in silico evolution also suggests original and elegant solutions to practical problems, as illustrated by the design of counter-intuitive anti-reflective coatings for solar cells.

SUBMITTER: Barry MA

PROVIDER: S-EPMC7374560 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Evolutionary algorithms converge towards evolved biological photonic structures.

Barry Mamadou Aliou MA Berthier Vincent V Wilts Bodo D BD Cambourieux Marie-Claire MC Bennet Pauline P Pollès Rémi R Teytaud Olivier O Centeno Emmanuel E Biais Nicolas N Moreau Antoine A

Scientific reports 20200721 1

Nature features a plethora of extraordinary photonic architectures that have been optimized through natural evolution in order to more efficiently reflect, absorb or scatter light. While numerical optimization is increasingly and successfully used in photonics, it has yet to replicate any of these complex naturally occurring structures. Using evolutionary algorithms inspired by natural evolution and performing particular optimizations (maximize reflection for a given wavelength, for a broad rang ...[more]

PMID: 32694514

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Project description:Evolutionary computing (EC) is an area of computer sciences and applied mathematics covering heuristic optimization algorithms inspired by evolution in Nature. EC extensively study all the variety of methods which were originally based on the principles of selectionism. As a result, many new algorithms and approaches, significantly more efficient than classical selectionist schemes, were found. This is especially true for some families of special problems. There are strong arguments to believe that EC approaches are quite suitable for modeling and numerical analysis of those methods of synthetic biology and biotechnology that are known as in vitro evolution. Therefore, it is natural to expect that the new algorithms and approaches developed in EC can be effectively applied in experiments on the directed evolution of biological macromolecules. According to the John Holland's Schema theorem, the effective evolutionary search in genetic algorithms (GA) is provided by identifying short schemata of high fitness which in the further search recombine into the larger building blocks (BBs) with higher and higher fitness. The multimodularity of functional biological macromolecules and the preservation of already found modules in the evolutionary search have a clear analogy with the BBs in EC. It seems reasonable to try to transfer and introduce the methods of EC, preserving BBs and essentially accelerating the search, into experiments on in vitro evolution. We extend the key instrument of the Holland's theory, the Royal Roads fitness function, to problems of the in vitro evolution (Biological Royal Staircase, BioRS, functions). The specific version of BioRS developed in this publication arises from the realities of experimental evolutionary search for (DNA-) RNA-devices (aptazymes). Our numerical tests showed that for problems with the BioRS functions, simple heuristic algorithms, which turned out to be very effective for preserving BBs in GA, can be very effective in in vitro evolution approaches. We are convinced that such algorithms can be implemented in modern methods of in vitro evolution to achieve significant savings in time and resources and a significant increase in the efficiency of evolutionary search.

Project description:Fluorescence technology pervades all areas of chemical and biological sciences. In recent years, it is being realized that traditional fluorescence can be enriched in many ways by harnessing the power of plasmonic or photonic structures that have remarkable abilities to mold the flow of optical energy. Conventional fluorescence is omnidirectional in nature, which makes it difficult to capture the entire emission. Suitably designed emission directivity can improve collection efficiency and is desirable for many fluorescence-based applications like sensing, imaging, single molecule spectroscopy, and optical communication. By incorporating fluorophores in plasmonic or photonic substrates, it is possible to tailor the optical environment surrounding the fluorophores and to modify the spatial distribution of emission. This promising approach works on the principle of near-field interaction of fluorescence with spectrally overlapping optical modes present in the substrates. In this Account, we present our studies on directional emission with different kinds of planar metallic, dielectric, and hybrid structures. In metal-dielectric substrates, the coupling of fluorescence with surface plasmons leads to directional surface-plasmon-coupled emission with characteristic dispersion and polarization properties. In one-dimensional photonic crystals (1DPC), fluorophores can interact with Bloch surface waves, giving rise to sharply directional Bloch surface wave-coupled emission. The interaction of fluorescence with Fabry-Pérot-like modes in metal-dielectric-metal substrates and with Tamm states in plasmonic-photonic hybrid substrates provides beaming emission normal to the substrate surface. These interesting features are explained in the context of reflectivity dispersion diagrams, which provide a complete picture of the mode profiles and the corresponding coupled emission patterns. Other than planar substrates, specially fabricated plasmonic nanoantennas also have tremendous potential in controlling and steering fluorescence beams. Some representative studies by other research groups with various nanoantenna structures are described. While there are complexities to near-field interactions of fluorescence with plasmonic and photonic structures, there are also many exciting possibilities. The routing of each emission wavelength along a specific direction with a given angular width and polarization will allow spatial and spectral multiplexing. Directional emission close to surface normal will be particularly useful for microscopy and array-based studies. Application-specific angular emission patterns can be obtained by varying the design parameters of the plasmonic/photonic substrates in a flexible manner. We anticipate that the ability to control the flow of emitted light in the nanoscale will lead to the development of a new generation of fluorescence-based assays, instrumentation, portable diagnostics, and emissive devices.

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Evolutionary algorithms converge towards evolved biological photonic structures.

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Evolutionary algorithms converge towards evolved biological photonic structures.

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